Fellows Webinar: Utilizing Data Citation for Aggregating, Contextualizing, and Engaging with Research Data in STEM Education Research

Our fellow team from Purdue University will present about how they characterized citation data from the literature in the field of STEM education research.

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Event Details

When: December 9 at 3 p.m. ET
Where: Online
Livestream link: Register for this meeting here. After registering, you will receive a confirmation email containing information about joining the meeting.

About the research: Researchers will characterize citation of data from the literature in the field of STEM education research. A sample of relevant publication venues in the field will be identified from WoS and MAG.

Digital Object Identifiers (DOIs) of datasets registered with DataCite will be used to query and associate datasets with publications. The team will assess rates of citation for datasets that are cited using DataCite DOIs for each publication venue and analyze a sample of data citations and publications to determine suitability for providing an initial context to help a researcher who is unfamiliar with the data determine whether to use the dataset.

Abstract: Research in the field of Science, Technology, Engineering, and Mathematics (STEM) education is distributed across disparate communities of researchers with minimal sharing of data among and across them. The practice of citing data that are used or reused in STEM education research is an emerging, but not yet widely adopted, practice. In this project, we seek to characterize citation of data from the literature in the field of STEM education research and to begin to evaluate the context that cited literature can provide for better understanding the cited data. A sample of relevant publication venues in the field will be identified from the Web of Science and Microsoft Academic Search. 5,959,459 Digital Object Identifiers (DOIs) of datasets registered with DataCite will be used to query and associate datasets with publications from the WoS and MAG sample. Quantitative and qualitative methods will be used to characterize rates ! of citation for datasets that are cited using DataCite DOIs for each publication venue; lastly, a small, pilot sample of data citations and publications will be analyzed to determine suitability of the publication for providing an initial context to help a researcher who is unfamiliar with the data to understand and factor into a decision to potentially use the dataset or not.

Read more about the researchers here.