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Research Data Repositories: Home

Locating research data repositories and features of popular research data repositories

What is a Research Data Repository?

A research data repository is a virtual place to store and preserve research data. Depositing research data in a repository increases data transparency and exposure and promotes research collaboration opportunities. There are multidisciplinary, subject-based, and special purpose repositories available to researchers worldwide. For example, iDEA houses digital resources produced by the Drexel University community.

Repository Selection Criteria

Although Drexel University Libraries does not currently recommend specific repositories, we advise reviewing the following considerations before selecting a repository for your research data. 

  1. Does the Repository support FAIR principles?

FAIR means that data publishing platforms should enable data to be Findable, Accessible, Interoperable, and Re-usable. Many organizations, including the NIH, place considerable emphasis on data sharing that meets these principles.

  • Data is Findable if it is uniquely and persistently identifiable. Does the repository register your data to create a persistent identifier (such as a DOI)? Does the repository provide for rich metadata that will enable discovery? Is your research output and data indexed in Google or subject databases?
  • Data is Accessible if it can be understood and obtained by machines or humans, through a standard protocol that allows for authorization and authentication, where necessary.
  • Data Objects are Interoperable if metadata and data are machine-accessible and utilize shared terminology.
  • Data Objects are Re-Usable if the data can be automatically linked or integrated with other data sources, with proper citation of the source. Are data use agreements and/or licensing clearly presented, to allow depositors to state explicitly up front what uses they would be willing to allow?
  1. What is the cost structure?
    Are there ongoing costs after deposit? Have you accounted for these costs in your grant budget?
  1. Does the repository meet a set of certification standards?
    Check to see if a repository follows certification standards such as the Core Trust Seal of Approval or the Trustworthy Repositories audit & Certification: Criteria and Checklist (TRAC). Although certification criteria are informative, repository certification is still in its infancy.Most repositories have not achieved certification.

*University of Iowa Libraries. Research Data Services Data Repositories. Retrieved August 27, 2019 http://www.lib.uiowa.edu/data/share/data-repositories/

Finding Repositories

As the number of research data repositories increases, so do registries and directories of repositories. The following registries are useful for locating a repository for your research data:

  • re3data.org: global registry that includes data repositories from various academic disciplines
  • DataONE: DataONE is a community driven project providing access to data across multiple member repositories, supporting enhanced search and discovery of Earth and environmental data.
  • NIH: These repositories include NIH-supported data accessible for reuse. Most accept submissions of appropriate data from NIH-funded investigators (and others), but some restrict data submission to only those researchers involved in a specific research network.
  • PLOS Recommended Repositories: PLOS has identified a set of established repositories that are trusted and recognized within their respective communities
  • Scientific Data Recommended Data Repositories: repositories recommended by Scientific Data. Repositories on this list have been evaluated by Scientific Data, to ensure that they meet their requirements for data access, preservation, and stability.

Popular Research Data Repositories

Listed below are some popular research data repositories and details regarding each one. 

Dryad

Dryad https://www.datadryad.org/​

  • Subject/Discipline: multidisciplinary, initially biosciences
  • Data Types/Data Status: Unstandardized file types found in most research. Final, from accepted peer-reviewed journal articles, or dissertations & books.
  • File Format/File Size:  any that follow accepted community standards and follow preservation-friendly file formats.
  • Deposit Size Limitations: excess storage fees for data packages totaling over 20GB
  • Accepted Metadata Schemas: any, so long as relevant details about data collection, processing, and analysis are included in a README document.
  • Persistent Identifiers provided: DOI
  • Levels of Access to Deposited Data: Unpublished, Published
  • Fees: yes, base charge per data package is $120
  • Data Curation Services (yes/no): yes
  • Where Indexed: DCIOAD, OpenDOAR, re3data
  • Supports OAI (yes/no): yes
  • API available (yes/no): yes

Figshare

 Figshare https://knowledge.figshare.com/   https://figshare.com/features https://knowledge.figshare.com/articles/item/how-can-figshare-help-my-research

Harvard Dataverse

Harvard Dataverse https://dataverse.harvard.edu/​

  • Subject/Discipline: multidisciplinary
  • Data Types/Data Status: quantitative, qualitative/any
  • File Format/File Size: any/varies
  • Deposit Size Limitations: varies
  • Accepted Metadata Schemas: various
  • Persistent Identifiers provided: DOI/Handle
  • Levels of Access to Deposited Data: Closed, Unpublished, Published (restricted, not restricted)
  • Fees: none
  • Data Curation Services (yes/no): no
  • Where IndexedOAD, OpenDOAR, re3data
  • Supports OAI (yes/no): yes
  • API available (yes/no): yes

ICPSR Inter-university Consortium for Political and Social Science Research

ICPSR  https://www.icpsr.umich.edu/icpsrweb/​    ACCESS NOTE: User must create free MyData Login while on-campus or using VPN in order to download data. After the Login is created you will be able to download from anywhere.

  • Subject/Discipline: social and behavioral sciences, with specialized collections in education, aging, criminal justice, substance abuse, terrorism, and other fields.
  • Data Types/Data Status:  accepts quantitative, qualitative and GIS data; final project status
  • File Format/File Size:  SAS, SPSS, or Stata files preferred. ASCII and other file formats also accepted. 
  • Deposit Size Limitations:  no reported limit for curated ICPSR deposit; 2GB free self-deposit in OpenICSPSR 
  • Accepted Metadata Schemas:  Recommended: DDI metadata schema
  • Persistent Identifiers provided:  DOI
  • Levels of Access to Deposited Data:  Open; Secure Online Analysis (public or password-protected); Restricted Use Data Agreement; Virtual Data Enclave; Physical Data Enclave
  • Fees:  no fee for self-deposit of data up to 2GB in OpenICPSR; fee for fully-curated deposit. Drexel institutional membership discounts curation fees.
  • Data Curation Services (yes/no):  none for OpenICPSR; full OIAS-based curation services for curated deposit.
  • Where Indexed:  DCIOADre3data
  • Supports OAI (yes/no):  yes
  • API available (yes/no):  yes

QDR

QDR https://qdr.syr.edu/​

  • Subject/Discipline: social sciences, related traditions that use cognate methods
  • Data Types/Data Status: qualitative, multi-method/various
  • File Format/File Size: alphanumeric, audio, video, photographic/less than 2 MB
  • Deposit Size Limitations: not listed
  • Accepted Metadata Schemas: DDI
  • Persistent Identifiers provided: DOI
  • Levels of Access to Deposited Data: Standard, Conditional Online, Depositor Approved, Restricted Offline, Embargoed
  • Fees: no fees to access or deposit data, but institutional membership available
  • Data Curation Services (yes/no): yes (and more comprehensive curation services for QDR institutional members)
  • Where Indexedre3data
  • Supports OAI (yes/no): no
  • API available (yes/no): yes

Zenodo

Zenodo  https://zenodo.org/

  • Subject/Discipline:  multidisciplinary
  • Data Types/Data Status:  qualitative, quantitative and mixed method
  • File Format/File Size: text, spreadsheets, audio, video, images, source code.
  • Deposit Size Limitations: 50 GB per data set, unlimited number of data sets.
  • Accepted Metadata Schem. as: Marc, Dublin Core, Data Cite
  • Persistent Identifiers provided:  DOI
  • Levels of Access to Deposited Data:  Opened, embargoed, restricted and closed
  • Fees: none
  • Data Curation Services (yes/no): no
  • Where Indexed:  DCIOADOpenDOAR, re3data
  • Supports OAI (yes/no):  yes
  • API available (yes/no):  yes

Citing Data from Research Data Repositories

Data should be cited within a publication just as other literature are cited. Use the appropriate format based on the citation style you're using (eg. APA, Chicago, Turabian, etc.). The minimum amount of information that should be included in a dataset citation is the following:

  1. Author(s)
  2. Title
  3. Date published
  4. Universal, persistent identifier (PID)
  5. Some way to resolve the PID (DOIs and ARKs both have resolution services)
  6. Date accessed

Source: 

https://libguides.utk.edu/dataservices/citation

 

Many data repositories have specific guidelines on how the data they host should be attributed. These citation guidelines are often included in the dataset’s metadata or linked from the repository’s web site.  

Example of citing data from the Dryad repository:

How do I cite data from Dryad?

When citing data found in Dryad, please cite both the original article, as well as the Dryad data package. You can see both of these citations on the Dryad page for each data package.

Westbrook JW, Kitajima K, Burleigh JG, Kress WJ, Erickson DL, Wright SJ (2011) Data from: What makes a leaf tough? Patterns of correlated evolution between leaf toughness traits and demographic rates among 197 shade-tolerant woody species in a neotropical forest. Dryad Digital Repository. https://doi.org/10.5061/dryad.8525

Source: https://datadryad.org//pages/faq#using

 

Related Websites:

How to Cite Datasets and Link to Publications (Digital Curation Centre)

Why and How Should I Cite Data? (ICPSR)

 

Related Library Guides:

For Further Assistance

Please contact  datamanagement@drexel.edu to request assistance with finding a research data repository or uploading research data to a repository.