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Despite the pandemic’s disruptions, MIT’s research community still found a way to generate a number of impressive research breakthroughs in 2021. In the spirit of reflection that comes with every new orbit around the sun, below we count down 10 of the most-viewed research stories on MIT News from the past year.

We’ve also rounded up the year’s top MIT community-related stories .

10. Giving cancer treatment a recharge . In October, researchers discovered a way to jump-start the immune system to attack tumors. The method combines chemotherapy and immunotherapy to spur immune cells into action. The researchers hope it could allow immunotherapy to be used against more types of cancer.

9. Generating 3D holograms in real-time . Computer scientists developed a deep-learning-based system that allows computers to create holograms almost instantly. The system could be used to create holograms for virtual reality, 3D printing, medical imaging, and more — and it’s efficient enough to run on a smartphone.

8. Creating inhalable vaccines . Scientists at the Koch Institute developed a method for delivering vaccines directly to the lungs through inhalation. The new strategy induced a strong immune response in the lungs of mice and could offer a quicker response to viruses that infect hosts through mucosal surfaces.

7. Assessing Covid-19 transmission risk . Two MIT professors proposed a new approach to estimating the risks of exposure to Covid-19 in different indoor settings. The guidelines suggest a limit for exposure based on factors such as the size of the space, the number of people, the kinds of activity, whether masks are worn, and ventilation and filtration rates.

6. Teaching machine learning models to adapt . Researchers in CSAIL developed a new type of neural network that can change its underlying equations to continuously adapt to new data. The advance could improve models’ decision-making based on data that changes over time, such as in medical diagnosis and autonomous driving.

5. Programming fibers . In June, a team created the first fabric fiber with digital capabilities. The fibers can sense, store, analyze, and infer data and activity after being sewn into a shirt. The researchers say the fibers could be used to monitor physical performance, to detect diseases, and for a variety of medical purposes.

4. Examining the limitations of data visualizations . A collaboration between anthropologists and computer scientists found that coronavirus skeptics have used sophisticated data visualizations to argue against public health orthodoxy like wearing a mask. The researchers concluded that data visualizations aren’t sufficient to convey the urgency of the Covid-19 pandemic because even the clearest graphs can be interpreted through a variety of belief systems.

3. Developing a Covid-detecting face mask . Engineers at MIT and Harvard University designed a prototype face mask that can diagnose the person wearing the mask with Covid-19 in about 90 minutes. The masks are embedded with tiny, disposable sensors that can be fitted into other face masks and could also be adapted to detect other viruses.

2. Confirming Hawking’s black hole theorem . Using observations of gravitational waves, physicists from MIT and elsewhere confirmed a major theorem created by Stephen Hawking in 1971. The theorem states that the area of a black hole’s event horizon — the boundary beyond which nothing can ever escape — will never shrink.

1. Advancing toward fusion energy . In September, researchers at MIT and the MIT spinout Commonwealth Fusion Systems ramped up a high-temperature superconducting electromagnet to a field strength of 20 tesla, the most powerful magnetic field of its kind ever created on Earth. The demonstration was three years in the making and is believed to resolve one of greatest remaining points of uncertainty in the quest to build the world’s first fusion power plant that produces more energy than it consumes.

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Education During Coronavirus

A Smithsonian magazine special report

Science | June 15, 2020

Seventy-Five Scientific Research Projects You Can Contribute to Online

From astrophysicists to entomologists, many researchers need the help of citizen scientists to sift through immense data collections

Rachael Lallensack

Former Assistant Editor, Science and Innovation

If you find yourself tired of streaming services, reading the news or video-chatting with friends, maybe you should consider becoming a citizen scientist. Though it’s true that many field research projects are paused , hundreds of scientists need your help sifting through wildlife camera footage and images of galaxies far, far away, or reading through diaries and field notes from the past.

Plenty of these tools are free and easy enough for children to use. You can look around for projects yourself on Smithsonian Institution’s citizen science volunteer page , National Geographic ’s list of projects and CitizenScience.gov ’s catalog of options. Zooniverse is a platform for online-exclusive projects , and Scistarter allows you to restrict your search with parameters, including projects you can do “on a walk,” “at night” or “on a lunch break.”

To save you some time, Smithsonian magazine has compiled a collection of dozens of projects you can take part in from home.

American Wildlife

If being home has given you more time to look at wildlife in your own backyard, whether you live in the city or the country, consider expanding your view, by helping scientists identify creatures photographed by camera traps. Improved battery life, motion sensors, high-resolution and small lenses have made camera traps indispensable tools for conservation.These cameras capture thousands of images that provide researchers with more data about ecosystems than ever before.

Smithsonian Conservation Biology Institute’s eMammal platform , for example, asks users to identify animals for conservation projects around the country. Currently, eMammal is being used by the Woodland Park Zoo ’s Seattle Urban Carnivore Project, which studies how coyotes, foxes, raccoons, bobcats and other animals coexist with people, and the Washington Wolverine Project, an effort to monitor wolverines in the face of climate change. Identify urban wildlife for the Chicago Wildlife Watch , or contribute to wilderness projects documenting North American biodiversity with The Wilds' Wildlife Watch in Ohio , Cedar Creek: Eyes on the Wild in Minnesota , Michigan ZoomIN , Western Montana Wildlife and Snapshot Wisconsin .

"Spend your time at home virtually exploring the Minnesota backwoods,” writes the lead researcher of the Cedar Creek: Eyes on the Wild project. “Help us understand deer dynamics, possum populations, bear behavior, and keep your eyes peeled for elusive wolves!"

If being cooped up at home has you daydreaming about traveling, Snapshot Safari has six active animal identification projects. Try eyeing lions, leopards, cheetahs, wild dogs, elephants, giraffes, baobab trees and over 400 bird species from camera trap photos taken in South African nature reserves, including De Hoop Nature Reserve and Madikwe Game Reserve .

With South Sudan DiversityCam , researchers are using camera traps to study biodiversity in the dense tropical forests of southwestern South Sudan. Part of the Serenegeti Lion Project, Snapshot Serengeti needs the help of citizen scientists to classify millions of camera trap images of species traveling with the wildebeest migration.

Classify all kinds of monkeys with Chimp&See . Count, identify and track giraffes in northern Kenya . Watering holes host all kinds of wildlife, but that makes the locales hotspots for parasite transmission; Parasite Safari needs volunteers to help figure out which animals come in contact with each other and during what time of year.

Mount Taranaki in New Zealand is a volcanic peak rich in native vegetation, but native wildlife, like the North Island brown kiwi, whio/blue duck and seabirds, are now rare—driven out by introduced predators like wild goats, weasels, stoats, possums and rats. Estimate predator species compared to native wildlife with Taranaki Mounga by spotting species on camera trap images.

The Zoological Society of London’s (ZSL) Instant Wild app has a dozen projects showcasing live images and videos of wildlife around the world. Look for bears, wolves and lynx in Croatia ; wildcats in Costa Rica’s Osa Peninsula ; otters in Hampshire, England ; and both black and white rhinos in the Lewa-Borana landscape in Kenya.

Under the Sea

Researchers use a variety of technologies to learn about marine life and inform conservation efforts. Take, for example, Beluga Bits , a research project focused on determining the sex, age and pod size of beluga whales visiting the Churchill River in northern Manitoba, Canada. With a bit of training, volunteers can learn how to differentiate between a calf, a subadult (grey) or an adult (white)—and even identify individuals using scars or unique pigmentation—in underwater videos and images. Beluga Bits uses a “ beluga boat ,” which travels around the Churchill River estuary with a camera underneath it, to capture the footage and collect GPS data about the whales’ locations.

Many of these online projects are visual, but Manatee Chat needs citizen scientists who can train their ear to decipher manatee vocalizations. Researchers are hoping to learn what calls the marine mammals make and when—with enough practice you might even be able to recognize the distinct calls of individual animals.

Several groups are using drone footage to monitor seal populations. Seals spend most of their time in the water, but come ashore to breed. One group, Seal Watch , is analyzing time-lapse photography and drone images of seals in the British territory of South Georgia in the South Atlantic. A team in Antarctica captured images of Weddell seals every ten minutes while the seals were on land in spring to have their pups. The Weddell Seal Count project aims to find out what threats—like fishing and climate change—the seals face by monitoring changes in their population size. Likewise, the Año Nuevo Island - Animal Count asks volunteers to count elephant seals, sea lions, cormorants and more species on a remote research island off the coast of California.

With Floating Forests , you’ll sift through 40 years of satellite images of the ocean surface identifying kelp forests, which are foundational for marine ecosystems, providing shelter for shrimp, fish and sea urchins. A project based in southwest England, Seagrass Explorer , is investigating the decline of seagrass beds. Researchers are using baited cameras to spot commercial fish in these habitats as well as looking out for algae to study the health of these threatened ecosystems. Search for large sponges, starfish and cold-water corals on the deep seafloor in Sweden’s first marine park with the Koster seafloor observatory project.

The Smithsonian Environmental Research Center needs your help spotting invasive species with Invader ID . Train your eye to spot groups of organisms, known as fouling communities, that live under docks and ship hulls, in an effort to clean up marine ecosystems.

If art history is more your speed, two Dutch art museums need volunteers to start “ fishing in the past ” by analyzing a collection of paintings dating from 1500 to 1700. Each painting features at least one fish, and an interdisciplinary research team of biologists and art historians wants you to identify the species of fish to make a clearer picture of the “role of ichthyology in the past.”

Interesting Insects

Notes from Nature is a digitization effort to make the vast resources in museums’ archives of plants and insects more accessible. Similarly, page through the University of California Berkeley’s butterfly collection on CalBug to help researchers classify these beautiful critters. The University of Michigan Museum of Zoology has already digitized about 300,000 records, but their collection exceeds 4 million bugs. You can hop in now and transcribe their grasshopper archives from the last century . Parasitic arthropods, like mosquitos and ticks, are known disease vectors; to better locate these critters, the Terrestrial Parasite Tracker project is working with 22 collections and institutions to digitize over 1.2 million specimens—and they’re 95 percent done . If you can tolerate mosquito buzzing for a prolonged period of time, the HumBug project needs volunteers to train its algorithm and develop real-time mosquito detection using acoustic monitoring devices. It’s for the greater good!

For the Birders

Birdwatching is one of the most common forms of citizen science . Seeing birds in the wilderness is certainly awe-inspiring, but you can birdwatch from your backyard or while walking down the sidewalk in big cities, too. With Cornell University’s eBird app , you can contribute to bird science at any time, anywhere. (Just be sure to remain a safe distance from wildlife—and other humans, while we social distance ). If you have safe access to outdoor space—a backyard, perhaps—Cornell also has a NestWatch program for people to report observations of bird nests. Smithsonian’s Migratory Bird Center has a similar Neighborhood Nest Watch program as well.

Birdwatching is easy enough to do from any window, if you’re sheltering at home, but in case you lack a clear view, consider these online-only projects. Nest Quest currently has a robin database that needs volunteer transcribers to digitize their nest record cards.

You can also pitch in on a variety of efforts to categorize wildlife camera images of burrowing owls , pelicans , penguins (new data coming soon!), and sea birds . Watch nest cam footage of the northern bald ibis or greylag geese on NestCams to help researchers learn about breeding behavior.

Or record the coloration of gorgeous feathers across bird species for researchers at London’s Natural History Museum with Project Plumage .

Pretty Plants

If you’re out on a walk wondering what kind of plants are around you, consider downloading Leafsnap , an electronic field guide app developed by Columbia University, the University of Maryland and the Smithsonian Institution. The app has several functions. First, it can be used to identify plants with its visual recognition software. Secondly, scientists can learn about the “ the ebb and flow of flora ” from geotagged images taken by app users.

What is older than the dinosaurs, survived three mass extinctions and still has a living relative today? Ginko trees! Researchers at Smithsonian’s National Museum of Natural History are studying ginko trees and fossils to understand millions of years of plant evolution and climate change with the Fossil Atmospheres project . Using Zooniverse, volunteers will be trained to identify and count stomata, which are holes on a leaf’s surface where carbon dioxide passes through. By counting these holes, or quantifying the stomatal index, scientists can learn how the plants adapted to changing levels of carbon dioxide. These results will inform a field experiment conducted on living trees in which a scientist is adjusting the level of carbon dioxide for different groups.

Help digitize and categorize millions of botanical specimens from natural history museums, research institutions and herbaria across the country with the Notes from Nature Project . Did you know North America is home to a variety of beautiful orchid species? Lend botanists a handby typing handwritten labels on pressed specimens or recording their geographic and historic origins for the New York Botanical Garden’s archives. Likewise, the Southeastern U.S. Biodiversity project needs assistance labeling pressed poppies, sedums, valerians, violets and more. Groups in California , Arkansas , Florida , Texas and Oklahoma all invite citizen scientists to partake in similar tasks.

Historic Women in Astronomy

Become a transcriber for Project PHaEDRA and help researchers at the Harvard-Smithsonian Center for Astrophysics preserve the work of Harvard’s women “computers” who revolutionized astronomy in the 20th century. These women contributed more than 130 years of work documenting the night sky, cataloging stars, interpreting stellar spectra, counting galaxies, and measuring distances in space, according to the project description .

More than 2,500 notebooks need transcription on Project PhaEDRA - Star Notes . You could start with Annie Jump Cannon , for example. In 1901, Cannon designed a stellar classification system that astronomers still use today. Cecilia Payne discovered that stars are made primarily of hydrogen and helium and can be categorized by temperature. Two notebooks from Henrietta Swan Leavitt are currently in need of transcription. Leavitt, who was deaf, discovered the link between period and luminosity in Cepheid variables, or pulsating stars, which “led directly to the discovery that the Universe is expanding,” according to her bio on Star Notes .

Volunteers are also needed to transcribe some of these women computers’ notebooks that contain references to photographic glass plates . These plates were used to study space from the 1880s to the 1990s. For example, in 1890, Williamina Flemming discovered the Horsehead Nebula on one of these plates . With Star Notes, you can help bridge the gap between “modern scientific literature and 100 years of astronomical observations,” according to the project description . Star Notes also features the work of Cannon, Leavitt and Dorrit Hoffleit , who authored the fifth edition of the Bright Star Catalog, which features 9,110 of the brightest stars in the sky.

Microscopic Musings

Electron microscopes have super-high resolution and magnification powers—and now, many can process images automatically, allowing teams to collect an immense amount of data. Francis Crick Institute’s Etch A Cell - Powerhouse Hunt project trains volunteers to spot and trace each cell’s mitochondria, a process called manual segmentation. Manual segmentation is a major bottleneck to completing biological research because using computer systems to complete the work is still fraught with errors and, without enough volunteers, doing this work takes a really long time.

For the Monkey Health Explorer project, researchers studying the social behavior of rhesus monkeys on the tiny island Cayo Santiago off the southeastern coast of Puerto Rico need volunteers to analyze the monkeys’ blood samples. Doing so will help the team understand which monkeys are sick and which are healthy, and how the animals’ health influences behavioral changes.

Using the Zooniverse’s app on a phone or tablet, you can become a “ Science Scribbler ” and assist researchers studying how Huntington disease may change a cell’s organelles. The team at the United Kingdom's national synchrotron , which is essentially a giant microscope that harnesses the power of electrons, has taken highly detailed X-ray images of the cells of Huntington’s patients and needs help identifying organelles, in an effort to see how the disease changes their structure.

Oxford University’s Comprehensive Resistance Prediction for Tuberculosis: an International Consortium—or CRyPTIC Project , for short, is seeking the aid of citizen scientists to study over 20,000 TB infection samples from around the world. CRyPTIC’s citizen science platform is called Bash the Bug . On the platform, volunteers will be trained to evaluate the effectiveness of antibiotics on a given sample. Each evaluation will be checked by a scientist for accuracy and then used to train a computer program, which may one day make this process much faster and less labor intensive.

Out of This World

If you’re interested in contributing to astronomy research from the comfort and safety of your sidewalk or backyard, check out Globe at Night . The project monitors light pollution by asking users to try spotting constellations in the night sky at designated times of the year . (For example, Northern Hemisphere dwellers should look for the Bootes and Hercules constellations from June 13 through June 22 and record the visibility in Globe at Night’s app or desktop report page .)

For the amateur astrophysicists out there, the opportunities to contribute to science are vast. NASA's Wide-field Infrared Survey Explorer (WISE) mission is asking for volunteers to search for new objects at the edges of our solar system with the Backyard Worlds: Planet 9 project .

Galaxy Zoo on Zooniverse and its mobile app has operated online citizen science projects for the past decade. According to the project description, there are roughly one hundred billion galaxies in the observable universe. Surprisingly, identifying different types of galaxies by their shape is rather easy. “If you're quick, you may even be the first person to see the galaxies you're asked to classify,” the team writes.

With Radio Galaxy Zoo: LOFAR , volunteers can help identify supermassive blackholes and star-forming galaxies. Galaxy Zoo: Clump Scout asks users to look for young, “clumpy” looking galaxies, which help astronomers understand galaxy evolution.

If current events on Earth have you looking to Mars, perhaps you’d be interested in checking out Planet Four and Planet Four: Terrains —both of which task users with searching and categorizing landscape formations on Mars’ southern hemisphere. You’ll scroll through images of the Martian surface looking for terrain types informally called “spiders,” “baby spiders,” “channel networks” and “swiss cheese.”

Gravitational waves are telltale ripples in spacetime, but they are notoriously difficult to measure. With Gravity Spy , citizen scientists sift through data from Laser Interferometer Gravitational­-Wave Observatory, or LIGO , detectors. When lasers beamed down 2.5-mile-long “arms” at these facilities in Livingston, Louisiana and Hanford, Washington are interrupted, a gravitational wave is detected. But the detectors are sensitive to “glitches” that, in models, look similar to the astrophysical signals scientists are looking for. Gravity Spy teaches citizen scientists how to identify fakes so researchers can get a better view of the real deal. This work will, in turn, train computer algorithms to do the same.

Similarly, the project Supernova Hunters needs volunteers to clear out the “bogus detections of supernovae,” allowing researchers to track the progression of actual supernovae. In Hubble Space Telescope images, you can search for asteroid tails with Hubble Asteroid Hunter . And with Planet Hunters TESS , which teaches users to identify planetary formations, you just “might be the first person to discover a planet around a nearby star in the Milky Way,” according to the project description.

Help astronomers refine prediction models for solar storms, which kick up dust that impacts spacecraft orbiting the sun, with Solar Stormwatch II. Thanks to the first iteration of the project, astronomers were able to publish seven papers with their findings.

With Mapping Historic Skies , identify constellations on gorgeous celestial maps of the sky covering a span of 600 years from the Adler Planetarium collection in Chicago. Similarly, help fill in the gaps of historic astronomy with Astronomy Rewind , a project that aims to “make a holistic map of images of the sky.”

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Rachael Lallensack | READ MORE

Rachael Lallensack is the former assistant web editor for science and innovation at Smithsonian .

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Article Contents

Primacy of the research question, structure of the paper, writing a research article: advice to beginners.

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Thomas V. Perneger, Patricia M. Hudelson, Writing a research article: advice to beginners, International Journal for Quality in Health Care , Volume 16, Issue 3, June 2004, Pages 191–192, https://doi.org/10.1093/intqhc/mzh053

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Writing research papers does not come naturally to most of us. The typical research paper is a highly codified rhetorical form [ 1 , 2 ]. Knowledge of the rules—some explicit, others implied—goes a long way toward writing a paper that will get accepted in a peer-reviewed journal.

A good research paper addresses a specific research question. The research question—or study objective or main research hypothesis—is the central organizing principle of the paper. Whatever relates to the research question belongs in the paper; the rest doesn’t. This is perhaps obvious when the paper reports on a well planned research project. However, in applied domains such as quality improvement, some papers are written based on projects that were undertaken for operational reasons, and not with the primary aim of producing new knowledge. In such cases, authors should define the main research question a posteriori and design the paper around it.

Generally, only one main research question should be addressed in a paper (secondary but related questions are allowed). If a project allows you to explore several distinct research questions, write several papers. For instance, if you measured the impact of obtaining written consent on patient satisfaction at a specialized clinic using a newly developed questionnaire, you may want to write one paper on the questionnaire development and validation, and another on the impact of the intervention. The idea is not to split results into ‘least publishable units’, a practice that is rightly decried, but rather into ‘optimally publishable units’.

What is a good research question? The key attributes are: (i) specificity; (ii) originality or novelty; and (iii) general relevance to a broad scientific community. The research question should be precise and not merely identify a general area of inquiry. It can often (but not always) be expressed in terms of a possible association between X and Y in a population Z, for example ‘we examined whether providing patients about to be discharged from the hospital with written information about their medications would improve their compliance with the treatment 1 month later’. A study does not necessarily have to break completely new ground, but it should extend previous knowledge in a useful way, or alternatively refute existing knowledge. Finally, the question should be of interest to others who work in the same scientific area. The latter requirement is more challenging for those who work in applied science than for basic scientists. While it may safely be assumed that the human genome is the same worldwide, whether the results of a local quality improvement project have wider relevance requires careful consideration and argument.

Once the research question is clearly defined, writing the paper becomes considerably easier. The paper will ask the question, then answer it. The key to successful scientific writing is getting the structure of the paper right. The basic structure of a typical research paper is the sequence of Introduction, Methods, Results, and Discussion (sometimes abbreviated as IMRAD). Each section addresses a different objective. The authors state: (i) the problem they intend to address—in other terms, the research question—in the Introduction; (ii) what they did to answer the question in the Methods section; (iii) what they observed in the Results section; and (iv) what they think the results mean in the Discussion.

In turn, each basic section addresses several topics, and may be divided into subsections (Table 1 ). In the Introduction, the authors should explain the rationale and background to the study. What is the research question, and why is it important to ask it? While it is neither necessary nor desirable to provide a full-blown review of the literature as a prelude to the study, it is helpful to situate the study within some larger field of enquiry. The research question should always be spelled out, and not merely left for the reader to guess.

Typical structure of a research paper

The Methods section should provide the readers with sufficient detail about the study methods to be able to reproduce the study if so desired. Thus, this section should be specific, concrete, technical, and fairly detailed. The study setting, the sampling strategy used, instruments, data collection methods, and analysis strategies should be described. In the case of qualitative research studies, it is also useful to tell the reader which research tradition the study utilizes and to link the choice of methodological strategies with the research goals [ 3 ].

The Results section is typically fairly straightforward and factual. All results that relate to the research question should be given in detail, including simple counts and percentages. Resist the temptation to demonstrate analytic ability and the richness of the dataset by providing numerous tables of non-essential results.

The Discussion section allows the most freedom. This is why the Discussion is the most difficult to write, and is often the weakest part of a paper. Structured Discussion sections have been proposed by some journal editors [ 4 ]. While strict adherence to such rules may not be necessary, following a plan such as that proposed in Table 1 may help the novice writer stay on track.

References should be used wisely. Key assertions should be referenced, as well as the methods and instruments used. However, unless the paper is a comprehensive review of a topic, there is no need to be exhaustive. Also, references to unpublished work, to documents in the grey literature (technical reports), or to any source that the reader will have difficulty finding or understanding should be avoided.

Having the structure of the paper in place is a good start. However, there are many details that have to be attended to while writing. An obvious recommendation is to read, and follow, the instructions to authors published by the journal (typically found on the journal’s website). Another concerns non-native writers of English: do have a native speaker edit the manuscript. A paper usually goes through several drafts before it is submitted. When revising a paper, it is useful to keep an eye out for the most common mistakes (Table 2 ). If you avoid all those, your paper should be in good shape.

Common mistakes seen in manuscripts submitted to this journal

Huth EJ . How to Write and Publish Papers in the Medical Sciences , 2nd edition. Baltimore, MD: Williams & Wilkins, 1990 .

Browner WS . Publishing and Presenting Clinical Research . Baltimore, MD: Lippincott, Williams & Wilkins, 1999 .

Devers KJ , Frankel RM. Getting qualitative research published. Educ Health 2001 ; 14 : 109 –117.

Docherty M , Smith R. The case for structuring the discussion of scientific papers. Br Med J 1999 ; 318 : 1224 –1225.

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• Published: 21 January 2022

Behind every great research project is great data management

• Samantha Kanza   ORCID: orcid.org/0000-0002-4831-9489 1   na1 &
• Nicola J. Knight   ORCID: orcid.org/0000-0001-8286-3835 1   na1  

BMC Research Notes volume  15 , Article number:  20 ( 2022 ) Cite this article

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Research data management (RDM) is the cornerstone of a successful research project, and yet it often remains an underappreciated art that gets overlooked in the hustle and bustle of everyday project management even when required by funding bodies. If researchers are to strive for reproducible science that adheres to the principles of FAIR, then they need to manage the data associated with their research projects effectively. It is imperative to plan your RDM strategies early on, and setup your project organisation before embarking on the work. There are several different factors to consider: data management plans, data organisation and storage, publishing and sharing your data, ensuring reproducibility and adhering to data standards. Additionally it is important to reflect upon the ethical implications that might need to be planned for, and adverse issues that may need a mitigation strategy. This short article discusses these different areas, noting some best practices and detailing how to incorporate these strategies into your work. Finally, the article ends with a set of top ten tips for effective research data management.

Introduction

A research project without proper research data management (RDM) is akin to building a house without laying the foundations. Good RDM is critical to the success of a research project; however, it is an element that is often neglected even when required by funding bodies. Planning your RDM needs to take into account not just the current moment, but considering how you will look back on your information in several years or how you might be able to share the information with colleagues, possibly across multiple disciplines, in a form that they can easily understand. There are many aspects involved in the data research lifecycle that will help a research project and its data to be findable, accessible, interoperable and re-useable (FAIR) [ 1 ]. In this short article we are going to discuss some of the key areas involved in RDM including: Organising, storing and sharing your data, creating data management plans and ensuring that any research conducted is both ethical and reproducible. We discuss why these areas are important and how they might be incorporated in your work and conclude with a list of our top ten tips for how to manage your research data.

Data organisation and storage

How you organise and store your data will shape your capacity to find, manage, publish and re-use it at a later date [ 2 ]. The first person likely to benefit from a sensible organisational system is your future self. Using sensible easy to follow folder and file structures will enable you to easily locate different pieces of your data. Just randomly naming files and putting in a haphazard folder structure will not benefit either you or anyone looking to use your data in the future. Another potential consideration is being aware of restrictions on where you are permitted to store your research data, such as institutional requirements or specific collaborator requirements related to security and international transfer of data.

This should be something that you think about at the very beginning of your work, as it is much simpler to add to an existing structure than having to go back and rework years of files at the end of the project (if you can even remember what each file referred to). If you are storing lots of similar types of data then you might want to consider making template folders that you can use each time you create a new dataset. When working in a collaborative research project it is also important that the organisational strategies are agreed upon as a group at the start to ensure consistency across the team with respect to both where and how team members are storing and organising the project data.

It is also worth identifying which aspects of your data you will need to store for the short term and long term, and how you are going to store the data. Further, it is worth considering the trade-off between data storage and recreating data, as data that is expensive to store but easy to re-create doesn’t necessarily need to be stored [ 3 ].

If your data is being produced in a proprietary format, then you need to work out how to store it in an accessible way that you and others can use it later down the line even if you don’t have access to the software that produced it. One way of ensuring the longevity of your data is to save it in a .txt file, meaning that even if the proprietary files become unusable, the data still remains in a readable and editable format. However, this strategy should only be employed alongside saving the data in the original data formats as opposed to relying on this as the primary storage method. Additionally, when doing this, it is important to supply context alongside the data potentially in the form of a README data description file or as additional metadata as merely saving the data in raw text files isn’t very helpful when it comes to sharing or understanding it later down the line.

It is also worth remembering that if you are working on collaborative research projects, then a key aspect of organising your data is communication. Even with the most organised group members, projects and data cannot be effectively managed unless all group members are communicating and have agreed on who is doing what with the different pieces of data [ 4 ]. The more data, and the more complex the data, the more time you need to devote to planning the organisation and communication of the data.

Data management

Poor data management can lead to data breaches and subsequently, unsuccessful and potentially harmful research projects. Managing your data well and planning how to achieve this from the start is absolutely key to a successful research project and is often a requirement of Research Application Funding Bodies. In order to achieve this, a Data Management Plan (DMP) should be created which outlines how the data is going to be managed throughout the entire project lifecycle. Many universities have their own internal resources for creating these plans, but there are also templates available from DMP Online [ 5 ].

A DMP should be an active document that is referred to throughout the project and used to measure whether it is on track. It is essential that these documents are updated throughout the project to reflect any changes, and data managers should be consulted with respect to the DMP throughout the entire project lifecycle, rather than only at the beginning. Further, in collaborative data projects these plans become even more essential as all group members should be collecting and handling data in the same way.

Another core aspect of data management is version control. All the work associated with a research project should be backed up, but versions should also be kept such that changes can be recorded and documents or data can be rolled back to a previous version if necessary. There are a number of ways to version data depending on the nature of the data and the project teams expertise. There are version control systems such as GitHub [ 6 ] for code or datasets. For documents, you can use integrated track changes, alternatively separate files can be created with version numbers, or version control tables can be added at the top of documents to record in document changes.

Data publication and sharing

Publishing your data and making it shareable is an important outcome for any successful research project. Ultimately it is desirable to disseminate the useful and relevant outputs of a research project to those who might be interested in reading or using them. It is important to give careful consideration to what parts of the project are published, and where they are published. Ultimately, the choice of what to publish and where to publish might be a requirement of the research funding, in which case that should be adhered to. If there is no specific data mandate, then publishing data in an open access repository that is relevant and well used within the research domain is advisable.

Data should always be published with suitable metadata, README files, and it should adhere to the FAIR standards of being findable, accessible, interoperable and re-useable [ 1 ]. Ideally, the datasets would have their own DOI and would be published under a license that enables their re-use. When considering what extent of the data and descriptions to publish, it is worth establishing what level of data (and methods) needs to be shared in order for the project results to be reproduced. Depending on the nature of your data (e.g. if it contains any sensitive or personal data) it may be necessary to anonymise and or aggregate the data before making it available [ 7 ].

Data reproducibility

Reproducibility (or the lack thereof) is a significant problem in scientific research in the 21st Century, as in order to allow other scientists to assess your work and also use it in the advancement of scientific knowledge it is crucial that the work can be reproduced. There are unfortunately a large number of peer reviewed scientific studies that are not reproducible [ 8 , 9 ], which could be due to lack of availability of raw data, poor methodological explanations, missing data, and a number of other considerations. There are so many factors, parameters and methods that can be used on data, right from the point of acquisition, through analysis, up to the visualisation of outputs. All of these changes can affect the data findings, and it essential that these are all captured alongside the data if it is to stand a chance of being reproducible.

There are a number of steps that can be taken to aid with facilitating reproducibility. One of the crucial elements in reproducibility is sharing your data provenance, that could be pointing researchers to specific datasets, if using existing data, or your detailed protocols if you collected the data yourself. It is also becoming increasingly important to share your code and detailed methods alongside the data used in the analysis, as this enables other researchers to understand the processes that were undertaken and attempt to reproduce them. It is worth considering using an electronic lab notebook (ELN) System or a notebook that can combine commentary and analysis code such as Jupyter Notebooks [ 10 ]. Additionally, using version control systems for your documents and code will allow others to see any changes that you have made, and specific versions can be viewed and used. Ultimately, if you yourself could not reproduce the project results from the data and documents that you have shared, then you cannot expect another researcher to be able to. This is something that should be considered and evaluated before finalising what data to share.

• Data ethics

Data ethics is another vital aspect of responsible research. In most jurisdictions any study that involves humans (whether through direct data generation, the use of their tissue/cells, or the use of their previously generated data e.g. tweets or online contributions) will need specific ethics approval [ 11 ], but ethical considerations should apply generally as well.

The core requirements of an ethics application are to lay out the purposes of the study, what data you are collecting and why, and to ensure that participants are fully informed about their involvement [ 12 ]. Consent needs to be obtained from any active participants (and that includes the researchers themselves), and researchers need to make a data protection plan and devise a risk assessment to ensure that the research is being conducted safely, with mitigated risks, and that the data collected is going to be adequately protected.

If you are working with personal data then there are ethical considerations around collection of the appropriate amount of data to collect and ensuring that it is anonymised as soon as possible. It is also worth remembering that, even when projects are not working with personal data there are ethical considerations around the potential effects of your research and possible unintended consequences to the communities involved [ 13 ].

The biggest piece of advice that we can give to improve your data management is start early! Don’t leave thinking about this until the project wraps up, or when writing up your results, think about it when you start out, and continue to evolve this as your project matures. Don’t be afraid to ask for advice, as there is lots of expertise out there, and remember that changes can always be made. It is obviously preferable to start out with an optimum data management plan, but it is much better to change a system that isn’t working or to make improvements than to just stick to a plan that isn’t working. Making small steps towards better overall data handling is better than not taking any steps.

Top ten tips for good research data management

To help with this here are our top ten tips for good research data management as shown in Fig. 1 .

Start early: Plan your data management strategy right from the start, think about every aspect of your project from the data collection, organisation, storage, and even where you are planning on publishing and sharing the results.

Data management plan: Make one of these right at the beginning and refer to it and improve it throughout the entire project life cycle.

Organisation is key: Use sensible folder/file structures that have been agreed with the entire team.

Version control your work: Decide on what version control systems you are going to use and implement these plans from the beginning.

Storage strategy: Consider your long term and short term data storage. And implement the 321 data storage rule: (3 copies of the data, within 2 types of media, with 1 stored at a separate site), and NEVER rely on USB sticks.

Remember your standards and be FAIR: Think about what standards you are going to make your data available in. Data should be Findable, Accessible, Interoperable and Re-useable.

Consider ethics: If you are interacting with human data in any way, you will need ethics! These applications can take a while to write and obtain approval for, so start straight away!

Factor in resources: Time and costs should be factored in for all required resources, including your data management!

Future proof your data: Metadata alone will not future proof your data, you should get DOI’s for your datasets and include relevant README’s and description files.

Communicate: If you are working on collaborative research projects then communication is key both in setting up the initial organisational strategies, and throughout the entire project life cycle to ensure that team members are working consistently with respect to data collection, organisation, storage etc.

These tips and the content of this article was collated from our own research, and through the results of running our “Failed it to Nailed it Getting Data Sharing Right” and “Skills4Scientists” series. More information on these series including links to videos can be found here: http://www.ai3sd.org/fi2ni and http://www.ai3sd.org/s4s .

Availability of data and materials

These tips and the content of this article was collated from our own research, and through the results of running our “Failed it to Nailed it Getting Data Sharing Right” and “Skills4Scientists” series. All referenced videos have already been published on YouTube and deposited in the Southampton ePrints repository with a CC-BY 4.0 License. More information on these series including links to videos can be found here: http://www.ai3sd.org/fi2ni and http://www.ai3sd.org/s4s .

Abbreviations

• Research data management

Findable, accessible, interoperable, reusable

Data management plan

Digital object identifier

Electronic lab notebook

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Acknowledgements

We wish to acknowledge Professor Jeremy Frey and Dr Sarah Callaghan for their support in planning and organising the event series and for proof-reading our article. We also extend our heartfelt thanks to all our speakers and contributors who participated in our Failed it to nailed it and Skills4Scientists series.

This work was funded by EPSRC through grants EP/S000356/1-AI3SD Network+ (Artificial Intelligence and Augmented Intelligence for Automated Investigations for Scientific Discovery) and EP/S020357/1-PSDS (Physical Sciences Data science Service).

Author information

Samantha Kanza and Nicola J. Knight contributed equally to this work

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Department of Chemistry, Faculty of Engineering and Physical Sciences, University of Southampton, University Road, Southampton, SO17 1BJ, UK

Samantha Kanza & Nicola J. Knight

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SK and NK jointly organised and co-ordinated the survey and event series that provided the basis for this commentary. The article was also written and edited jointly. Both authors read and approved the final manuscript.

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Correspondence to Samantha Kanza .

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The survey used in the design of our event series was approved by University of Southampton ethics panel ERGO No: 57287.

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Kanza, S., Knight, N.J. Behind every great research project is great data management. BMC Res Notes 15 , 20 (2022). https://doi.org/10.1186/s13104-022-05908-5

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Research Project Evaluation—Learnings from the PATHWAYS Project Experience

Aleksander galas.

1 Epidemiology and Preventive Medicine, Jagiellonian University Medical College, 31-034 Krakow, Poland; [email protected] (A.G.); [email protected] (A.P.)

Aleksandra Pilat

Matilde leonardi.

2 Fondazione IRCCS, Neurological Institute Carlo Besta, 20-133 Milano, Italy; [email protected]

Beata Tobiasz-Adamczyk

Background: Every research project faces challenges regarding how to achieve its goals in a timely and effective manner. The purpose of this paper is to present a project evaluation methodology gathered during the implementation of the Participation to Healthy Workplaces and Inclusive Strategies in the Work Sector (the EU PATHWAYS Project). The PATHWAYS project involved multiple countries and multi-cultural aspects of re/integrating chronically ill patients into labor markets in different countries. This paper describes key project’s evaluation issues including: (1) purposes, (2) advisability, (3) tools, (4) implementation, and (5) possible benefits and presents the advantages of a continuous monitoring. Methods: Project evaluation tool to assess structure and resources, process, management and communication, achievements, and outcomes. The project used a mixed evaluation approach and included Strengths (S), Weaknesses (W), Opportunities (O), and Threats (SWOT) analysis. Results: A methodology for longitudinal EU projects’ evaluation is described. The evaluation process allowed to highlight strengths and weaknesses and highlighted good coordination and communication between project partners as well as some key issues such as: the need for a shared glossary covering areas investigated by the project, problematic issues related to the involvement of stakeholders from outside the project, and issues with timing. Numerical SWOT analysis showed improvement in project performance over time. The proportion of participating project partners in the evaluation varied from 100% to 83.3%. Conclusions: There is a need for the implementation of a structured evaluation process in multidisciplinary projects involving different stakeholders in diverse socio-environmental and political conditions. Based on the PATHWAYS experience, a clear monitoring methodology is suggested as essential in every multidisciplinary research projects.

1. Introduction

Over the last few decades, a strong discussion on the role of the evaluation process in research has developed, especially in interdisciplinary or multidimensional research [ 1 , 2 , 3 , 4 , 5 ]. Despite existing concepts and definitions, the importance of the role of evaluation is often underestimated. These dismissive attitudes towards the evaluation process, along with a lack of real knowledge in this area, demonstrate why we need research evaluation and how research evaluation can improve the quality of research. Having firm definitions of ‘evaluation’ can link the purpose of research, general questions associated with methodological issues, expected results, and the implementation of results to specific strategies or practices.

Attention paid to projects’ evaluation shows two concurrent lines of thought in this area. The first is strongly associated with total quality management practices and operational performance; the second focuses on the evaluation processes needed for public health research and interventions [ 6 , 7 ].

The design and implementation of process’ evaluations in fields different from public health have been described as multidimensional. According to Baranowski and Stables, process evaluation consists of eleven components: recruitment (potential participants for corresponding parts of the program); maintenance (keeping participants involved in the program and data collection); context (an aspect of environment of intervention); resources (the materials necessary to attain project goals); implementation (the extent to which the program is implemented as designed); reach (the extent to which contacts are received by the targeted group); barriers (problems encountered in reaching participants); exposure (the extent to which participants view or read material); initial use (the extent to which a participant conducts activities specified in the materials); continued use (the extent to which a participant continues to do any of the activities); contamination (the extent to which participants receive interventions from outside the program and the extent to which the control group receives the treatment) [ 8 ].

There are two main factors shaping the evaluation process. These are: (1) what is evaluated (whether the evaluation process revolves around project itself or the outcomes which are external to the project), and (2) who is an evaluator (whether an evaluator is internal or external to the project team and program). Although there are several existing gaps in current knowledge about the evaluation process of external outcomes, the use of a formal evaluation process of a research project itself is very rare.

To define a clear evaluation and monitoring methodology we performed different steps. The purpose of this article is to present experiences from the project evaluation process implemented in the Participation to Healthy Workplaces and Inclusive Strategies in the Work Sector (the EU PATHWAYS project. The manuscript describes key project evaluation issues as: (1) purposes, (2) advisability, (3) tools, (4) implementation, and (5) possible benefits. The PATHWAYS project can be understood as a specific case study—presented through a multidimensional approach—and based on the experience associated with general evaluation, we can develop patterns of good practices which can be used in other projects.

1.1. Theoretical Framework

The first step has been the clear definition of what is an evaluation strategy or methodology . The term evaluation is defined by the Cambridge Dictionary as the process of judging something’s quality, importance, or value, or a report that includes this information [ 9 ] or in a similar way by the Oxford Dictionary as the making of a judgment about the amount, number, or value of something [ 10 ]; assessment and in the activity, it is frequently understood as associated with the end rather than with the process. Stufflebeam, in its monograph, defines evaluation as a study designed and conducted to assist some audience to assess an object’s merit and worth. Considering this definition, there are four categories of evaluation approaches: (1) pseudo-evaluation; (2) questions and/or methods-oriented evaluation; (3) improvement/accountability evaluation; (4) social agenda/advocacy evaluation [ 11 ].

In brief, considering Stufflebeam’s classification, pseudo-evaluations promote invalid or incomplete findings. This happens when findings are selectively released or falsified. There are two pseudo-evaluation types proposed by Stufflebeam: (1) public relations-inspired studies (studies which do not seek truth but gather information to solicit positive impressions of program), and (2) politically controlled studies (studies which seek the truth but inappropriately control the release of findings to right-to-know audiences).

The questions and/or methods-oriented approach uses rather narrow questions, which are oriented on operational objectives of the project. Questions oriented uses specific questions, which are of interest by accountability requirements or an expert’s opinions of what is important, while method oriented evaluations favor the technical qualities of program/process. The general concept of these two is that it is better to ask a few pointed questions well to get information on program merit and worth [ 11 ]. In this group, one may find the following evaluation types: (a) objectives-based studies: typically focus on whether the program objectives have been achieved through an internal perspective (by project executors); (b) accountability, particularly payment by results studies: stress the importance of obtaining an external, impartial perspective; (c) objective testing program: uses standardized, multiple-choice, norm-referenced tests; (d) outcome evaluation as value-added assessment: a recurrent evaluation linked with hierarchical gain score analysis; (e) performance testing: incorporates the assessment of performance (by written or spoken answers, or psychomotor presentations) and skills; (f) experimental studies: program evaluators perform a controlled experiment and contrast the outcomes observed; (g) management information system: provide information needed for managers to conduct their programs; (h) benefit-cost analysis approach: mainly sets of quantitative procedures to assess the full cost of a program and its returns; (i) clarification hearing: an evaluation of a trial in which role-playing evaluators competitively implement both a damning prosecution of a program—arguing that it failed, and a defense of the program—and arguing that it succeeded. Next, a judge hears arguments within the framework of a jury trial and controls the proceedings according to advance agreements on rules of evidence and trial procedures; (j) case study evaluation: focused, in-depth description, analysis, and synthesis of a particular program; (k) criticism and connoisseurship: certain experts in a given area do in-depth analysis and evaluation that could not be done in other way; (l) program theory-based evaluation: based on the theory beginning with another validated theory of how programs of a certain type within similar settings operate to produce outcomes (e.g., Health Believe Model, Predisposing, Reinforcing and Enabling Constructs in Educational Diagnosis and Evaluation and Policy, Regulatory, and Organizational Constructs in Educational and Environmental Development - thus so called PRECEDE-PROCEED model proposed by L. W. Green or Stage of Change Theory by Prochaska); (m) mixed method studies: include different qualitative and quantitative methods.

The third group of methods considered in evaluation theory are improvement/accountability-oriented evaluation approaches. Among these, there are the following: (a) decision/accountability oriented studies: emphasizes that evaluation should be used proactively to help improve a program and retroactively to assess its merit and worth; (b) consumer-oriented studies: wherein the evaluator is a surrogate consumer who draws direct conclusions about the evaluated program; (c) accreditation/certification approach: an accreditation study to verify whether certification requirements have been/are fulfilled.

Finally, a social agenda/advocacy evaluation approach focuses on the assessment of difference, which is/was intended to be the effect of the program evaluation. The evaluation process in this type of approach works in a loop, starting with an independent evaluator who provides counsel and advice towards understanding, judging and improving programs as evaluations to serve the client’s needs. In this group, there are: (a) client-centered studies (or responsive evaluation): evaluators work with, and for, the support of diverse client groups; (b) constructivist evaluation: evaluators are authorized and expected to maneuver the evaluation to emancipate and empower involved and affected disenfranchised people; (c) deliberative democratic evaluation: evaluators work within an explicit democratic framework and uphold democratic principles in reaching defensible conclusions; (d) utilization-focused evaluation: explicitly geared to ensure that program evaluations make an impact.

1.2. Implementation of the Evaluation Process in the EU PATHWAYS Project

The idea to involve the evaluation process as an integrated goal of the PATHWAYS project was determined by several factors relating to the main goal of the project, defined as a special intervention to existing attitudes to occupational mobility and work activity reintegration of people of working age, suffering from specific chronic conditions into the labor market in 12 European Countries. Participating countries had different cultural and social backgrounds and different pervasive attitudes towards people suffering from chronic conditions.

The components of evaluation processes previously discussed proved helpful when planning the PATHWAYS evaluation, especially in relation to different aspects of environmental contexts. The PATHWAYS project focused on chronic conditions including: mental health issues, neurological diseases, metabolic disorders, musculoskeletal disorders, respiratory diseases, cardiovascular diseases, and persons with cancer. Within this group, the project found a hierarchy of patients and social and medical statuses defined by the nature of their health conditions.

According to the project’s monitoring and evaluation plan, the evaluation process followed specific challenges defined by the project’s broad and specific goals and monitored the progress of implementing key components by assessing the effectiveness of consecutive steps and identifying conditions supporting the contextual effectiveness. Another significant aim of the evaluation component on the PATHWAYS project was to recognize the value and effectiveness of using a purposely developed methodology—consisting of a wide set of quantitative and qualitative methods. The triangulation of methods was very useful and provided the opportunity to develop a multidimensional approach to the project [ 12 ].

From the theoretical framework, special attention was paid to the explanation of medical, cultural, social and institutional barriers influencing the chance of employment of chronically ill persons in relation to the characteristics of the participating countries.

Levels of satisfaction with project participation, as well as with expected or achieved results and coping with challenges on local–community levels and macro-social levels, were another source of evaluation.

In the PATHWAYS project, the evaluation was implemented for an unusual purpose. This quasi-experimental design was developed to assess different aspects of the multidimensional project that used a variety of methods (systematic review of literature, content analysis of existing documents, acts, data and reports, surveys on different country-levels, deep interviews) in the different phases of the 3 years. The evaluation monitored each stage of the project and focused on process implementation, with the goal of improving every step of the project. The evaluation process allowed to perform critical assessments and deep analysis of benefits and shortages of the specific phase of the project.

The purpose of the evaluation was to monitor the main steps of the Project, including the expectations associated with a multidimensional, methodological approach used by PATHWAYS partners, as well as improving communication between partners, from different professional and methodological backgrounds involved in the project in all its phases, so as to avoid errors in understanding the specific steps as well as the main goals.

2. Materials and Methods

The paper describes methodology and results gathered during the implementation of Work Package 3, Evaluation of the Participation to Healthy Workplaces and Inclusive Strategies in the Work Sector (the PATHWAYS) project. The work package was intended to keep internal control over the run of the project to achieve timely fulfillment of tasks, milestones, and purpose by all project partners.

2.1. Participants

The project consortium involved 12 partners from 10 different European countries. There were academics (representing cross-disciplinary research including socio-environmental determinants of health, clinicians), institutions actively working for the integration of people with chronic and mental health problems and disability, educational bodies (working in the area of disability and focusing on inclusive education), national health institutes (for rehabilitation of patients with functional and workplace impairments), an institution for inter-professional rehabilitation at a country level (coordinating medical, social, educational, pre-vocational and vocational rehabilitation), a company providing patient-centered services (in neurorehabilitation). All the partners represented vast knowledge and high-level expertise in the area of interest and all agreed with the World Health Organization’s (WHO) International Classification of Functioning, Disability and Health-ICF and of the biopsychosocial model of health and functioning. The consortium was created based on the following criteria:

• vision, mission, and activities in the area of project purposes,
• high level of experience in the area (supported by publications) and in doing research (being involved in international projects, collaboration with the coordinator and/or other partners in the past),
• being able to get broad geographical, cultural and socio-political representation from EU countries,
• represent different stakeholder type in the area.

2.2. Project Evaluation Tool

The tool development process involved the following steps:

• (1) Review definitions of ‘evaluation’ and adopt one which consorts best with the reality of public health research area;
• (2) Review evaluation approaches and decide on the content which should be applicable in the public health research;
• (3) Create items to be used in the evaluation tool;
• (4) Decide on implementation timing.

According to the PATHWAYS project protocol, an evaluation tool for the internal project evaluation was required to collect information about: (1) structure and resources; (2) process, management and communication; (3) achievements and/or outcomes and (4) SWOT analysis. A mixed methods approach was chosen. The specific evaluation process purpose and approach are presented in Table 1 .

Evaluation purposes and approaches adopted for the purpose in the PATHWAYS project.

* Open ended questions are not counted here.

The tool was prepared following different steps. In the paragraph to assess structure and resources, there were questions about the number of partners, professional competences, assigned roles, human, financial and time resources, defined activities and tasks, and the communication plan. The second paragraph, process, management and communication, collected information about the coordination process, consensus level, quality of communication among coordinators, work package leaders, and partners, whether project was carried out according to the plan, involvement of target groups, usefulness of developed materials, and any difficulties in the project realization. Finally, the paragraph achievements and outcomes gathered information about project specific activities such as public-awareness raising, stakeholder participation and involvement, whether planned outcomes (e.g., milestones) were achieved, dissemination activities, and opinions on whether project outcomes met the needs of the target groups. Additionally, it was decided to implement SWOT analysis as a part of the evaluation process. SWOT analysis derives its name from the evaluation of Strengths (S), Weaknesses (W), Opportunities (O), and Threats (T) faced by a company, industry or, in this case, project consortium. SWOT analysis comes from the business world and was developed in the 1960s at Harvard Business School as a tool for improving management strategies among companies, institutions, or organization [ 13 , 14 ]. However, in recent years, SWOT analysis has been adapted in the context of research to improve programs or projects.

For a better understanding of SWOT analysis, it is important to highlight the internal features of Strengths and Weaknesses, which are considered controllable. Strengths refers to work inside the project such as capabilities and competences of partners, whereas weaknesses refers to aspects, which needs improvement, such as resources. Conversely, Opportunities and Threats are considered outside factors and uncontrollable [ 15 ]. Opportunities are maximized to fit the organization’s values and resources and threats are the factors that the organization is not well equipped to deal with [ 9 ].

The PATHWAYS project members participated in SWOT analyses every three months. They answered four open questions about strengths, weaknesses, opportunities, and threats identified in evaluated period (last three months). They were then asked to assess those items on 10-point scale. The sample included results from nine evaluated periods from partners from ten different countries.

The tool for the internal evaluation of the PATHWAYS project is presented in Appendix A .

2.3. Tool Implementation and Data Collection

The PATHWAYS on-going evaluation took place at three-month intervals. It consisted of on-line surveys, and every partner assigned a representative who was expected to have good knowledge on the progress of project’s progress. The structure and resources were assessed only twice, at the beginning (3rd month) and at the end (36th month) of the project. The process, management, and communication questions, as well as SWOT analysis questions, were asked every three months. The achievements and outcomes questions started after the first year of implementation (i.e., after 15th month), and some of items in this paragraph, (results achieved, whether project outcomes meet the needs of the target groups and published regular publications), were only implemented at the end of the project (36th month).

2.4. Evaluation Team

The evaluation team was created from professionals with different backgrounds and extensive experience in research methodology, sociology, social research methods and public health.

The project started in 2015 and was carried out for 36 months. There were 12 partners in the PATHWAYS project, representing Austria, Belgium, Czech Republic, Germany, Greece, Italy, Norway, Poland, Slovenia and Spain and a European Organization. The on-line questionnaire was sent to all partners one week after the specified period ended and project partners had at least 2 weeks to fill in/answer the survey. Eleven rounds of the survey were performed.

The participation rate in the consecutive evaluation surveys was 11 (91.7%), 12 (100%), 12 (100%), 11 (91.7%), 10 (83.3%), 11 (91.7%), 11 (91.7%), 10 (83.3%), and 11 (91.7%) till the project end. Overall, it rarely covered the whole group, which may have resulted from a lack of coercive mechanisms at a project level to answer project evaluation questions.

3.1. Evaluation Results Considering Structure and Resources (3rd Month Only)

A total of 11 out of 12 project partners participated in the first evaluation survey. The structure and resources of the project were not assessed by the project coordinator and as such, the results in represent the opinions of the other 10 participating partners. The majority of respondents rated the project consortium as having at least adequate professional competencies. In total eight to nine project partners found human, financial and time resources ‘just right’ and the communication plan ‘clear’. More concerns were observed regarding the clarity of tasks, what is expected from each partner, and how specific project activities should be or were assigned.

3.2. Evaluation Results Considering Process, Management and Communication

The opinions about project coordination, communication processes (with coordinator, between WP leaders, and between individual partners/researchers) were assessed as ‘good’ and ‘very good’, along the whole period. There were some issues, however, when it came to the realization of specific goals, deliverables, or milestones of the project.

Given the broad scope of the project and participating partner countries, we created a glossary to unify the common terms used in the project. It was a challenge, as during the project implementation there were several discussions and inconsistencies in the concepts provided ( Figure 1 ).

Partners’ opinions about the consensus around terms (shared glossary) in the project consortium across evaluation waves (W1—after 3-month realization period, and at 3-month intervals thereafter).

Other issues, which appeared during project implementation, were recruitment of, involvement with, and cooperation with stakeholders. There was a range of groups to be contacted and investigated during the project including individual patients suffering from chronic conditions, patients’ advocacy groups and national governmental organizations, policy makers, employers, and international organizations. It was found that during the project, the interest and the involvement level of the aforementioned groups was quite low and difficult to achieve, which led to some delays in project implementation ( Figure 2 ). This was the main cause of smaller percentages of “what was expected to be done in designated periods of project realization time”. The issue was monitored and eliminated by intensification of activities in this area ( Figure 3 ).

Partners’ reports on whether the project had been carried out according to the plan ( a ) and the experience of any problems in the process of project realization ( b ) (W1—after 3-month realization period, and at 3-month intervals thereafter).

Partners’ reports on an approximate estimation (in percent) of the project plan implementation (what has been done according to the plan) ( a ) and the involvement of target groups (W1—after 3-month realization period, and at 3-month intervals thereafter) ( b ).

3.3. Evaluation Results Considering Achievements and Outcomes

The evaluation process was prepared to monitor project milestones and deliverables. One of the PATHWAYS project goals was to raise public awareness surrounding the reintegration of chronically ill people into the labor market. This was assessed subjectively by cooperating partners and only half (six) felt they achieved complete success on that measure. The evaluation process monitored planned outcomes according to: (1) determination of strategies for awareness rising activities, (2) assessment of employment-related needs, and (3) development of guidelines (which were planned by the project). The majority of partners completely fulfilled this task. Furthermore, the dissemination process was also carried out according to the plan.

3.4. Evaluation Results from SWOT

3.4.1. strengths.

Amongst the key issues identified across all nine evaluated periods ( Figure 4 ), the “strong consortium” was highlighted as the most important strength of the PATHWAYS project. The most common arguments for this assessment were the coordinator’s experience in international projects, involvement of interdisciplinary experts who could guarantee a holistic approach to the subject, and a highly motivated team. This was followed by the uniqueness of the topic. Project implementers pointed to the relevance of the analyzed issues, which are consistent with social needs. They also highlighted that this topic concerned an unexplored area in employment policy. The interdisciplinary and international approach was also emphasized. According to the project implementers, the international approach allowed mapping of vocational and prevocational processes among patients with chronic conditions and disability throughout Europe. The interdisciplinary approach, on the other hand, enabled researchers to create a holistic framework that stimulates innovation by thinking across boundaries of particular disciplines—especially as the PATHWAYS project brings together health scientists from diverse fields (physicians, psychologists, medical sociologists, etc.) from ten European countries. This interdisciplinary approach is also supported by the methodology, which is based on a mixed-method approach (qualitative and quantitative data). The involvement of an advocacy group was another strength identified by the project implementers. It was stressed that the involvement of different types of stakeholders increased validity and social triangulation. It was also assumed that it would allow for the integration of relevant stakeholders. The last strength, the usefulness of results, was identified only in the last two evaluation waves, when the first results had been measured.

SWOT Analysis—a summary of main issues reported by PATHWAYS project partners.

3.4.2. Weaknesses

The survey respondents agreed that the main weaknesses of the project were time and human resources. The subject of the PATHWAYS project turned out to be very broad, and therefore the implementers pointed to the insufficient human resources and inadequate time for the implementation of individual tasks, as well as the project overall. This was related to the broad categories of chronic diseases chosen for analysis in the project. On one hand, the implementers complained about the insufficient number of chronic diseases taken into account in the project. On the other hand, they admitted that it was not possible to cover all chronic diseases in details. The scope of the project was reported as another weakness. In the successive waves of evaluation, the implementers more often pointed out that it was hard to cover all relevant topics.

Nevertheless, some of the major weaknesses reported during the project evaluation were methodological problems. Respondents pointed to problems with the implementation of tasks on a regular basis. For example, survey respondents highlighted the need for more open questions in the survey that the questionnaire was too long or too complicated, that the tools were not adjusted for relevancy in the national context, etc. Another issue was that the working language was English, but all tools or survey questionnaire needed to be translated into different languages and this issue was not always considered by the Commission in terms of timing and resources. This issue could provide useful for further projects, as well as for future collaborations.

The difficulties of involving stakeholders were reported, especially during tasks, which required their active commitment, like participation in in-depth interviews or online questionnaires. Interestingly, the international approach was considered both strength and weakness of the project. The implementers highlighted the complexity of making comparisons between health care and/or social care in different countries. The budget was also identified as a weakness by the project implementers. More funds obtained from the partners could have helped PATHWAYS enhance dissemination and stakeholders’ participation.

3.4.3. Opportunities

A list of seven issues within the opportunities category reflects the positive outlook of survey respondents from the beginning of the project to its final stage. Social utility was ranked as the top opportunity. The implementers emphasized that the project could fill a gap between the existing solutions and the real needs of people with chronic diseases and mental disorders. The implementers also highlighted the role of future recommendations, which would consist of proposed solutions for professionals, employees, employers, and politicians. These advantages are strongly associated with increasing awareness of employment situations of people with chronic diseases in Europe and the relevance of the problem. Alignment with policies, strategies, and stakeholders’ interests were also identified as opportunities. The topic is actively discussed on the European and national level, and labor market and employment issues are increasingly emphasized in the public discourse. What is more relevant is that the European Commission considers the issue crucial, and the results of the project are in line with its requests for the future. The implementers also observed increasing interest from the stakeholders, which is very important for the future of the project. Without doubt, the social network of project implementers provides a huge opportunity for the sustainability of results and the implementation of recommendations.

3.4.4. Threats

Insufficient response from stakeholders was the top perceived threat selected by survey respondents. The implementers indicated that insufficient involvement of stakeholders resulted in low response rates in the research phase, which posed a huge threat for the project. The interdisciplinary nature of the PATHWAYS project was highlighted as a potential threat due to differences in technical terminology and different systems of regulating the employment of persons with reduced work capacity in each country, as well as many differences in the legislation process. Insufficient funding and lack of existing data were identified as the last two threats.

One novel aspect of the evaluation process in the PATHWAYS project was a numerical SWOT analysis. Participants were asked to score strengths, weaknesses, opportunities, and threats from 0 (meaning the lack of/no strengths, weaknesses) to 10 (meaning a lot of ... several ... strengths, weaknesses). This concept enabled us to get a subjective score of how partners perceive the PATHWAYS project itself and the performance of the project, as well as how that perception changes over time. Data showed an increase in both strengths and opportunities and a decrease in weaknesses and threats over the course of project implementation ( Figure 5 ).

Numerical SWOT, combined, over a period of 36 months of project realization (W1—after 3-month realization period, and at 3-month intervals thereafter).

4. Discussion

The need for project evaluation was born from an industry facing challenges regarding how to achieve market goals in more efficient way. Nowadays, every process, including research project implementation, faces questions regarding its effectiveness and efficiency.

The challenge of a research project evaluation is that the majority of research projects are described as unique, although we believe several projects face similar issues and challenges as those observed in the PATHWAYS project.

The main objectives of the PATHWAYS Project were (a) to identify integration and re-integration strategies that are available in Europe and beyond for individuals with chronic diseases and mental disorders experiencing work-related problems (such as unemployment, absenteeism, reduced productivity, stigmatization), (b) to determine their effectiveness, (c) to assess the specific employment-related needs of those people, and (d) to develop guidelines supporting the implementation of effective strategies of professional integration and reintegration. The broad area of investigation, partial knowledge in the field, diversity of determinants across European Union countries, and involvement with stakeholders representing different groups caused several challenges in the project, including:

• problem : uncovered, challenging, demanding (how to encourage stakeholders to participate, share experiences),
• diversity : different European regions; different determinants: political, social, cultural; different public health and welfare systems; differences in law regulations; different employment policies and issues in the system,
• multidimensionality of research: some quantitative, qualitative studies including focus groups, opinions from professionals, small surveys in target groups (workers with chronic conditions).

The challenges to the project consequently led to several key issues, which should be taken, into account during project realization:

• partners : with their own expertise and interests; different expectations; different views on what is more important to focused on and highlighted;
• issues associated with unification : between different countries with different systems (law, work-related and welfare definitions, disability classification, others);
• coordination : as multidimensionality of the project may have caused some research activities by partners to move in a wrong direction (data, knowledge which is not needed for the project purposes), a lack of project vision in (some) partners might postpone activities through misunderstanding;
• exchange of information : multidimensionality, the fact that different tasks were accomplished by different centers and obstacles to data collection required good communication methods and smooth exchange of information.

Identified Issues and Implemented Solutions

There were several issues identified through the semi-internal evaluation process performed during the project. Those, which might be more relevant for the project realization, are mentioned in the Table 2 .

Issues identified by the evaluation process and solutions implemented.

The PATHWAYS project included diverse partners representing different areas of expertise and activity (considering broad aspect of chronic diseases, decline in functioning and of disability, and its role in a labor market) in different countries and social security systems, which caused a challenge when developing a common language to achieve effective communication and better understanding of facts and circumstances in different countries. The implementation of continuous project process monitoring, and proper adjustment, enabled the team to overcome these challenges.

The evaluation tool has several benefits. First, it covers all key areas of the research project including structure and available resources, the run of the process, quality and timing of management and communication, as well as project achievements and outcomes. Continuous evaluation of all of these areas provides in-depth knowledge about project performance. Second, the implementation of SWOT tool provided opportunities to share out good and bad experiences by all project partners, and the use of a numerical version of SWOT provided a good picture about inter-relations strengths—weaknesses and opportunities—threats in the project and showed the changes in their intensity over time. Additionally, numerical SWOT may verify whether perception of a project improves over time (as was observed in the PATHWAYS project) showing an increase in strengths and opportunities and a decrease in weaknesses and threats. Third, the intervals in which partners were ‘screened’ by the evaluation questionnaire seems to be appropriate, as it was not very demanding but frequent enough to diagnose on-time some issues in the project process.

The experiences with the evaluation also revealed some limitations. There were no coercive mechanisms for participation in the evaluation questionnaires, which may have caused a less than 100% response rate in some screening surveys. Practically, that was not a problem in the PATHWAYS project. Theoretically, however, this might lead to unrevealed problems, as partners experiencing troubles might not report them. Another point is asking about quality of the consortium to the project coordinator, which has no great value (the consortium is created by the coordinator in the best achievable way and it is hard to expect other comments especially at the beginning of the project). Regarding the tool itself, the question Could you give us approximate estimation (in percent) of the project plan realization (what has been done according to the plan)? was expected to collect information about the project partners collecting data on what has been done out of what should be done during each evaluation period, meaning that 100% was what should be done in 3-month time in our project. This question, however, was slightly confusing at the beginning, as it was interpreted as percentage of all tasks and activities planned for the whole duration of the project. Additionally, this question only works provided that precise, clear plans on the type and timing of tasks were allocated to the project partners. Lastly, there were some questions with very low variability in answer types across evaluation surveys (mainly about coordination and communication). Our opinion is that if the project runs/performs in a smooth manner, one may think such questions useless, but in more complicated projects, these questions may reveal potential causes of troubles.

5. Conclusions

The PATHWAYS project experience shows a need for the implementation of structured evaluation processes in multidisciplinary projects involving different stakeholders in diverse socio-environmental and political conditions. Based on the PATHWAYS experience, a clear monitoring methodology is suggested as essential in every project and we suggest the following steps while doing multidisciplinary research:

• Define area/s of interest (decision maker level/s; providers; beneficiaries: direct, indirect),
• Identify 2–3 possible partners for each area (chain sampling easier, more knowledge about; check for publications),
• Prepare a research plan (propose, ask for supportive information, clarify, negotiate),
• Create a cross-partner groups of experts,
• Prepare a communication strategy (communication channels, responsible individuals, timing),
• Prepare a glossary covering all the important issues covered by the research project,
• Monitor the project process and timing, identify concerns, troubles, causes of delays,
• Prepare for the next steps in advance, inform project partners about the upcoming activities,
• Summarize, show good practices, successful strategies (during project realization, to achieve better project performance).

Acknowledgments

The current study was part of the PATHWAYS project, that has received funding from the European Union’s Health Program (2014–2020) Grant agreement no. 663474.

The evaluation questionnaire developed for the PATHWAYS Project.

SWOT analysis:

What are strengths and weaknesses of the project? (list, please)

What are threats and opportunities? (list, please)

Visual SWOT:

Please, rate the project on the following continua:

How would you rate:

(no strengths) 0 1 2 3 4 5 6 7 8 9 10 (a lot of strengths, very strong)

(no weaknesses) 0 1 2 3 4 5 6 7 8 9 10 (a lot of weaknesses, very weak)

(no risks) 0 1 2 3 4 5 6 7 8 9 10 (several risks, inability to accomplish the task(s))

(no opportunities) 0 1 2 3 4 5 6 7 8 9 10 (project has a lot of opportunities)

Author Contributions

A.G., A.P., B.T.-A. and M.L. conceived and designed the concept; A.G., A.P., B.T.-A. finalized evaluation questionnaire and participated in data collection; A.G. analyzed the data; all authors contributed to writing the manuscript. All authors agreed on the content of the manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

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Sat / act prep online guides and tips, 113 great research paper topics.

General Education

One of the hardest parts of writing a research paper can be just finding a good topic to write about. Fortunately we've done the hard work for you and have compiled a list of 113 interesting research paper topics. They've been organized into ten categories and cover a wide range of subjects so you can easily find the best topic for you.

In addition to the list of good research topics, we've included advice on what makes a good research paper topic and how you can use your topic to start writing a great paper.

What Makes a Good Research Paper Topic?

Not all research paper topics are created equal, and you want to make sure you choose a great topic before you start writing. Below are the three most important factors to consider to make sure you choose the best research paper topics.

#1: It's Something You're Interested In

A paper is always easier to write if you're interested in the topic, and you'll be more motivated to do in-depth research and write a paper that really covers the entire subject. Even if a certain research paper topic is getting a lot of buzz right now or other people seem interested in writing about it, don't feel tempted to make it your topic unless you genuinely have some sort of interest in it as well.

#2: There's Enough Information to Write a Paper

Even if you come up with the absolute best research paper topic and you're so excited to write about it, you won't be able to produce a good paper if there isn't enough research about the topic. This can happen for very specific or specialized topics, as well as topics that are too new to have enough research done on them at the moment. Easy research paper topics will always be topics with enough information to write a full-length paper.

Trying to write a research paper on a topic that doesn't have much research on it is incredibly hard, so before you decide on a topic, do a bit of preliminary searching and make sure you'll have all the information you need to write your paper.

#3: It Fits Your Teacher's Guidelines

Don't get so carried away looking at lists of research paper topics that you forget any requirements or restrictions your teacher may have put on research topic ideas. If you're writing a research paper on a health-related topic, deciding to write about the impact of rap on the music scene probably won't be allowed, but there may be some sort of leeway. For example, if you're really interested in current events but your teacher wants you to write a research paper on a history topic, you may be able to choose a topic that fits both categories, like exploring the relationship between the US and North Korea. No matter what, always get your research paper topic approved by your teacher first before you begin writing.

113 Good Research Paper Topics

Below are 113 good research topics to help you get you started on your paper. We've organized them into ten categories to make it easier to find the type of research paper topics you're looking for.

Arts/Culture

• Discuss the main differences in art from the Italian Renaissance and the Northern Renaissance .
• Analyze the impact a famous artist had on the world.
• How is sexism portrayed in different types of media (music, film, video games, etc.)? Has the amount/type of sexism changed over the years?
• How has the music of slaves brought over from Africa shaped modern American music?
• How has rap music evolved in the past decade?
• How has the portrayal of minorities in the media changed?

Current Events

• What have been the impacts of China's one child policy?
• How have the goals of feminists changed over the decades?
• How has the Trump presidency changed international relations?
• Analyze the history of the relationship between the United States and North Korea.
• What factors contributed to the current decline in the rate of unemployment?
• What have been the impacts of states which have increased their minimum wage?
• How do US immigration laws compare to immigration laws of other countries?
• How have the US's immigration laws changed in the past few years/decades?
• How has the Black Lives Matter movement affected discussions and view about racism in the US?
• What impact has the Affordable Care Act had on healthcare in the US?
• What factors contributed to the UK deciding to leave the EU (Brexit)?
• What factors contributed to China becoming an economic power?
• Discuss the history of Bitcoin or other cryptocurrencies  (some of which tokenize the S&P 500 Index on the blockchain) .
• Do students in schools that eliminate grades do better in college and their careers?
• Do students from wealthier backgrounds score higher on standardized tests?
• Do students who receive free meals at school get higher grades compared to when they weren't receiving a free meal?
• Do students who attend charter schools score higher on standardized tests than students in public schools?
• Do students learn better in same-sex classrooms?
• How does giving each student access to an iPad or laptop affect their studies?
• What are the benefits and drawbacks of the Montessori Method ?
• Do children who attend preschool do better in school later on?
• What was the impact of the No Child Left Behind act?
• How does the US education system compare to education systems in other countries?
• What impact does mandatory physical education classes have on students' health?
• Which methods are most effective at reducing bullying in schools?
• Do homeschoolers who attend college do as well as students who attended traditional schools?
• Does offering tenure increase or decrease quality of teaching?
• How does college debt affect future life choices of students?
• Should graduate students be able to form unions?

• What are different ways to lower gun-related deaths in the US?
• How and why have divorce rates changed over time?
• Is affirmative action still necessary in education and/or the workplace?
• Should physician-assisted suicide be legal?
• How has stem cell research impacted the medical field?
• How can human trafficking be reduced in the United States/world?
• Should people be able to donate organs in exchange for money?
• Which types of juvenile punishment have proven most effective at preventing future crimes?
• Has the increase in US airport security made passengers safer?
• Analyze the immigration policies of certain countries and how they are similar and different from one another.
• Several states have legalized recreational marijuana. What positive and negative impacts have they experienced as a result?
• Do tariffs increase the number of domestic jobs?
• Which prison reforms have proven most effective?
• Should governments be able to censor certain information on the internet?
• Which methods/programs have been most effective at reducing teen pregnancy?
• What are the benefits and drawbacks of the Keto diet?
• How effective are different exercise regimes for losing weight and maintaining weight loss?
• How do the healthcare plans of various countries differ from each other?
• What are the most effective ways to treat depression ?
• What are the pros and cons of genetically modified foods?
• Which methods are most effective for improving memory?
• What can be done to lower healthcare costs in the US?
• What factors contributed to the current opioid crisis?
• Analyze the history and impact of the HIV/AIDS epidemic .
• Are low-carbohydrate or low-fat diets more effective for weight loss?
• How much exercise should the average adult be getting each week?
• Which methods are most effective to get parents to vaccinate their children?
• What are the pros and cons of clean needle programs?
• How does stress affect the body?
• Discuss the history of the conflict between Israel and the Palestinians.
• What were the causes and effects of the Salem Witch Trials?
• Who was responsible for the Iran-Contra situation?
• How has New Orleans and the government's response to natural disasters changed since Hurricane Katrina?
• What events led to the fall of the Roman Empire?
• What were the impacts of British rule in India ?
• Was the atomic bombing of Hiroshima and Nagasaki necessary?
• What were the successes and failures of the women's suffrage movement in the United States?
• What were the causes of the Civil War?
• How did Abraham Lincoln's assassination impact the country and reconstruction after the Civil War?
• Which factors contributed to the colonies winning the American Revolution?
• What caused Hitler's rise to power?
• Discuss how a specific invention impacted history.
• What led to Cleopatra's fall as ruler of Egypt?
• How has Japan changed and evolved over the centuries?
• What were the causes of the Rwandan genocide ?

• Why did Martin Luther decide to split with the Catholic Church?
• Analyze the history and impact of a well-known cult (Jonestown, Manson family, etc.)
• How did the sexual abuse scandal impact how people view the Catholic Church?
• How has the Catholic church's power changed over the past decades/centuries?
• What are the causes behind the rise in atheism/ agnosticism in the United States?
• What were the influences in Siddhartha's life resulted in him becoming the Buddha?
• How has media portrayal of Islam/Muslims changed since September 11th?

Science/Environment

• How has the earth's climate changed in the past few decades?
• How has the use and elimination of DDT affected bird populations in the US?
• Analyze how the number and severity of natural disasters have increased in the past few decades.
• Analyze deforestation rates in a certain area or globally over a period of time.
• How have past oil spills changed regulations and cleanup methods?
• How has the Flint water crisis changed water regulation safety?
• What are the pros and cons of fracking?
• What impact has the Paris Climate Agreement had so far?
• What have NASA's biggest successes and failures been?
• How can we improve access to clean water around the world?
• Does ecotourism actually have a positive impact on the environment?
• Should the US rely on nuclear energy more?
• What can be done to save amphibian species currently at risk of extinction?
• What impact has climate change had on coral reefs?
• How are black holes created?
• Are teens who spend more time on social media more likely to suffer anxiety and/or depression?
• How will the loss of net neutrality affect internet users?
• Analyze the history and progress of self-driving vehicles.
• How has the use of drones changed surveillance and warfare methods?
• Has social media made people more or less connected?
• What progress has currently been made with artificial intelligence ?
• Do smartphones increase or decrease workplace productivity?
• What are the most effective ways to use technology in the classroom?
• How is Google search affecting our intelligence?
• When is the best age for a child to begin owning a smartphone?
• Has frequent texting reduced teen literacy rates?

How to Write a Great Research Paper

Even great research paper topics won't give you a great research paper if you don't hone your topic before and during the writing process. Follow these three tips to turn good research paper topics into great papers.

#1: Figure Out Your Thesis Early

Before you start writing a single word of your paper, you first need to know what your thesis will be. Your thesis is a statement that explains what you intend to prove/show in your paper. Every sentence in your research paper will relate back to your thesis, so you don't want to start writing without it!

As some examples, if you're writing a research paper on if students learn better in same-sex classrooms, your thesis might be "Research has shown that elementary-age students in same-sex classrooms score higher on standardized tests and report feeling more comfortable in the classroom."

If you're writing a paper on the causes of the Civil War, your thesis might be "While the dispute between the North and South over slavery is the most well-known cause of the Civil War, other key causes include differences in the economies of the North and South, states' rights, and territorial expansion."

#2: Back Every Statement Up With Research

Remember, this is a research paper you're writing, so you'll need to use lots of research to make your points. Every statement you give must be backed up with research, properly cited the way your teacher requested. You're allowed to include opinions of your own, but they must also be supported by the research you give.

#3: Do Your Research Before You Begin Writing

You don't want to start writing your research paper and then learn that there isn't enough research to back up the points you're making, or, even worse, that the research contradicts the points you're trying to make!

Get most of your research on your good research topics done before you begin writing. Then use the research you've collected to create a rough outline of what your paper will cover and the key points you're going to make. This will help keep your paper clear and organized, and it'll ensure you have enough research to produce a strong paper.

What's Next?

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Christine graduated from Michigan State University with degrees in Environmental Biology and Geography and received her Master's from Duke University. In high school she scored in the 99th percentile on the SAT and was named a National Merit Finalist. She has taught English and biology in several countries.

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Read the March magazine issue on nuclear testing

Awaiting a decision on new research regulations, scientists pen dueling articles to shape ‘gain-of-function’ policies

By Matt Field | March 23, 2024

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Nearly 14 months have slipped by since an influential group of government science advisors recommended reforming rules governing the funding of US pathogen research. According to the group’s chair, Gerald Parker, that’s too many months. Parker, an associate dean at Texas A&M University, expected quicker action on the proposals to more stringently review experiments that make dangerous viruses more transmissible or virulent, estimating that it should have taken the government about six months to address the recommendations.

As they await a decision on policies for potential pandemic pathogen research, dueling camps of scientists have emerged, weighing in through a journal article, responses to the article, and even responses to the responses. Those camps are seeking to undercut or boost the advisory recommendations developed in the wake of the COVID pandemic—and to bolster or diminish the suspicion that a lab accident could have caused it.

Broadly speaking, the proposed recommendations—put forward by the National Science Advisory Board for Biosecurity, or NSABB—build on current government policy , established in 2017, that calls for a high-level review of research that risks creating potential pandemic pathogens, sometimes called gain-of-function research. Among scientists, the key question is: Will the proposals slow down research important for pandemic preparedness or ensure the adequate vetting of research that could spark a pandemic.

The answer to that question depends, in part, on what research the recommendations would apply to. One camp claims that virology work to enhance a pathogen’s transmissibility or virulence is a vanishingly small part of the virology field—and medically and industrially useless. The recommended policies would improve safety while applying extra review to just few research projects, this group says.

Another camp fears the proposals could touch on a wide swath of virology research, from vaccine development to disease surveillance. If such policies had been in place in 2019, they say, its questionable whether we would have had COVID vaccines in a year.

In a January article in the Journal of Virology , Angela Rasmussen, a virologist at the Vaccine and Infectious Disease Organization at the University of Saskatchewan in Canada, and 77 co-authors painted a picture of an existing and comprehensive web of regulation over virology research in the United States, including federal policies and regulations at the National Institutes of Health (NIH) and elsewhere. The recommendations by the NSABB would unnecessarily deter important work, they say.

Scientists are already shelving work related to vaccines and therapeutics in a climate of uncertainty, the scientists claim. Rasmussen told the Bulletin that several of her colleagues have been instructed to stop work that would not be subject to current policy and that does not meet the definitions of a potential pandemic pathogen “in anticipation of expanding the scope of oversight and due to increased scrutiny of biosafety.”

Current policy covers experiments that create pathogens that are both likely “highly” virulent and transmissible. The new recommendations would also include pathogens that are likely “moderately” virulent or transmissible. The recommendations require that the pathogen proposed for study pose a severe public health threat. They also remove a blanket exemption for vaccine research and disease surveillance.

The advisory recommendations would mean even work on non-pandemic viruses like seasonal influenza would first go through an onerous review before proceeding, Rasmussen and her co-authors say, because the current policy already covers work on the riskiest pathogens. “The [advisory group] recommendations, if adopted as proposed, would sweep much of virology research into new oversight by unnecessarily expanding oversight to pathogens that pose little risk,” the authors say.

But Richard Ebright, a professor of chemistry and chemical biology at Rutgers University who co-authored with 18 others a rebuttal letter this month in the Journal of Virology , disputes that the recommendations would affect much research. By early 2023, when they were issued, only three projects had gone through the existing review process for studies anticipated to create potential pandemic pathogens. The recommendations would apply to up to a dozen current projects, Ebright and his co-authors say. They say lapses in conducting proper review could lead to lab-generated pandemics. There have been many accidents and laboratory-acquired infections in the United States and elsewhere in the past.

The recommendations don’t expand the category of projects that should be reviewed, they just add clarity, Ebright told the Bulletin . “It does go beyond how the [current policy] was interpreted since it was introduced, which was to interpret that there is no such thing as a potential pandemic pathogen, and there certainly isn’t such thing as an enhanced potential pandemic pathogen,” Ebright said.

Rasmussen and her co-authors see ambiguity in the recommendations. She said a broad interpretation of the recommendations could “effectively mean that virtually every experiment involving an infectious viral pathogen would be subject to review.”

But Ebright said it’s clear to scientists what potential pandemic pathogens are; they come from a short list that includes some influenzas, some coronaviruses, and a handful of other organisms. “The grant proposals will say potential pandemic pathogen or pathogen of pandemic potential right in their project summaries or right in their titles,” Ebright said. “Every virologist knows exactly what that includes; every microbiologist knows what that includes.”

NIH, the primary federal funder of biological research, didn’t respond to a request for comment on the status of the advisory recommendations.

Parker, who stressed he was speaking only for himself, said that regardless of whether the Department of Health and Human Services, of which NIH is a part, approves the NSABB proposals, the department should make an implementation plan that describes various responsibilities and gives examples of research that should receive extra scrutiny. The process needs to be efficient, he said, acknowledging that biosecurity and biosafety are unfunded mandates.

In another recent response to Rasmussen’s article, Harvard epidemiologist Marc Lipsitch and three others pointed to efforts in states to ban gain-of-function research on potential pandemic pathogens and “extreme” budget cuts to areas of science. “We interpret these measures, at least in part, as harmful overreactions to what policymakers legitimately perceive as the scientific community’s reluctance to address public concerns about the risks of a laboratory-associated pandemic,” they wrote.

Rasmussen and her colleagues wrote in response, “Broad prohibitions on pathogen research will diminish response capacity at the expense of the American public.”

The sedate back-and-forth in the pages of the Journal of Virology over the potential policy changes masks a fiery and acrimonious debate on social media—one that began with divisions over how the COVID pandemic started four years ago. Rasmussen and some of her colleagues, who’ve participated in research suggesting the pandemic began when the COVID virus leapt from animals to people, recently sent a letter to Rutgers University, where Ebright, who has promoted the so-called “lab leak” theory of pandemic origins, works. They accused him and another colleague of harassment and endangering their safety. They cited posts calling them frauds and liars and comparing scientists to historical mass murderers like Khmer Rouge dictator Pol Pot.

But the researchers who believe it’s possible the COVID pandemic started with a laboratory accident of some sort in China claim they’ve been called plenty of names, too. A molecular biologist at the Broad Institute, Alina Chan, a prominent proponent of the lab leak theory, said she is also a victim.

“Alina has been subjected to more harassment than almost anyone, endangering her, including from highly-credentialed people who constantly complain about harassment,” The New York Times columnist Zeynep Tufekci posted on the X platform.

Efforts to tighten oversight of virology that creates potential pandemic pathogens began over a decade ago, when scientists in Wisconsin and the Netherlands mutated the H5N1 avian influenza virus so it could spread by air among mammals. This led to scientific debates, research moratoriums, and eventually the current NIH project review policies. Despite all this attention, the importance of these experiments can look different in retrospect.

Michael Imperiale, a microbiologist at the University of Michigan, who has written extensively about  gain-of-function research, cited hopes at the time of the experiments that they could aid in vaccine development or disease surveillance during a February interview with the Bulletin . “I think to a large degree that those experiments did not provide the types of actionable information that [it was] originally thought they were going to provide back when they were being done,” he said. They did show that H5N1 could evolve to spread in mammals, he said.

Parker, who has long experience working at high levels in US government biodefense operations, including a stint as commander of the US Army Medical Research Institute of Infectious Diseases, said he was at the Department of Health and Human Services and the Defense Department as the debate over the bird flu studies played out. “The results of that work did not change any of our acquisition plans. It didn’t change what we were doing with pre-pandemic H5N1 and our advanced development for a cell-based H5N1 vaccine. It didn’t change anything,” he said.

As far as government pandemic preparedness went, Parker said, they were “interesting studies.”

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Keywords: COVID-19 , NIH Topics: Biosecurity

Matt Field is an associate editor at the  Bulletin of the Atomic Scientists . Before joining the  Bulletin , he covered the White House,... Read More

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UC engineering student committed to improving education in STEM

Gibin raju is motivated by a desire to expand opportunities for underrepresented students.

At the University of Cincinnati, Gibin Raju was able to combine his passions for engineering and teaching. UC is home to a prolific engineering education program, one of the first of its kind.

As a doctoral student, Raju uses biomarkers like eye-tracking and electrodermal activity to understand how students go about solving problems in engineering. He was named Graduate Student Engineer of the Month by the College of Engineering and Applied Science. 

Why did you choose UC?

Gibin Raju is a doctoral student in engineering education at UC. Photo/Provided

Choosing UC for my master's in aerospace engineering was influenced by a blend of things. Initially, the university's reputation for fostering engineering excellence caught my attention. Engaging conversations with current graduate students in the program provided me with invaluable insights into the supportive academic environment at CEAS. Their shared experiences highlighted the university's commitment to student success in the engineering field, making it an appealing choice. 

While finishing my aerospace engineering degree, my career aspirations shifted towards integrating my engineering expertise with my passion for education. This led me to join UC's College of Education, Criminal Justice and Human Services as an adjunct faculty and start pursuing another master's degree in educational studies. UC's graduate program in engineering education presented a unique opportunity to venture into an emerging field that aligned perfectly with my interests and CEAS being among the first to offer such a program solidified my decision. This confluence of academic excellence, a supportive community, and innovative programs made the University of Cincinnati the ideal choice for my higher education journey. 

Why did you choose your field of study?

My journey into the field of engineering education is a testament to my passion for teaching and a curiosity that transcends boundaries. From tutoring my peers in middle school to navigating the rich tapestry of teaching as an international student at UC, my academic voyage has been extraordinary. The transition from an undergraduate degree in India to advanced studies in the U.S. illuminated the stark differences in educational approaches. 

The field of engineering education, with its noble aim of arming higher education faculty with innovative teaching tools, resonated with my belief in the transformative power of education. Engineering, a field where early careers are often research-heavy, traditionally leaves little room for pedagogical refinement. This realization propelled me into the heart of engineering education, driven by a mission to elevate teaching methodologies. Immersing myself in courses about learning theories, teaching strategies for engineering, and curriculum design for diverse student bodies has been exhilarating. 

As engineering education continues to evolve, I am thrilled by the prospect of discovering and implementing cutting-edge teaching techniques on optimal learning practices. My commitment to enhancing engineering education is not just a career choice — it's a lifelong journey fueled by passion, curiosity, and the desire to make a lasting impact. 

Describe your research work. What motivates you?

Gibin Raju researches the connection between spatial visualization and engineering design skills of students. Photo/provided

At the heart of my research lies a commitment to fostering diversity, equity, and inclusion in engineering. My dissertation delves into the connection between spatial visualization and engineering design skills of undergraduate students. My work aims to illuminate the relationship between these occurrences through a cognitive lens. This is done by employing advanced biomarkers like eye-tracking and electrodermal activity to understand how students solve problems, and if they were stressed during the solving process. The objective is to enhance students' spatial abilities during their formative years of undergraduate education to equip them with necessary design skills. 

Driven by a desire to expand opportunities for underrepresented and neurodiverse students in STEM, my efforts extend to developing innovative methodologies that amplify their engagement and access to resources. Recently, I have explored the impact of summer bridge programs and experiential learning opportunities on these students, showcasing the power of early exposure to STEM. 

I am dedicated to education and am passionate in the belief that no student should face learning barriers due to miscommunication with instructors. This conviction led me to focus on enhancing the teaching pedagogies of students, ensuring a better educational journey for all. Through my work, I aspire to dismantle obstacles and pave the way for a more diverse, skilled generation of engineers, ready to tackle the challenges of tomorrow. 

What are some of the most impactful experiences during your time at UC?

I had the privilege of collaborating with some of the most esteemed researchers in my domain. This experience equipped me with insights and skills that have become the cornerstone of my professional identity. Additionally, my involvement in community outreach initiatives to foster STEM interest among underrepresented groups was equally enriching. These endeavors not only enhanced my educational journey but deepened my understanding of engineers' critical role in society and the importance of making education accessible to all. 

What are a few of your accomplishments of which you are most proud?

My graduate journey at UC has been full of leadership, advocacy, and community building. The most transformative experience was during my tenure as President of the Graduate Student Government . In this role, I championed the academic and professional aspirations of our student community, achieving milestones that have a lasting mark on campus. 

Under my leadership, we achieved a very significant increase in research fellowship funding and the conference travel award budget. This expansion ensured our graduate students could showcase their research and enhance their professional development on a global stage. 

I successfully advocated for comprehensive health insurance for part-time students, which led to the funding of 50 applicants for the academic year. This initiative was representative of our commitment to ensuring the well-being and academic success of our students. We were also able to add resources and events tailored to supporting the mental health needs of graduate students. 

I founded the Graduate Student Association for the Department of Engineering and Computing Education and established the UC chapter of the American Society for Engineering Education . These organizations are dedicated to fostering a supportive and inclusive academic environment for students pursuing careers in STEM. 

Our group initiates mentorship programs for high school, undergraduate, and graduate students, aiming to pave the way for future leaders in academia. We are also committed to raising awareness about critical issues such as mental health, accessibility, and diversity in engineering. I extend a heartfelt invitation to students passionate about these causes to join us in our mission to create a supportive community for all. 

When do you expect to graduate? What are your plans after earning your degree?

I'm thrilled to share that I will be donning my graduation cap in the spring of 2024! After receiving my degree, I'm excited to embark on my journey into academia as either a postdoctoral fellow or an assistant professor on the tenure track. This next chapter will enable me to dive deeper into my research interests, contributing groundbreaking insights to my field. The path ahead is brimming with potential, and I'm eager to explore the vast horizons of knowledge and innovation. 

Do you have any other hobbies, experiences, or involvements you want to share?

Outside of my academic and research pursuits, I enjoy photography, cooking, traveling, and volunteering at local schools. Being part of the university's administrative committee of UC has also been a highlight, allowing me to engage with leaders who help to advocate the needs of graduate students at UC. I also serve on the national chapter of the American Society for Engineering Education as a delegate working towards developing welcoming environments for all engineers to thrive. 

Interested in engineering graduate programs?

See what the College of Engineering and Applied Science has to offer. 

Featured image at top: Gibin Raju uses eye-tracking equipment to gather data on how students solve engineering problems. Photo/Provided

• Student Experience
• Aerospace Engineering and Engineering Mechanics
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• Engineering Education

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Engineering students present senior capstone projects digitally.

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May 6, 2022

Graduating engineering undergraduates from the University of Cincinnati’s College of Engineering and Applied Science gathered for the inaugural CEAS Expo in April to showcase their senior capstone projects to more than 500 attendees, including faculty, staff, alumni and industry representatives. The event, organized by the college and CEAS Tribunal student government, was held in downtown Cincinnati at the Duke Energy Convention Center.

First-year students get a head start as researchers

August 25, 2020

University of Cincinnati’s Protégé Undergraduate Research Program gives first-year College of Engineering and Applied Science students early access to research experience through a paid summer position working with faculty researchers or industry partners.

The problem with making all academic research free

A new funding model for journals could deprive the world of valuable research in the humanities and social sciences..

There has been an earthquake in my corner of academia that will affect who teaches in prestigious universities and what ideas circulate among educated people around the world.

And it all happened because a concept rooted in good intentions — that academic research should be “open access,” free for everyone to read — has started to go too far.

The premise of open-access publishing is simple and attractive. It can cost libraries thousands of dollars a year to subscribe to academic journals, which sometimes means only academics affiliated with wealthy colleges and universities may access that research. But under open-access publishing, nearly anyone with an internet connection can find and read those articles for free. Authors win, because they find more readers. Academics around the world benefit, because they can access the latest scholarship. And the world wins, because scientific and intellectual progress is facilitated by the free exchange of ideas.

By now this model has taken hold in the natural sciences, especially in biology and biomedicine; during the pandemic many publishers removed paywalls from articles about vaccines and treatments. The Biden administration requires federally funded scholarly publications to be made freely available without any delay.

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However, there is no such thing as a free academic article. Even with digital distribution, the expenses of running a journal are considerable. These costs include hosting the websites where people submit, peer-review, and edit articles; copyediting; advertising; preserving journal archives; and maintaining continuity as editors come and go.

As a result, unless journals have a source of revenue other than subscription fees, any move toward open access raises the question of who will cover the costs of publication.

One answer is that the money will come from authors themselves or their academic institutions or other backers. This works well enough in the natural sciences, because those researchers are often funded by grants, and some of that money can be set aside to cover a journal’s fees for publishing scientific articles. The Bill and Melinda Gates Foundation demands that all research funded by the foundation, including the underlying data, be published open access.

According to an MIT study , however, only a small fraction of scholars in the humanities publish their articles on an open-access basis. Unlike biologists and biomedical engineers, humanities scholars such as philosophers and historians do not get grants that can cover the publishing costs.

This means that if open access is to take hold in those fields as well — as many publishers and academics are advocating — the costs will have to be covered by some foundation or other sponsor, by the scholars’ institutions, or even by the scholars themselves. And all these models have serious downsides.

I’m a political philosopher. The earthquake in my field that I mentioned earlier shook one of our most prominent journals: the Journal of Political Philosophy.

Publishing an article in this journal has long made the difference between whether a candidate gets hired, tenured, or promoted at an elite institution of higher education. The high quality has stemmed in large part from the rigorous approach of the founding editor, Robert Goodin.

At the end of 2023, the publisher, Wiley, terminated its contract with Goodin. The reasons were not immediately clear, and over 1,000 academics, including me, signed a petition stating that we would not serve on the editorial board or write or review for the journal until Wiley reinstates Goodin. I recently attended a panel at an American Philosophical Association conference where philosophers voiced their anger and puzzlement about the situation.

One source of the problem appears to be that Wiley now charges the authors of an article or their institutions $3,840 to get published open access in the journal.

The Journal of Political Philosophy is actually hybrid open access, which means it waives the article processing charges for authors who permit their work to appear behind a subscription-only paywall. Nonetheless, Goodin and Anna Stilz , a Princeton professor and Journal of Political Philosophy editorial board member, point out that publishers like Wiley now have a strong incentive to favor open-access articles.

In the old model, in which university libraries subscribed to journals, editors were mainly incentivized to publish first-rate material that would increase subscriptions. In the open-access model, however, now that authors or their universities must cover the costs of processing articles, publishers of humanities journals seem to be incentivized to boost revenue by accepting as many articles as possible. According to Goodin , open access has “been the death knell of quality academic publishing.” The reason that Goodin lost his job, Goodin and Stilz imply, is that Wiley pressured Goodin to accept more articles to increase Wiley’s profits, and he said no. (Wiley representatives say that lines of communication had collapsed with Goodin.)

Early this year, Goodin cofounded a new journal titled simply Political Philosophy . The journal will be published by the Open Library of Humanities, which is subsidized by libraries and institutions around the world. But this version of open-access publishing does not have the financial stability of the old subscription model. Scholars affiliated with the Open Library of Humanities have pointed out that the project has substantial overhead costs, and it relied on a grant from the Andrew W. Mellon Foundation that has already ended. The Open Library of Humanities is an experiment, and I hope that it works, but as of now it publishes only 30 journals , compared with the 1,600 journals that Wiley publishes.

The fact remains that no one has satisfactorily explained how open access could work in the humanities and social sciences.

In his 2023 book “ Athena Unbound : Why and How Scholarly Knowledge Should Be Free for All,” UCLA history professor Peter Baldwin attempts an answer. He points to Latin America, where some national governments cover all expenses of academic publishing. But this proposal ignores the fact that the governments of the United States and other nations probably do not want to pay for humanities and social sciences journals.

Baldwin also floats the idea of preprint depositories where academics could share documents on the cloud before they have undergone the (somewhat expensive) process of peer review. But this means that academics would lose the benefits that come from getting double-blind feedback from one’s peers. This idea would reduce the costs of publishing a journal article, but it would turn much academic writing into fancy blogging.

Ultimately, Baldwin’s solution is that authors might “have to participate directly, giving them skin in the game and helping contain costs.” This means academics might ask their employers to pay the article processing charges, ask a journal for the processing fees to be waived, or dig into their own pockets to pay to publish.

And it might mean less gets published overall. The journal Government and Opposition, published by Cambridge University Press, is entirely open access and charges $3,450 for an article to be published. I’d have to apply for a discount or a waiver to publish there. Or I could do what political philosophers in Japan and Bosnia and Herzegovina have told me they do: avoid submitting to open-access journals. Their universities will not cover their article processing charges except maybe in the top journals, and even the reduced fees can run into hundreds of dollars that these professors do not have.

In “Athena Unbound,” Baldwin notes that Harvard subscribes to 10 times as many periodicals as India’s Institute of Science. One can bemoan this fact, but one may also appreciate that Harvard’s largesse spread enough subscription revenue around to reputable journals to enable academics to avoid paying to publish in them, no matter whether they teach at regional state schools, non-elite private schools, or institutions of higher education in poor countries. For all its flaws, the old model meant that when rich alumni donated to their alma maters, it increased library budgets and thereby made it possible for scholars of poetry and state politics to run and publish in academic journals.

Until we have more evidence that open-access journals in the humanities and social sciences can thrive in the long run, academics need to appreciate the advantages of the subscription model.

Nicholas Tampio is a professor of political science at Fordham University in New York City.

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ESB and Trinity’s ADAPT and CONNECT research centres to accelerate technology innovation in energy sector

Posted on: 25 March 2024

The research involves two main projects with a goal of enabling large energy users to make better energy choices, helping the environment and supporting the Government's green agenda.

Team members pictured in front of ‘Gaia’ in Trinity College Dublin’s Long Room symbolising the commitment to understanding and preser ving the intricate connections within our world. (L - R) Chief Innovation and Enterprise Officer at Trinity, Dr Michelle Olmstead; Prof. Marco Ruffini, CONNECT at Trinity; Geraldine Moloney, ESB; Prof Hitesh Tewari, ADAPT at Trinity.

The research will help accelerate technology innovation and drive the energy transition to reach Ireland’s carbon targets. The collaborative projects with CONNECT and ADAPT will have clear benefits for society in tackling the climate crisis. Each project will run for 18 months.

The partnership with CONNECT, which will be led by Professor Marco Ruffini, focuses on harnessing the extensive data available from the electrical grid, encompassing energy sources, demand, and predictive models. The project will then explore the effects of providing Large Energy Users (LEUs), such as data centres and pharmaceutical plants, with accurate, market-based data models to optimise energy demand.

The partnership with ADAPT focuses on the efficient generation and distribution of Guarantee of Origin (GO) certificates, which verify that a unit of power was produced from renewable sources.  The research will address the current challenges in the GO certification market, including the lengthy processing time, and exploit technologies such as blockchain to explore more efficient mechanisms for real-time generation and distribution of GO certificates, enhancing transparency and ensuring timely consumption by green energy users.

Increased energy demand has led to the depletion of fossil fuel reserves, resulting in higher generation costs and increased carbon emissions. To combat these challenges, ESB has been focusing on integrating renewable energy resources to bridge the demand-supply gap. 

Geraldine Moloney, Head of New Ventures at ESB , expressed her excitement about the partnership, stating:  “ESB is delighted to partner with ADAPT and CONNECT at Trinity College Dublin and hopes to harness the power of research and innovation to advance us on our Net Zero emissions target by 2040. Tackling these defining challenges requires collaboration with like-minded partners, so this investment will help set a new standard for energy consumption and help drive the energy transition. I look forward to seeing the creative solutions developed through these collaborations.”

Professor Marco Ruffini, Principal Investigator at CONNECT and Professor in Computer Science at Trinity , said: “Efficient resource allocation and energy management are critical for both environmental sustainability and cost-effectiveness. In this collaboration with ESB, we will develop an intelligent task scheduler that takes into account real-time energy price fluctuations at multiple locations and allocates computation tasks to locations where energy is more cost-effective and greener. This will have the effect of considerably reducing the overall operational expenditure and maximising the use of green energy.  

“At CONNECT we have developed globally recognised expertise in the area of Optical Spectrum as a Service. We will leverage this expertise in this project to show how it can be effectively used to pre-book capacity and move large amounts of data at low cost in order to achieve substantial cost reduction.”

Professor Hitesh Tewari, Funded Investigator at ADAPT, and Assistant Professor in Computer Science at Trinity , said:  “ Our collaboration with ESB is a fantastic opportunity to showcase the power of Distributed Ledger Technology, commonly referred to as Blockchains, for the real-time creation and distribution of Guarantee of Origin (GO) certificates in a secure, timely and transparent manner. This will enable Large Energy Users (LEUs) to say with a very high level of confidence that they are consuming electricity generated from renewable sources to power their enterprise operations in Ireland.”

Chief Innovation and Enterprise Officer at Trinity College Dublin, Dr Michelle Olmstead , said: “This partnership underscores ESB's dedication to leading the energy transition through innovative solutions and collaborative research.  Trinity is committed to creating real impact from our research expertise, in partnering with ambitious organisations like ESB, collectively driving a culture of innovation and a spirit of entrepreneurship to realise solutions to climate change.  Partnership is key to Trinity’s Innovation & Enterprise strategy; to curate a globally connected innovation community.”

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'Curious Conversations' podcast: Audrey Ruple talks about the Dog Aging Project

• Travis Williams

25 Mar 2024

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Audrey Ruple joined Virginia Tech’s “Curious Conversations” to talk about the Dog Aging Project, the largest-known study of dog health that aims to understand the keys to healthy aging in dogs and the risks to their health. She explained what information they are collecting, what it means for dogs, and how it might also be used to better understand human health.

About Ruple

Ruple is associate professor of quantitative epidemiology and the Metcalf Professor of Veterinary Medical Informatics in the Virginia-Maryland College of Veterinary Medicine. She is also the program director of the biomedical and veterinary sciences graduate program and serves on the executive leadership team of the Dog Aging Project.

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Three takeaways

The Dog Aging Project analyzes data that includes lifestyle, health events, diet, exercise, and environmental factors to gain insights into the aging process and its impact on dogs' health.

Dogs are good sentinels for human health hazards, and studying their lifespans provides valuable information about exposure science and latency periods.

The project has already made significant discoveries such as characterizing the normal aging process in dogs and developing frailty indices.

Audrey Ruple collaborates with Dog Aging Project, largest-known study of dog health

Veterinary college’s Audrey Ruple inducted into two scientific honor societies

About the podcast

"Curious Conversations" is a series of free-flowing conversations with Virginia Tech researchers that take place at the intersection of world-class research and everyday life. Produced and hosted by Virginia Tech writer and editor Travis Williams, university researchers share their expertise and motivations as well as the practical applications of their work in a format that more closely resembles chats at a cookout than classroom lectures. New episodes are shared each Tuesday.

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• Virginia-Maryland College of Veterinary Medicine

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• CAREER FEATURE
• 08 February 2023

How to wrap up research projects gracefully

Andy Tay is a freelance writer in Singapore.

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Some research projects arrive gracefully at a natural conclusion, such as when a trainee leaves the laboratory. Others come to a screeching halt when funding runs out. Still more dance along the edge of viability, daring lab heads to pull the plug and move on. Four researchers share best practices on deciding when projects should end, and how best to wrap them up or redesign them. They advocate using approaches that ensure that colleagues’ interests, feelings and career prospects are protected in the process.

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Nature 615 , 549-550 (2023)

doi: https://doi.org/10.1038/d41586-023-00377-7

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Methodology

Research Methods | Definitions, Types, Examples

Research methods are specific procedures for collecting and analyzing data. Developing your research methods is an integral part of your research design . When planning your methods, there are two key decisions you will make.

First, decide how you will collect data . Your methods depend on what type of data you need to answer your research question :

• Qualitative vs. quantitative : Will your data take the form of words or numbers?
• Primary vs. secondary : Will you collect original data yourself, or will you use data that has already been collected by someone else?
• Descriptive vs. experimental : Will you take measurements of something as it is, or will you perform an experiment?

Second, decide how you will analyze the data .

• For quantitative data, you can use statistical analysis methods to test relationships between variables.
• For qualitative data, you can use methods such as thematic analysis to interpret patterns and meanings in the data.

Table of contents

Methods for collecting data, examples of data collection methods, methods for analyzing data, examples of data analysis methods, other interesting articles, frequently asked questions about research methods.

Data is the information that you collect for the purposes of answering your research question . The type of data you need depends on the aims of your research.

Qualitative vs. quantitative data

Your choice of qualitative or quantitative data collection depends on the type of knowledge you want to develop.

For questions about ideas, experiences and meanings, or to study something that can’t be described numerically, collect qualitative data .

If you want to develop a more mechanistic understanding of a topic, or your research involves hypothesis testing , collect quantitative data .

You can also take a mixed methods approach , where you use both qualitative and quantitative research methods.

Primary vs. secondary research

Primary research is any original data that you collect yourself for the purposes of answering your research question (e.g. through surveys , observations and experiments ). Secondary research is data that has already been collected by other researchers (e.g. in a government census or previous scientific studies).

If you are exploring a novel research question, you’ll probably need to collect primary data . But if you want to synthesize existing knowledge, analyze historical trends, or identify patterns on a large scale, secondary data might be a better choice.

Descriptive vs. experimental data

In descriptive research , you collect data about your study subject without intervening. The validity of your research will depend on your sampling method .

In experimental research , you systematically intervene in a process and measure the outcome. The validity of your research will depend on your experimental design .

To conduct an experiment, you need to be able to vary your independent variable , precisely measure your dependent variable, and control for confounding variables . If it’s practically and ethically possible, this method is the best choice for answering questions about cause and effect.

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Your data analysis methods will depend on the type of data you collect and how you prepare it for analysis.

Data can often be analyzed both quantitatively and qualitatively. For example, survey responses could be analyzed qualitatively by studying the meanings of responses or quantitatively by studying the frequencies of responses.

Qualitative analysis methods

Qualitative analysis is used to understand words, ideas, and experiences. You can use it to interpret data that was collected:

• From open-ended surveys and interviews , literature reviews , case studies , ethnographies , and other sources that use text rather than numbers.
• Using non-probability sampling methods .

Qualitative analysis tends to be quite flexible and relies on the researcher’s judgement, so you have to reflect carefully on your choices and assumptions and be careful to avoid research bias .

Quantitative analysis methods

Quantitative analysis uses numbers and statistics to understand frequencies, averages and correlations (in descriptive studies) or cause-and-effect relationships (in experiments).

You can use quantitative analysis to interpret data that was collected either:

• During an experiment .
• Using probability sampling methods .

Because the data is collected and analyzed in a statistically valid way, the results of quantitative analysis can be easily standardized and shared among researchers.

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If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Chi square test of independence
• Statistical power
• Descriptive statistics
• Degrees of freedom
• Pearson correlation
• Null hypothesis
• Double-blind study
• Case-control study
• Research ethics
• Data collection
• Hypothesis testing
• Structured interviews

Research bias

• Hawthorne effect
• Unconscious bias
• Recall bias
• Halo effect
• Self-serving bias
• Information bias

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
• If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

Methodology refers to the overarching strategy and rationale of your research project . It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.

Methods are the specific tools and procedures you use to collect and analyze data (for example, experiments, surveys , and statistical tests ).

In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section .

In a longer or more complex research project, such as a thesis or dissertation , you will probably include a methodology section , where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.

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Other students also liked, writing strong research questions | criteria & examples.

• What Is a Research Design | Types, Guide & Examples
• Data Collection | Definition, Methods & Examples

More interesting articles

• Between-Subjects Design | Examples, Pros, & Cons
• Cluster Sampling | A Simple Step-by-Step Guide with Examples
• Confounding Variables | Definition, Examples & Controls
• Construct Validity | Definition, Types, & Examples
• Content Analysis | Guide, Methods & Examples
• Control Groups and Treatment Groups | Uses & Examples
• Control Variables | What Are They & Why Do They Matter?
• Correlation vs. Causation | Difference, Designs & Examples
• Correlational Research | When & How to Use
• Critical Discourse Analysis | Definition, Guide & Examples
• Cross-Sectional Study | Definition, Uses & Examples
• Descriptive Research | Definition, Types, Methods & Examples
• Ethical Considerations in Research | Types & Examples
• Explanatory and Response Variables | Definitions & Examples
• Explanatory Research | Definition, Guide, & Examples
• Exploratory Research | Definition, Guide, & Examples
• External Validity | Definition, Types, Threats & Examples
• Extraneous Variables | Examples, Types & Controls
• Guide to Experimental Design | Overview, Steps, & Examples
• How Do You Incorporate an Interview into a Dissertation? | Tips
• How to Do Thematic Analysis | Step-by-Step Guide & Examples
• How to Write a Literature Review | Guide, Examples, & Templates
• How to Write a Strong Hypothesis | Steps & Examples
• Inclusion and Exclusion Criteria | Examples & Definition
• Independent vs. Dependent Variables | Definition & Examples
• Inductive Reasoning | Types, Examples, Explanation
• Inductive vs. Deductive Research Approach | Steps & Examples
• Internal Validity in Research | Definition, Threats, & Examples
• Internal vs. External Validity | Understanding Differences & Threats
• Longitudinal Study | Definition, Approaches & Examples
• Mediator vs. Moderator Variables | Differences & Examples
• Mixed Methods Research | Definition, Guide & Examples
• Multistage Sampling | Introductory Guide & Examples
• Naturalistic Observation | Definition, Guide & Examples
• Operationalization | A Guide with Examples, Pros & Cons
• Population vs. Sample | Definitions, Differences & Examples
• Primary Research | Definition, Types, & Examples
• Qualitative vs. Quantitative Research | Differences, Examples & Methods
• Quasi-Experimental Design | Definition, Types & Examples
• Questionnaire Design | Methods, Question Types & Examples
• Random Assignment in Experiments | Introduction & Examples
• Random vs. Systematic Error | Definition & Examples
• Reliability vs. Validity in Research | Difference, Types and Examples
• Reproducibility vs Replicability | Difference & Examples
• Reproducibility vs. Replicability | Difference & Examples
• Sampling Methods | Types, Techniques & Examples
• Semi-Structured Interview | Definition, Guide & Examples
• Simple Random Sampling | Definition, Steps & Examples
• Single, Double, & Triple Blind Study | Definition & Examples
• Stratified Sampling | Definition, Guide & Examples
• Structured Interview | Definition, Guide & Examples
• Survey Research | Definition, Examples & Methods
• Systematic Review | Definition, Example, & Guide
• Systematic Sampling | A Step-by-Step Guide with Examples
• Textual Analysis | Guide, 3 Approaches & Examples
• The 4 Types of Reliability in Research | Definitions & Examples
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• What Is Predictive Validity? | Examples & Definition
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• What Is Purposive Sampling? | Definition & Examples
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• What Is Qualitative Research? | Methods & Examples
• What Is Quantitative Observation? | Definition & Examples
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US Supreme Court abortion pill fight brings claims of distorted science

ABORTION CRACKDOWN

Emergency room visits.

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Reporting by Andrew Chung in New York; Editing by Will Dunham

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China, battling low birth rates and high costs, encourages frugal weddings

Young couples in China planning "simple" weddings, rather than traditional banquets with hundreds of guests, was one of the top hits online after an article urging more frugal nuptials was published by the government body in charge of women's rights.