Qualitative data sharing

The Center for Qualitative and Mixed Methods Inquiry at Syracuse University (only a few hours away from McGill!) hosts a well known Summer Institute for Qualitative and Multi-Method Research. I recently found out that the center also houses a qualitative data repository (QDR). The topic of whether or not to share qualitative data has come up in brownbag discussions in the past. Undoubtedly there are drawbacks to sharing qualitative data. But the website of the QDR outlines some interesting rationales for qualitative data sharing. It states:

QDR provides leadership and training in—and works to develop and publicize common standards and practices for—managing, archiving, sharing, reusing, and citing qualitative data. QDR hopes to expand and improve the use of qualitative data in the evaluation of research, in scholarly production, and in teaching.

Qualitative data are used by social scientists to advance a range of analytical, interpretive, and inferential goals. Yet in the United States, traditionally such data have been used only once: social scientists collect them for a particular research purpose, and then discard them. The lack of a data-sharing custom is due in part to an infrastructure gap – the absence of a suitable venue for storing and sharing qualitative data.

QDR hopes to help to fill this gap. First, the repository expands and eases access to qualitative social science data. This access empowers research that otherwise would not be conducted, and promotes teaching and learning about generating, sharing, analyzing, and reusing qualitative data. Further, the repository contributes to making the process and products of qualitative research more transparent. This increased openness facilitates the replication, reproduction, and assessment of empirically based qualitative analysis. Finally, by increasing researcher visibility, the repository induces intellectual exchange, promoting the formation of epistemic communities and serving as a platform for research networks and partnerships.

It will be interesting to see if the data sharing in qualitative research will become seen as a best practice as it increasingly is in quantitative research.

Teaching Good Research Practice

I attended a webinar on how to teach students to document empirical research by Richard Ball and Norm Medeiros from Havorford College and hosted by the Interuniversity Consortium for Political and Social Research (ICPSR). This idea aims to counter current norms, policies and practices in teaching empirical research by having students submit all their statistical analyses with their final project. This should include all the necessary documentation to allow a third-party to replicate all statistical results, what Ball and Medeiros call “a soup-to-nuts approach”. This approach in turn enhances professional norms and practices through a trickle-up effect, students actually understand what they are doing, and students know they are being held accountable. The webinar used an example from an economics course, but it is easy to imagine the potential for social work education and research.

The slides are available on their YouTube channel. It’s worth checking out and rethinking how we can use this in our classrooms and research.

Guidelines for more open scholarship in social work research

Ross Mounce (@rmounce) distills advice for disseminating papers preprint and postprint.
HERE

Step 1: before submitting to a journal or peer-review service upload your manuscript to a public preprint server

Step 2: after your research is accepted for publication, deposit all the outputs – full-text, data & code in subject or institutional repositories

Before Step 1, you should know your rights as an author. See the Scholarly Publishing and Academic Resources Coalition (SPARC) guidelines HERE.
Examples of preprint servers in social sciences include SSRN and Zenodo (need to know more about Zenodo).
escholarship@McGill is our institutional repository. I’ve uploaded a few papers there but overall have been unsatisfied with the turnaround time. And, I am not clear on how to upload data there and associate it with a paper.
Ultimately, I’ve turned to creating a website on the McGill web management system where I can post papers and data. HERE In due time, we will upload our dissertation database there with link to Dataverse.
The downside of this strategy is that the papers are not indexed by google scholar and other search engines. We are hoping to meet with the escholarship@McGill staff this summer and will plan to invite them to an upcomign brownbag seminar.

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