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Research Data Management - Best Practices

Introduction to Research Data Management

How Do I Share?

Navigating this page

This page addresses common approaches for sharing research data. It is organized into two sections:

  1. Publishing with a Data Repository, the gold standard approach to data sharing
  2. Other Sharing Methods you may have heard about

Each box below begins with "quick facts" about the section, followed by multiple tabs to explore the topic.

Publishing with a Data Repository

Quick Facts about Data Repositories

  • Repositories are databases intended for long-term preservation and are the gold standard approach to data sharing 
  • Funders and publishers often require this method for data sharing
  • Use of a repository may be restricted to specific disciplines, research methodologies, or grantees
  • Repositories require careful evaluation to ensure they are high quality

I. Types of Data Repositories

A repository is a database intended for long-term preservation. 

Typically, researchers are not equipped to take on the long-term care that data needs in order to remain intact and re-useable. Instead, professional repositories have the mission and technical capabilities to properly store and manage the data. This includes aspects such as fixity checks, format migration, and providing a persistent link. 

Repositories are generally either categorized as general-use, meaning they accept data from any discipline, or disciplinary repositories, which focus on a particular research field. 

Expand the panels below for more information about each type of repository:

When determining  where to deposit your data it is important to consider where your colleagues are most likely to find and make use of your data. Disciplinary repositories have some sort of theme or common element to the data that they will accept; however, what that guiding principle is can be different across disciplinary repositories.  These different themes can include:

  • A particular subject or area of research, such as genomics or astronomy
  • A particular type of data or methodology, such as imaging, flow cytometry, or qualitative data

Generalists repositories, on the other hand, will accept any type of data and from any discipline or subject area, including inter-disciplinary data.  They do not have any particular collection themes, and so they can contain a very broad and diverse collection of data.  To help improve the findability of your data, it is recommended that researchers use a disciplinary repository option when there is one available. Some universities also have institutional repositories, which are typically general-use repositories designated for only by researchers affiliated with that institution.

II. Finding a Repository

This section provides additional details about types of data repositories and how to find and evaluate a repository that meets your needs.

Funder Requirements

The first thing to do when selecting a repository is to check if your funding agency has any requirements about where you should be sharing your data.  If they specify a repository that they want you to use, then that is the repository you should select.

Sometimes a funder may not require a certain repository, but they have one they recommend or that they otherwise sponsor.  Again, if your funding agency points you to any particular repository, that is a good option to use.

Most funder required repositories would also be considered to be a type of disciplinary repository.

Disciplinary Options

If there is not a repository that is either required or suggested by your funder, the next step would be to look for any discipline-specific repository options.  Some disciplines or research areas may have a certain repository that it is customary to use.  Even if your discipline doesn't have a repository they typically use, you may also be able to find a repository that specializes in the type of data you will be creating, such as images, fluroscopy, etc.

There are several tools available for searching disciplinary data repositories:

Ohio State Support

Ohio State is an institutional member the disciplinary repository Qualitative Data Repository. Affiliated researchers with qualitative data can deposit data for free to this repository, including complimentary curation.

Check out the Ohio State Resources page for more information.

Generalist Repositories

If there is not a repository that is either required or suggested by your funder, and there is not a good disciplinary option available (e.g. your research is interdisciplinary, there is not a disciplinary option that matches what you are doing), then the next option would be to use a generalist repository.

As their name implies, generalist repositories accept data from across disciplines and do not have a subject-specific focus.

Ohio State Support

Ohio State is an institutional member of the generalist data repository Dryad. Affiliated researchers can deposit data for free to this repository, including complimentary curation.

Check out the Ohio State Resources page for more information.

None of the Above

If none of the above options match your research data, or you are otherwise unsure of what the best option might be, then your next step should be to schedule a consultation to discuss your specific project and identify possible solutions.  This may be the case when your data is too big or too sensitive to deposit in a generalist repository, but there is not a good funder-based or disciplinary option available.

Ohio State Support

Ohio State provides one-on-one consultation to help researchers with the process of selecting a suitable data repository.

Send an email to datamanagement@osu.edu to schedule a consultation or check out the Ohio State Resources page for more information.

III. Evaluating a Repository

Expand the panels below for criteria to consider when evaluating a repository.

Project-specific criteria:

Does this repository charge a fee? How much does it cost?

  • Many repositories charge a one-time fee at the time of deposit
  • Costs can be a flat fee or project-based, typically assessed by the size and complexity of a dataset (e.g. file size, number of variables)
  • Services included vary and may consist of long-term storage, curation or other deposit support, and specialized support for data with human research participants (e.g. de-identification, mediated access, risk disclosure review)
  • Deposit fees are often an allowable cost for grant-funded research

Ohio State Support

Ohio State is an institutional member of two data repositories: Dryad and the Qualitative Data Repository. Affiliated researchers can deposit data for free to these repositories, including complementary curation.

Check out the Ohio State Resources page for more information.

Does the repository have any relevant limits, such as individual file limits or overall project limits?

  • Some repositories may have a limit on how big an individual file can be, or how large an overall project can be. Before settling on a repository, you will want to think about how much data you expect to generate and if these limits might cause any issues for you down the road. If size limits are an issue, there are some ways to work around it:
    • If you have multiple types of data, you might consider using two different repositories. This can help split things up into smaller chunks that will not exceed the file limits.
    • You can also consider whether a single large project could be split up into several smaller projects, but all still be deposited into the same repository.
    • Lastly, some repositories will work with you if you have larger files. Try reaching out to them directly to ask if there is a possibility to still deposit your larger data files.
  • As mentioned previously, some repositories will have limits on the type of data they will accept, so you want to make sure that your data is a good match for the content scope of the repository.

Does the repository mediate access to ensure authorized use? Or will my data be open for anyone to view?

  • Some repositories make all of their data openly available and viewable to anyone in the world, while others may have the ability to control or limit access to the data.
  • If you have data that you need to control (e.g. sensitive human subjects data, data with intellectual property (IP) considerations, etc.), this can be a very important repository characteristic.
  • Dryad Data Repository makes all of their data openly available, so if you need to have access controls this is not a good repository option for you.

What terms will potential users of the data have to agree to?

  • Some repositories may give depositors a choice on how they would like to share their data and what terms or conditions might apply to future use, while others may require you to use only one particular license type.
  • For example, any data deposited to the Dryad Data Repository must have a Creative Commons 0 license (CC0) applied, which means that your data will become part of the public domain, while data deposited in the QDR will have a custom license applied.
  • Even if your data is licensed for open use, you and your dataset should still receive citation if someone reuses it, so you will still get credit for your work.
 

General Best Practices:

Is the data browsable? In other words, will other people be able to find a record of the data in some type of catalog or online listing?

  • The first principle of FAIR data is that it be findable. If your data is in a repository, but there is no easy way for other researchers to know it exists, then your data is not really findable.
  • Being findable is not the same as being open. This is similar to viewing the Table of Contents of a journal to find that an article exists, but then going through some sort of process to get access to the full text.

Does the repository assign some type of persistent and unique identifier to the data?

  • Much like articles, datasets can receive a DOI to help identify and differentiate it from other items. Looking to see if a repository will issue a DOI, or a similar type of persistent identifier, is a good way to check that your data will be easily findable.
  • In addition, by having a DOI assigned to your dataset, other researchers will be able to easily cite your data and provide you with due credit.

Will the repository provide any support when preparing my data for deposit, or the actual uploading process?

  • Depositing your data can be a tricky and complex process, and some repositories will offer help and support.
  • We recommend that you use repositories that provide some type of curatorial support whenever possible. This will help ensure that your data is properly prepared and deposited in the repository.
  • Generally speaking, if a repository is free, it is unlikely that you will receive much assistance with depositing your data.
  • Both Dryad and QDR will provide curatorial support to Ohio State researchers in virtue of our memberships.

Does the repository appear to have some policies in place?

  • It is not always necessary for you to read through all of their policies, but it is a good indicator for a repository if they have some policies in place.
  • Examples of policies you might look for include:
    • Collection Development Policy: outlines the types of data they collect
    • Retention and/or Preservation Policy: defines how long they will retain your data and (what will happen to your data if the repository ceases to exist in the future) if they have plans in place should the repository cease to exist in the future
    • Security Policy: outlines what types of security they have in place to ensure that your data is secure.

Other Resources for Evaluating Data Repositories:

Other Sharing Methods

Quick Facts about Other Sharing Methods

  • Not all sharing methods meet funder or publisher requirements. Data sharing policies often require the use of repositories, discussed in the previous section.
  • Figures and tables published in journals usually don't qualify as "data" because they have already been analyzed. Sharing policies typically require the underlying data needed to replicate the findings conveyed in articles.
  • Websites can be a valuable supplement to publishing in a repository by enabling interactive displays or dashboards. 
  • Sharing data by request may be appropriate while research is still ongoing but is generally discouraged as a long-term solution.

I. Publish Supplementary Files in a Journal

Figures and tables published with a journal article are analyzed, edited, and formatted to illustrate researchers’ conclusions. In contrast, the research data required to meet data sharing requirements is usually the data used to produce these figures and tables. This is the data that another researcher would need to verify and replicate the findings of the research findings  that are conveyed through figures and tables.

In general, publishing data within a journal article or as a supplementary file will usually not meet funder requirements for data sharing. However, it may still be required by the publisher. With both funder and journal data publishing requirements evolving rapidly, it is important to crosscheck journal, funder, and repository requirements to ensure all policies are followed.

II. Post Data to a Personal/Lab/Project Website

Researchers who maintain a website on their research may want to post data or data visualizations to these pages so that all of the information for a study can be found in one place. This approach on its own generally does meet funder requirements for data sharing because of the following challenges:

  • Lack of Discoverability: Websites are typically not included in specialized data search tools like indexes and catalogs
  • Lack of Long-Term Availability: Websites maintained by research teams do not typically have the resources or expertise to ensure data is preserved over time
  • Link Rot: Website URLs often change over time, leading to broken links in places where the data is cited

However, personal websites do offer greater flexibility in hosting dynamic content like dashboards, maps, and other interactive visualizations. When you publish your data with a repository, you retain your rights to also display it through other places like a website. Just be sure to cite the version in the repository so others know where to find it!

III. Share Data by Request

For many years it was common to meet data sharing requirements by including a statement that the data will be available to other researchers upon request. However, numerous studies have found that data shared in this manner is rarely accessible. Commons challenges include:

  • Lack of Response to data requests
  • Unusable data that was not properly documented at the conclusion of a study
  • Missing data that was not maintained over time

It may still be appropriate to share data by request during an active study, but long-term data publication now requires the use of established data repositories. Data repositories are equipped to address these challenges by ensuring data is preserved and openly discoverable online. Some repositories can also process data requests that are necessary to ensure the security of sensitive data.