Category Archives: repository

Joel Meyer on sharing environmental health data for the public good

500 Datasets, 5 Researchers, 5 StoriesThis story is part of a fall 2026 series celebrating 500 published datasets in the Duke Research Data Repository (RDR) by spotlighting 5 Duke researchers who make their work more transparent, discoverable, and reusable.

Joel Meyer, Duke ProfessorJoel Meyer is a Sally Kleberg Distinguished Professor in the Nicholas School of the Environment, Director of the Integrated Toxicology and Environmental Health Program, and the Associate Director of Undergraduate Studies. Dr. Meyer is also a Principal Investigator within the Superfund Research Center. The Superfund Research Center focuses on early, low-dose exposures to environmental contaminants and their developmental impacts, changes usually only evident later in life (NIEHS grant, P42ES010356). The Superfund Research Center has a collection within the Duke Research Data Repository to highlight the public data generated by the Center’s investigators and demonstrate compliance with NIH data management and sharing policy. The Collection currently contains almost 30 datasets; the Center also has shared data in disciplinary repositories linked on their website.

Dr. Meyer shared with us his thoughts on sharing environmental health data within the Duke Research Data Repository (RDR).

Meyer Lab
The Meyer Lab, April 2026

Tell us a little about the research and the kinds of data shared through the RDR. What should someone outside your field know about them?

My group studies the effects of pollutants on health, largely using cells in culture and the small nematode (worm) Caenorhabditis elegans. We gather a wide range of data, from molecular impacts (e.g., does the chemical cause DNA damage or oxidative stress) to cellular effects (e.g., does the chemical cause neurons to degenerate or malfunction) to whole-organism effects (e.g., does the chemical inhibit growth or reproduction). We often generate datasets with many thousands of data points per experiment.

Why do you choose to share your research data?

I think it is important that other researchers, as well as other interested people in general, be able to access the data for themselves. They might want to analyze it in a different way, or see if they agree with our analysis, or combine the data with other data for larger-scale studies. I also think it is our responsibility to make this data generally available since most of it was generated with taxpayer money. Finally, I hope that this also promotes a sense of scientific transparency.

What do you hope other researchers, or other audiences, might be able to do with the data you’ve shared?

Superfund Research Center Team
Superfund Research Center Team

I hope that it will be useful to regulators who are trying to protect the public from negative health effects of pollutants. I also hope that the data may be of use to community members, nonprofit organizations, and other researchers. In fact, we recently published a paper on how to do academic research in a way that is broadly useful (open access!), and the use of data repositories, like the RDR, is one of the things we highlight.

What has your experience been like working with the Research Data Repository team? Is there anything about the publishing or curation process that has been particularly useful to you?

It has been great! The team has been very fast to respond to questions and provide feedback, and very helpful regarding how to describe and structure the data for maximum utility. Frankly, they and the process have improved our own processes for organizing and storing data and metadata.

What would you say to another Duke researcher who is considering sharing their data?

Do it!

Explore Dr Meyer’s and other Duke researcher’s datasets published in the Superfund Research Center RDR Collection.

If your research grant or project would like to create a Collection within the RDR to more easily highlight datasets, feel free to contact us!

The RDR team thanks Dr. Meyer for his participation and supporting data publishing at Duke. For questions about the RDR contact: datamanagement@duke.edu

 

 

 

Patrick Charbonneau on why he shares his data with the world

This story is part of a fall 2026 series celebrating 500 published datasets in the Duke Research Data Repository by spotlighting 5 Duke researchers who make their work more transparent, discoverable, and reusable.

Dr. Patrick Charbonneau maintains appointments in both Chemistry and Physics. Dr. Charbonneau published the 500th dataset within the Duke Research Data Repository (RDR) and is the top depositor. He shared with us his thoughts on data sharing and the use of the RDR.

Dr. Patrick CharbonneauTell us a little about the research and the kinds of data shared through the RDR. What should someone outside your field know about them?

My group works at the intersection of theoretical chemistry and physics, using statistical mechanics and computational methods to understand complex systems. The datasets we share typically contain the numerical data behind published figures, along with code and documentation needed to understand or reproduce the results.

Why do you choose to share your research data? Has your thinking about data sharing changed over time?

Early in my career, archiving meant asking students and postdocs, usually as they were leaving, to organize their files on a departmental drive. I eventually realized that this approach was both stressful and fragile. We therefore shifted to preparing data, code, and documentation alongside each manuscript, so that sharing becomes part of publishing rather than something done retrospectively. An unexpected benefit is that preparing a dataset for others to use provides an additional check on the research itself.

What do you hope other researchers, or other audiences, might be able to do with the data you’ve shared?

Dr. Charbonneau with then graduate student, Lin Fu, in 2012

I want our publications to remain reusable without having to track down a former student, postdoc, or me(!) years later. Surprisingly, this happened twice just this summer for papers from before we routinely deposited datasets; I have since deposited those data. But I also like that we cannot entirely predict what the data might eventually be useful for. A dataset created to answer one question may later become useful for comparison, methodological development, teaching, or a question we had never considered.

What has your experience been like working with the Duke Research Data Repository team? Is there anything about the publishing or curation process that has been particularly useful to you?

The RDR team has made data publication remarkably easy to incorporate into our research workflow. The curatorial oversight is particularly valuable: having another set of eyes on the organization, documentation, and long-term usability of a dataset helps turn files associated with a paper into a durable research product. Over time, working with the RDR has made depositing data simply part of what we consider completing a publication.

What would you say to another Duke researcher who is considering sharing their data?

Start small. There is no need to solve every possible question about what should be preserved before making a first deposit. Sharing even the numerical values behind published figures is a useful beginning, and once the process becomes part of the publication workflow, expanding what you share becomes much easier. In my experience, the cost is small, especially with the support of the RDR team, while the benefits for transparency, preservation, and future reuse can be substantial. Also, LLMs now make writing useful README files easier than ever.

A tray of pieces of sucre à la crème
A tray of pieces of sucre à la crème, the data from the associated article is published in the RDR

Has anything interesting or unexpected happened as a result of sharing data?

In recent years, I started publishing articles on the history of science and related questions. Surprisingly, the datasets I deposited to accompany those articles—oral history interviews, textual corpora, and archival documents—are among the most consulted of all my deposits. I certainly didn’t expect my humanities datasets to be the popular ones!

Charbonneau’s humanities datasets: Data from: Sucre à la crème: Origin and Trajectory of an Authentic Québec Confection; Data from: Pralines des Voyageurs: An Iconic Intercultural Food; Data from: Elizabeth Monroe Boggs: From Quantum Chemistry to the Manhattan Project

Additional selected datasets:
Simons Collaboration on Cracking the Glass Problem RDR Collection
Data from: Decorrelation of the static and dynamic length scales in hard-sphere glass formers (500th dataset published in RDR)

The RDR team thanks Dr. Charbonneau for his participation and supporting data publishing at Duke. For questions about the RDR contact: datamanagement@duke.edu

 

Announcing: Duke Research Data Repository 2.0

We are happy to announce that the Duke Research Data Repository (RDR) has updated our platform to provide enhancements for data depositors. The platform is implemented in partnership with Duke University Libraries and TIND, a spinoff of CERN (see the press release). Below we explain what you need to know about this change.

We also have this short video demonstrating key changes and features.

What is changing?

  • Homepage: There is a new landing page with slightly different navigation. All key documentation can be found under the “About” or “Resources” pages. You can still reach our site at research.repository.duke.edu.
  • Links: While URLs have changed for datasets, all DOIs assigned to datasets will continue to work. We always encourage you to use DOIs (vs. URLs from your browser window) as those are the most stable and persistent!
  • Persistent Identifiers (PIDs): All datasets will continue to receive DOIs, but we will also provide more robust support for ORCIDs (for unique identification of people) and RORs (for unique identification of organizations/institutions) for better tracking of research outputs and to comply with upcoming PID funder requirements
  • Metadata: We will now integrate more DataCite metadata. Key metadata (descriptive information) will remain primarily the same; however, the form for describing your data will now have more built-in features for metadata standardization and compliance with best practices (see PIDs above).
  • Dataset structure: All datasets now have a single landing page (no-sub pages as with the current platform). This resulted in certain datasets being slightly remodeled (e.g., folders zipped) to accommodate the new dataset structure. However, no files have been changed and data integrity, reuse, and reproducibility were prioritized in this process.

What do depositors need to know?

  • File upload: For smaller datasets, you will now upload your files directly within the web form prior to hitting the “Submit” button (vs. via a Box link in the previous workflow). For larger datasets, upload will continue to be facilitated via Globus.
  • Organization: Datasets will either need to be flat (no folders) or folders (if important to retain for access/reproducibility) will need to be packaged (e.g., zipped/tarred/etc) prior to upload.
  • ORCIDs: To allow linking ORCIDs with datasets, we strongly encourage all dataset authors to have an ORCID prior to beginning a data submission. Go to the ORCID website to get your ORCID today!

What is new and improved?

  • Submission dashboard: A new submission dashboard will allow depositors to track all current and past deposits in one easy location.
  • Versioning: A new versioning module will allow depositors to more easily request the creation of a new version of their dataset. All previous versions will still be retained and the new version will receive a new DOI.
  • File Previews: Previewing common file formats (e.g., tabular files, images, PDFs, zips) will now be available on the dataset landing page.
  • Data Citations: You will now be able to copy data citations in a wide variety of citation styles.

What is staying the same?

  • Curation by RDR staff: Datasets will continue to be reviewed by RDR staff prior to publication to help researchers make their data as FAIR (Findable, Accessible, Interoperable, and Reusable) as possible.
  • Preservation and retention: Data will continue to comply with the DUL preservation policy including redundant copies, fixity checks, and over all information security as required by Duke. Our stated retention policy also will not change.
  • Globus download: For datasets over a certain size threshold, users will continue to have the option to download those files via Globus (in addition to the option to download over the web browser). If the “Download from Globus” button appears at the top of a dataset, we encourage using Globus as downloading large scale data over a web browser has some challenges (e.g., timeouts, etc.).
  • Embargoes: Depositors can continue to request embargoes for up to one year and we can continue to facilitate access to embargoed files for journal reviewers. Embargoed file names will now be viewable on the dataset page but cannot be downloaded until the embargo is lifted.
  • Collections: Project-specific collections will still be supported and can be requested by emailing datamanagement@duke.edu.

The RDR curation team is excited to bring you this new and improved system and look forward to continuing to support data sharing, curation, and reproducibility for Duke generated data.

Please don’t hesitate to reach out with any questions at datamanagement@duke.edu.

Local Data Repository Infrastructure Matters

Over the past seven years, the Duke University Libraries Research Data Curation Program and the Duke Research Data Repository (RDR) have developed into essential resources for the Duke research community. What began as a “proof of concept” turned into a robust, well-used data publishing service meeting both publisher and funder requirements and furthering Duke’s commitment to a “culture of open science and open scholarship to ensure transparency and accountability in research.”

The Duke Research Data Repository (RDR) has published over 310 datasets in a myriad of scientific disciplines including chemistry, biology, biomedical engineering, marine science, and medicine. Additionally, the RDR hosts datasets associated with articles published in PLOS, Nature, and PNAS and funded by NIH and NSF, their multiple sub-agencies and institutes, and others. The RDR provides a DOI for all datasets, and commits to long-term access and retention of data and curates all data based on the Data Curation Network (DCN) CURATED model.  As members of the renowned Data Curation Network (DCN), we leverage the expertise of a multi-institutional consortium that shares expertise to increase the quality of data curation across all DCN affiliated repositories.  The Duke Libraries are proud to be able to offer this local resource that supports the needs of Duke researchers who are not sufficiently served by disciplinary, data type or funder-based resources. In addition to providing the platform, we also provide front-line services for data management planning, data curation, disclosure risk review and referrals .

As the culture and landscape of data sharing evolves, researchers have many different repository options – from funder-sponsored repositories to discipline/community specific repositories to generalist repositories. Occasionally, journal publishers and funding agency Program Officers have questioned the suitability of institutional data repositories for long-term data sharing and preservation. To communicate the value of institutional resources focused on data sharing, we and other members of the DCN collaboratively wrote a letter to Science arguing that institutional data repositories provide valuable local infrastructure for researchers needing to meet data publishing guidelines.

In this letter, we detail how our repositories align with the FAIR guiding principles and commit to providing sustainable access to data critical for research reproducibility. This letter was published in the September 13 Issue of Science – Institutional Data Repositories are Vital (DOI: 10.1126/science.adr0789, open access copy available at: https://hdl.handle.net/11299/265639). The DCN has also published research that examined what researchers valued about their institutional data repositories and the services they provide. As one researcher noted

“I am thankful and excited for the help in curation…I see that teamwork in this final step of research means that the best possible version of the material will be available to future generations..”

All this to say, should you, as a researcher, need to demonstrate that an institutional data repository is an acceptable strategy for sharing data, we encourage you to cite the Science letter and reference the Duke Research Data Repository’s documentation clarifying how the RDR approaches compliance with the NIH Desirable Characteristics for Data Repositories . Comments or questions about the RDR can be sent to datamanagement@duke.edu.

Publications referenced:

Jen Darragh et al. (2024). Institutional data repositories are vital. Science 385,1174-1174(2024). DOI:10.1126/science.adr0789

Marsolek W, Wright SJ, Luong H, Braxton SM, Carlson J, Lafferty-Hess S (2023). Understanding the value of curation: A survey of researcher perspectives of data curation services from six US institutions. PLoS ONE 18 (11): e0293534. https://doi.org/10.1371/journal.pone.0293534

Code Repository vs Archival Repository. You need both.

Years ago I heard the following quote attributed to Seamus Ross from 2007:

Digital objects do not, in contrast to many of their analog counterparts, respond well to benign neglect. 

National Wildlife Property Repository
National Wildlife Property Repository. USFWS Mountain-Prairie. https://flic.kr/p/SYVPBB

Meaning, you cannot simply leave digital files to their bit-rot tendencies while expecting them to be usable in the future.  Digital repositories are part of a solution to this problem.  But to review, there are many types of repositories, both digital and analog:  repositories of bones, insects, plants, books, digital data, etc.  Even among the subset of digital repositories there are many types.  Some digital repositories keep your data safe for posterity and replication.  Some help you manage the distribution of analysis and code.  Knowing about these differences will affect not only the ease of your computational workflow, but also the legacy of your published works.  

Version-control repositories and their hubs

The most widely known social coding hubs include GitHub, Bitbucket and GitLab.  These hubs leverage Git version-control software to track the evolution of project repositories – typically a software or computational analysis project.  Importantly, Git and GitHub are not the same thing but they work well together.

Git repository
GIT Repository. Treviño. https://flic.kr/p/SSras

Version control works by monitoring any designated folder or project directory, making that directory a local repository or repo.  Among other benefits, using version control enables “time travel.” Interactions with earlier versions of a project are commonplace.  It’s simple to retrieve a deleted paragraph from a report written six months ago.  However there are many advanced features as well. For example, unlike common file-syncing tools, it’s easy to recreate an earlier state of an entire project directory and every file from a particular point in time.  This feature among others makes Git version-control a handy tool in support of many research workflows and the respective outputs:  documents, visualizations, dashboards, slides, analysis, code, software, etc.  

Binary. Michael Coghlan. https://flic.kr/p/aYEytM

Git is one of the most popular, open-source, version-control applications; originally developed in 2005 to facilitate the evolution of the world’s most far reaching and successful open-source coding project.  Linux is a world-wide collaborative project that spans multiple developers, project managers, natural languages, geographies, and time-zones.  While Git can handle large projects, it is extensible and can easily scale up or down to support a wide range of workflows.  Additionally, Git is not just for software and code files.  Essentially any file on a file system can be monitored with Git:   MSWord, PDF files, images, datasets, etc. 

 

There are many ways to share a Git repository and profile your work.  The term push refers to a convenient process of synchronizing a repo up to a remote social coding hub.  Additional features of a hub include issue tracking, collaboration, hosting documentation, and Kanban Method planning.  Conveniently, pushing a repo to GitHub means maintaining a seamless, two-location backup – a push will simultaneously and efficiently synchronize the timeline and file versions. Meanwhile, at a repo editor’s discretion, any collaborator or interested party can be granted access to their GitHub repository.

Many public instances of social-coding hubs operate on a freemium model.  At GitHub most users pay nothing.  It’s also possible to run a local instance of a coding hub.  For example, OIT offers a local instance of GitLab, delivering many of the same features while enabling permissions, authorization, and access Via Duke’s NetID.

While social coding hubs are great tools for distributing files and managing project life-cycles, in and of themselves they do not sufficiently ensure long-term reproducible access to research data.  To do that simply synchronize version-control repositories with archival research data repositories.

Research Data Repositories


Preserving the computational artifacts of formal academic works requires a repository focus that is complementary to version-control repositories and social-coding hubs.  Nonetheless, version control is not a requirement of a data repository where the goal is long-term preservation. Fortunately, many special-purpose data repositories exist.  Discipline-specific research repositories are sometimes associated with academic societies.  There also exist more generalized archival research repositories such as Zenodo.org.  Additionally, many research universities host institutional research data repositories.  Not surprisingly, such a research data repository exists at Duke where the Duke University Libraries promotes and cooperatively shepherds Duke’s Research Data Repository (RDR).  

Colossus computer
Colossus. Chris Monk. https://flic.kr/p/fJssqg

Unlike social coding hubs, data repositories operate under different funding models and are motivated by different horizons.  Coding hubs like GitHub do not promise long-term retention, instead they focus on immediate distribution of version-control repos and offer project management features. Research data repositories take a long view centered closer to the artifacts of formal research and publication.  

By archiving the data milestones of publication, a deposit in the RDR links a formal publication – book edition, chapter, or serial article, etc. – with the data and code (i.e., a compendium) used to produce a single tangible instance of publication.  In turn, the building blocks of computational thinking and research processes are preserved for posterity because the RDR maintains an assurance of long term sustainability.  

Creator of MacPaint
Bill Atkinson. creator of MacPaint. painted in MacPaint” Photo by Kyra Rehn. https://flic.kr/p/e9urBF

In the Duke RDR, particular effort is focussed on preserving unique versions of data associated with each formal publication.  In this way, authors can associate a digital object identifier, or DOI, with the precise code and data used to draft an accepted paper or research project.  Once deposited in the RDR, researchers across the globe can look at these archives to verify, to learn, to refute, to cite, or be inspired toward new avenues of investigation.

By preserving workflow artifacts endemic to publication milestones, research data repositories preserve the record of academic progress.  Importantly, the preservation of these digital outcomes or artifacts is strongly encouraged by funding agencies.  Increasingly, these archival access points are a requirement for funding, especially among publicly funded research.  As such, the Duke RDR exists with aims to preserve and make the academic record accessible, and to create a library of reproducible academic research.  

Conclusion

The imperatives for preserving research data are derived from expressly different motives than those driving version-control repositories.  Minimally, version-control repositories do not promise academic posterity.  However, among the drivers of scholarship is the intentional engagement with the preserved academic record.  In reality, while unlikely, your GitHub repository could vanish in the blink of the next Wall Street acquisition. Conversely research data repositories exist with different affordances.  These two types of repositories complement each other.  Once more, they can be synchronized to enable and preserve digital processes that comprise many forms of data-driven research.  Using both types of repositories imply workflows that positively contribute to a scholarly legacy. It is this promise of academic transmission that drives Duke’s RDR, and benefits scholars by enabling access to persistent copies of research.