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Scholarly Communication: Data Sets and Repositories

Data Sets

All research involves data and the amount of data produced annually is tremendous. With the growth of open access and research transparency, data that was formerly unavailable is now much more open and located around the globe. Whether being shared because of grant funding requirements (eg. NIH) or open access mandates in some organizations and countries, many datasets are stored and made digitally accessible to anyone needing the data. Finding datasets is possible through a numbers of search engines. Such as:

Datacite -  provides persistent identifiers (DOIs) for research data and other research output

Google Dataset Search - search engine for datasets

ICPSR - Institute for Social Research at the University of Michigan - Datasets in the social sciences

OAD Data Repositories - Repositories and databases for open data

OSF Share - a free, open dataset of research (meta)data.

Data Repositories

In addition to using a data search engine, you may want to tap data repositories. Academic and research institutions require the storage of data, although they will vary when it comes to accessibility.  Some places to check out are...

Harvard Dataverse - allows for depositing and sharing data

Nature Data Repository Guidance - Links to a variety of dataset repository - a registry of research data repositories

Science Data Bank - makes "data citable, discoverable and persistently accessible"

Organize & Document

Organize Your Research Data

Great organization is your best asset for data management.

  • Create a system
  • Work with collaborators
  • Use file version control
Use a System

The most important step to organize your research data is having a system and using it consistently. You may choose to organize your data by the following, or use them in combination:

  • By project
  • By data
  • By analysis type
  • By research
  • By site or data source
Document, Document, Document

Document throughout your research process. 

  • Document any data processing analyses
  • Take notes!
  • Include both written, electronic, and recorded notes
  • Create documentation within your organization at project and folder levels
    • Create a README.txt file
  • Use descriptive names within your documentation

"Data Management - Organize & Document" by FGCU is licensed under CC BY 4.0

Storage & Backup

Storage & Backup

Storage ≠ Backup

  • Storage and backup are separate elements of data management that complement each other. 
  • Storage is for your working files that you access regularly. If you lose storage, you'll lose the current versions of your data.
  • Backup is the regular process of copyright data. You don't need a backup until you lose your data, but it can save your research.
  • A good combination of storage and backup supports strong data management.

"Data Management - Storage & Backup" by FGCU is licensed under CC BY 4.0