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Assessing the Impact of Open Research Data Sharing. Contributions and Tools from the PathOS Project

Authors: Stoy, Lennart; Martins Grapengiesser, Izabella; Seminaroti, Elisa; Grypari, Ioanna;

Assessing the Impact of Open Research Data Sharing. Contributions and Tools from the PathOS Project

Abstract

FAIR and Open research data sharing is becoming more and more ubiquitous. The rationale behind this trend and policy imperative includes improving efficiency and reproducibility, advancing interdisciplinary research, and driving uptake and innovation. However, the actual impact of research data sharing in academic, economic, or societal contexts, is less well understood than for instance the effects of open government data. PathOS (https://pathos-project.eu/) is a 3-year Horizon Europe project that seeks to expand the available knowledge on the impacts of Open Science and Open Research Data. It does so along three main areas: 1. Modelling of the impact pathways: Mapping key effects of OS in terms of outputs, their usage, outcomes and impacts for key areas, including open research data and open methods 2. Supporting the testing and operationalization of OS indicators: Providing indicators, tools, data and flows to ensure practical implementation and validating them in six case studies. 3. Developing a Cost-Benefit Analysis (CBA) framework: Providing insights on the net economic value of specific Open Science and Open Data practices. The poster will highlight the major findings and tools related to Open Research Data, focusing on four key dimensions: Conceptualise: A systematic framework for the evaluation of Open Science interventions applied to data sharing, derived from policy evaluation methodology, which aids the conceptualisation of Key Impact Pathways for the academic, societal, and economic impact of Open science. [3] Understand: Results of a large-scale literature review that identified gaps in evidence regarding the impact of research data sharing, where some evidence for impacts on re-use, citations, but also policymaking and governance could be identified [1,2] Measure: A snippet of open data and impact indicators in the PathOS Indicator Handbook (https://handbook.pathos-project.eu/) Evaluate. An example application of Cost-Benefit Analysis to Open Data infrastructures [4]. A case study on the UniProt repository operated by Elixir how such a framework can be applied to real-life example [5]. Through the poster, we seek to showcase the potential of these conceptual and practical outputs to be applied elsewhere. This can be for example through the design of impact pathways and impact monitoring indicators, such as in research projects, institutional monitoring, or policy/funding programmes. All results and tools of PathOS are available on the projects resource hub (https://pathos-project.eu/pathos-os-resources-hub ).

Keywords

IDCC25, Monitoring, Impact analysis, Research evaluation, Cost benefit analysis, Open data, Sustainability and strategy: Analyses of the costs and benefits of curation, Sharing data: Measuring the impact and reuse of data by traditional or alternative metrics

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    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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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).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
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