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The Make Data Count Summit took place in Washington DC on 12-13 September 2023 as a forum for dedicated discussion on data metrics and the evaluation of data usage. The event brought together representatives across research and research-supporting organizations, government and policy institutions, and infrastructure providers to discuss immediate needs to drive broader development and adoption of data metrics. We include the slides for the talks presented at the event: Welcome by Iratxe Puebla, DataCite ‘Defining the Need for Open Data Metrics’ by Daniella Lowenberg, University of California Office of the President ‘Forging the path forward: Global Data Citation Corpus’ by Matt Buys, DataCite and Carly Strasser, Chan Zuckerberg Initiative ‘Democratizing Data’ by Julia Lane, NYU Wagner Graduate School of Public Service ‘Five years since the US Evidence-act’ by Nancy Potok, NAPx Consulting and New York University ‘Meaningful Data Metrics: The State of Evidence from Bibliometrics Studies on Data Reuse’ by Stefanie Haustein, University of Ottawa and ScholCommLab, Nicolas Robinson-Garcia, University of Granada, Mike Thelwall, University of Sheffield, and Thed van Leeuwen, Centre for Science and Technology Studies, Leiden University
data metrics, data usage, open data, metrics, evaluation, assessment, evidence-based metrics, research, administrative data
data metrics, data usage, open data, metrics, evaluation, assessment, evidence-based metrics, research, administrative data
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 85 | |
| downloads | 40 |

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