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BEGIN: metadata for meaningful data metrics

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BEGIN: metadata for meaningful data metrics
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5
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CC Attribution 3.0 Unported:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
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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 third and last webinar in our series “BEGIN: metadata for meaningful metrics” will look at next steps to develop responsible and fair data metrics that can reflect the use and impact of research datasets and help elevate them to first-class scholarly outputs. We’ll focus on necessary metadata to construct metrics that take into account characteristics and contexts of open data across disciplines. Speakers include: 00:00 Introduction by Matt Buys (Executive Director of DataCite) 01:49 BEGIN: metadata for meaningful data metrics – Stefanie Haustein (University of Ottawa), 06:53 Meaningful Data Metrics for Whom? – Christine Borgman (UCLA), 14:13 Data Metrics and the Reward System of Science – Rodrigo Costas (Leiden University), 22:41 Developing responsible and fair data metrics – Nicolas Robinson-Garcia (Granada University), 29:56 Meaningful Indicators for Research Data – Isabella Peters (ZBW), 38:09 Q&A session