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EXPLORE: the need for an open classification system

April 7, 2022 @ 5:00 pm 6:00 pm UTC+2

Make Data Count (MDC) is a scholarly change initiative, made up of researchers and open infrastructure experts, building and advocating for evidence-based open data metrics. Throughout MDC’s tenure, various areas key to the development of research data assessment metrics have been identified. Please join a Spring seminar and discussion series centered around priority work areas, adjacent initiatives to learn from, and steps that can be taken immediately to drive diverse research communities towards assessment and reward for open data.

The second webinar titled “EXPLORE: the need for an open classification system” will deal with the issue that most datasets do not have subject information. However, meaningful data metrics cannot be developed without disciplinary contexts; the scholarly communications community needs an open classification system for research outputs (articles, journals, datasets etc.) – is this feasible?

Speakers include:

00:00 Introduction by Matt Buys (Executive Director of DataCite)

00:57 EXPLORE: the need for an open classification system – Daniella Lowenberg (California Digital Library), slides: https://doi.org/10.5281/zenodo.6423319

04:39 Exploring Open Classification – Stefanie Haustein (University of Ottawa), slides: https://doi.org/10.5281/zenodo.6420004

17:21 Ludo Waltman (Leiden University)

22:49 Kristi Holmes (Northwestern Feinberg School of Medicine)

25:43 Jason Priem (OurResearch)

30:19 Classification: The @crossref REST API story – Geoffrey Bilder (Crossref), slides: https://doi.org/10.5281/zenodo.6423362

38:48 Q&A session