[Amy Nurnberger]

Hey, RDA friends,
You may be interested in participating in the following study being conducted by Ceilyn Boyd on “the procedures data curators perform to recognize … anomalous datasets deposited in research data repositories and transform them into acceptable research datasets.”
[apologies for cross-posting]
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Do you curate or manage research data in a repository several hours per month? Do you have 60 – 90 minutes for a remote interview & other study-related activities?
Please sign-up to contribute to my dissertation research study that aims to understand how data curators define, recognize, and repair deposits made to their research data repositories.
Participants selected for the study will be compensated for their time.
See details below or express interest here: https://bit.ly/isthisdata
Study Details
 
Who is eligible?

You must be 18 years or older

You curate or manage research data in a data repository several hours per month, or more

You have 60 – 90 minutes for a remote interview and other study-related activities

Who is conducting the study?

Principal Investigator: Ceilyn Boyd, Ph.D. candidate in Library & Information Science at Simmons University, Boston, Massachusetts.

Faculty Advisor: Dr. Adam Kriesberg,  Library & Information Science at Simmons University, Boston, Massachusetts.

What is the study about?
I am interested in the procedures data curators perform to recognize what I call anomalous datasets deposited in research data repositories and transform them into acceptable research datasets. 
Acceptable research datasets meet minimum repository expectations for metadata, data, and documentation files. In contrast, anomalous datasets do not contain data files, have missing data files, or the presence or absence of research data is unclear to you. Procedures include inspecting a data deposit and making sense of its files, scanning READMEs and other accompanying documents, consulting with colleagues, and reviewing your repository’s best practices and policies.
My study will investigate anomalous datasets’ characteristics and how curators identify and interact with them.
How you may benefit by participating

Learning from colleagues. The study will reveal how curators’ data recognition and repair practices vary across repositories and are shaped by their knowledge and their repositories’ policies, technical requirements, and technical affordances.

Repository and curation improvements. Study results may inform improvements to repository and curation workflows to recognize, reduce, and repair poor-quality dataset deposits. Examples could include improved automated spam data detection strategies and depositor self-assessment tools to improve deposit quality while saving data curators time.

Training and best practices. Results may also point to improvements in onboarding and training materials featuring more detailed data recognition and repair procedures.

What will you do during the study? 
You will read a brief statement describing the research project and its goals, review the interview questions, and answer a few questions about the repository you work for and your curation experience. Then, I will interview you remotely using the Zoom video conferencing platform. Each interview will last 60 – 90 minutes. During the interview, I will ask you to describe times during your data curation work you have encountered 3 kinds of deposits. Deposits that were: 1) definitely not data, 2) were missing data, and 3) deposits you weren’t certain counted as research data. 
Compensation
All participants selected for the study will be compensated for their time.
Interested? Think you might be eligible? Learn more and express interest here: https://bit.ly/isthisdata   

 

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