Special Issue CFP: Aligning Qualitative Data Services with Open Science and Access

2024-10-16

Collections of qualitative data allow for countless angles, foci, and analytical techniques, enabling new insights and theories about the social, natural, and physical worlds. Qualitative data and their collections are valuable treasures for re-use, re-analysis, and training. However, there is a tension with qualitative data sharing, where researchers need an understanding of which data, with whom, and how to share data complying with institutional and funding agency policies as well as FAIR and CARE principles.

Open science and access trends are pushing qualitative research to adopt FAIR, CARE, and TRUST principles. In response to data sharing expectations, qualitative researchers have expressed concerns about the ethical challenges, methodological concerns, and labor involved in making their data and materials publicly available. While data archives and libraries are extending their services to support qualitative research, information professionals need a better understanding of key issues, best practices, guiding concepts, and tools in managing, sharing, and curating trustworthy qualitative data.

In 2019, members of the IASSIST Qualitative Social Science & Humanities Data Interest Group (QSSHDIG) edited an IASSIST Quarterly special issue (Vol. 43, No 2) focused on extending data services to qualitative research by exploring training, service visibility, transparency, and reuse practices. A second special issue of IASSIST Quarterly is warranted to explore qualitative data through the lens of FAIR, CARE, open science, and access. (We consider qualitative data to include textual, audiovisual, and other non-numeric formats.)  Given the recent global and disciplinary trends in open science and data, it is timely to revisit the qualitative data landscape to advance concepts, theory, and practices that support transparent, trustworthy, and accessible qualitative research now and into the future. 

We invite prospective authors to submit first a proposal for what they would like to contribute.  Topics of this issue may include but are not limited to:

  • Data curation, management, and preservation
  • Data use and reuse, the value of data
  • FAIR data principles
  • Indigenous data and CARE principles
  • TRUST digital preservation principles
  • Metadata, data models, and documentation
  • Data preparation and analysis (e.g., transcription, annotations)
  • Collaboration and teamwork in qualitative research
  • Collections, aggregations of qualitative data
  • Sharing qualitative data to support trustworthiness and research integrity
  • AI, text mining, and novel approaches to analysis/re-use
  • Ethical, legal, and privacy concerns (e.g., informed consent, copyright, license)
  • Data activism
  • Citation, attribution, identifiers
  • Data service models
  • Disciplinary and/or international perspectives on qualitative data support
  • Education and workforce issues
  • Tools and technologies supporting qualitative data
  • Theories and concepts that guide qualitative data support

Long live qualitative data!

Guidelines:

Abstract submissions (one page max) are due January 31, 2025 and should be sent to iqspecialissue26@gmail.com.  

Full manuscript submissions should be received by April 30, 2025. Manuscript submissions should use the IASSIST Quarterly author template and must be uploaded using the link at the top of the Submissions page. Please make a note that you are submitting for the special issue. If you have any questions, please do not hesitate to contact the guest editors.

Guest Editors:

  • Hilary Bussell, Head of Humanities and Social Sciences Librarians, The Ohio State University, bussell.21@osu.edu
  • Cheryl A. Thompson, PhD, Research Data Preservation Archivist, Research Data Management Core, University of North Carolina Chapel Hill, cathompson@unc.edu
  • Maureen Haaker, Senior Qualitative Research Data Officer, UK Data Service, mahaak@essex.ac.uk
  • Michael Beckstrand, PhD, Qualitative & Mixed Methods Research Associate, College of Liberal Arts, University of Minnesota, mjbeckst@umn.edu