Data Repositories

What is a data repository?

A research data repository is an online storage and management system for research data, designed to preserve, share, and make data discoverable and reusable. 

Why choose a data repository?

There are many reasons, here are a few,

1. Compliance with Data Sharing Policies: Many funding agencies, journals, and organizations require researchers to share their data through a data repository. This requirement helps ensure data transparency and reproducibility in research.
2. Long-term Sustainability: Using a personal or lab website or even uploading the dataset in journal article supplementary files is not advisable. In addition, simply adding “available upon request” to the data availability statement in a publication is not sufficient. Studies have demonstrated that when data is actually requested, many authors have failed to comply. 
3. Data Discovery and Accessibility: Repositories make data more visible and accessible to researchers and other users.

Data Repository Types

Institutional repository:
An institutional repository (IR) is an online archive subscribed and used by universities to collect, preserve, and disseminate digital versions of their scholarly and creative output both within and outside the institution. CMU does not have a subscription to an institutional repository. However, CMU Library Data Services can help researchers to locate suitable repositories to store and share their data based on their specific needs.

General-Purpose Repositories:
Cater to a broad range of research disciplines and are often open to the public (e.g.) Registry of Research Data Repositories (re3data), FAIRsharing that are open repositories recommended by funding agencies and publishers. Many institutional repositories partner with open repositories (e.g) DRYAD

Domain-Specific (disciplinary) Repositories:
Focused on specific research areas or data types (e.g., social sciences, genomics). Most of disciplinary repositories are included in General-Purpose repositories, while some repositories are from government agencies or organizations (e.g.) FITBIR, or open repositories recommended by government agencies (e.g.) NIH Controlled-Access or supported Data Repository.  

Government agencies, grant funders, institutions, and publishers worldwide are increasingly introducing open data policies and mandates to encourage researchers to share their research data openly with specific recommendations for data repositories. 

1. Check the requirements, guidelines, and recommendations with government agencies, grant funders, home institutions, or journal publishers of your research. 

2. Use the following entries of this guide to find a related data repository, though the listings are not exhaustive.   

• Repositories recommended by government agencies
• Repositories recommended by journal publishers
• Open repositories
• Domain-Specific Repositories
• Library database repositories
• Qualitative data repositories  

3. Contact Library Data Services to help you locate a suitable repository for your research.

Research data services have garnered sustained attention from library research support service providers for nearly two decades.^[1] Libraries have played a leading role in developing research data services, and on most university campuses they provide the largest and most diverse services.^[2] Ithaka 2024 report reveals that libraries are still significant providers of research data services across institution types. R1 institutions offer approximately three times the number of services offered by R2s. 

CMU is designated as an R2 Carnegie research university. Data related research activities have been increased across CMU campus with funding agencies and journal publishers' data policies and mandates. CMU Library has provided data services to assist CMU researchers with data collection, data repositories, data management across the entire research data lifecycle from the earliest planning phase, through archiving and dissemination. The data services are aligned with ACRL's guidelines.   

Specifically, we can assist with researchers' needs such as:

• Acquire data collection needed for researchers within the library budget
• Find and access various types of data (quantitative and qualitative data, texts, images, videos, maps, etc.) need related to your research;
• Help you to find publications relevant to your research data and methodology;
• Provide information and assistance for creating your data management plans (DMP);
• Provide information and assistance for file format selection, metadata, and documentation;
• Identify repositories suitable for depositing, preserving, and sharing various types of research data;
• Assist researchers to track data citation impact;
• Provide tailored consultations to assist individual researchers;
• Provide library instruction for classes related in using data collection and data management;
• Develop library research guides, workshops, and tutorials needed for CMU research community.

Contact the librarians for assistance:

• Rui Wang, Behavioral Social Science Librarian / ICPSR Official Representative wang1r@cmich.edu | Schedule an appointment 
• Rebecca Renirie, Life Science / Medical Librarian hill2ra@cmich.edu
• Other Subject Librarians

open access network

A distinction is made between institutional and disciplinary repositories. Institutional repositories are document servers operated by institutions (mainly university libraries, other infrastructural institutions, or research organisations) that enable their members to digitally publish scholarly documents. Disciplinary depositories, by contrast, are trans-institutional. They are available to scientists and scholars to publish and archive their works on specific subjects, for example, in a specialist discipline. Examples are media/rep/, an open access repository for publications in the field of media studies; Social Science Open Access Repository (SSOAR) for the social sciences; PubMed Central for the biomedical and life sciences; and arXiv for scholarly articles, especially from the fields of physics, mathematics, and computer science.