Find sources of qualitative training & support at UNC. How to search for and evaluate qualitative research, integrate qualitative research into systematic reviews, report/publish qualitative research. Includes some Mixed Methods resources.
This article reviews "the benefits and concerns associated with qualitative data sharing" and then describes "the results of a content analysis of guidelines from international repositories that archive qualitative data."
Multi-disciplinary research data archive focusing on the study of lives over time, a national repository for social science data on human development and social change, especially data that illuminates women's lives and issues of concern to women.
In 2005, the Archive joined the Institute for Quantitative Social Science at Harvard's Faculty of Arts and Sciences in order to benefit from the Institute's research in digital libraries and preservation, and from its connections with the university library. Since then, the archive has used technology developed by the Institute to make its holdings available for search, download, and analysis on-line; offer easy on-line depositing to contributor; and integrate with networks of libraries and archives.
• An international consortium of more than 750 academic institutions and research organizations, ICPSR provides leadership and training in data access, curation, and methods of analysis for the social science research community.
• ICPSR maintains a data archive of more than 250,000 files of research in the social and behavioral sciences. It hosts 21 specialized collections of data in education, aging, criminal justice, substance abuse, terrorism, and other fields.
• ICPSR collaborates with a number of funders, including U.S. statistical agencies and foundations, to create thematic data collections and data stewardship and research projects.
Jones, K., Alexander, S.M. et al.,Feb 07, 2018
This is a list of major research data repositories that accept qualitative and/or social science data, with details about their qualitative data-specific policies and content.
List of repositories with qualitative and/or social science data, Last updated February 1, 2018
This list of data repositories was created through a group brainstorming process during and after
a workshop at the National Socio-Environmental Synthesis Center (SESYNC) at the University of Maryland.
The workshop was held February 28-March 1, 2017. This list was compiled from March 1, 2017 through February 1, 2018.
Full information about workshop participants and outcomes from the workshop can be found in the resulting white paper,
Qualitative data sharing and re-use for socio-environmental systems research: A synthesis of opportunities, challenges, resources and approaches.
The white paper can be found with the following DOI: DOI:10.13016/M2WH2DG59.
re3data is a global registry of research data repositories from a diverse range of academic disciplines. It provides information on repositories for the permanent storage and access of data sets to researchers, funding bodies, publishers and scholarly institutions. It includes qualitative and related repositories.
While NIH encourages the use of domain-specific repositories where possible, such repositories are not available for all datasets. When investigators cannot locate a repository for their discipline or the type of data they generate, a generalist repository can be a useful place to share data. Generalist repositories accept data regardless of data type, format, content, or disciplinary focus. NIH does not recommend a specific generalist repository and the list below, which is not exhaustive, is provided as a guide for locating generalist repositories.
When possible, check the style manual or guide for the citation style you are using. If it does not include information for citing data or datasets, use the information below to generate a citation.
Whether you produced the data yourself or you're using someone else's data in your research, it is important to maintain a linkage between your paper and the supporting datasets by citing them. This gives credit to the person who created the data and enables others to reproduce the research and verify results. For additional information, see ICPSR 101: Why Should I Cite Data.
There are many challenges in citing data. In many disciplines, there are no clear instructions on how to cite data, and many major style guides (APA, NLM, etc.) do not give specific guidance to address data/dataset citation. Additionally, data is often not recognized as a format in citation managers, so you may have to create the citation manually. Some datasets are dynamic, which can further complicate how and what to cite. However, some data repositories will suggest a citation. When there are no specific instructions for citing data, you may need to adapt instructions for a similar format, such as an electronic resource or web page.
Try to include these elements of the dataset in your citation:
Creator, author, or producer
Unique identifie. If a Digital Object Identifier (DOI) is available, include it. If not, include a link to online datasets.
Date of publication and version number, if there is one (datasets often change over time)
Date and time the dataset was accessed
Distributor (e.g., ICPSR, DRYAD)
If the dataset is a derivative of one or more other datasets, you may need to credit those sources in addition.
Some dataset distributors provide a checksum to ensure that the dataset hasn't been changed or corrupted since it was published, and this may be included in a source note. Other important information for understanding and using the dataset may be included in supplementary files (e.g., codebook, readme.txt) available at the same link as the citation or in the source notes of the paper.
Adapted from Citing Data, Michael Witt, Purdue University Libraries
Inter-university Consortium for Political and Social Research (ICPSR) at the University of Michigan is the world's largest archive of digital social science data,.They acquire, preserve, and distribute original social science research data.
From the Digital Curation Centre (DCC). "This guide will help you create links between your academic publications and the underlying datasets, so that anyone viewing the publication will be able to locate the dataset and vice versa."