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Report . 2025
License: CC BY
Data sources: Datacite
ZENODO
Report . 2025
License: CC BY
Data sources: Datacite
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GATE Workshop #1 - Implementing Open Science for Communities

Authors: Alavi, Marie; Müller-Karabil, Anika; van Drimmelen, Tom; Fischer, Rebecca;

GATE Workshop #1 - Implementing Open Science for Communities

Abstract

This report summarises the die outcomes of the last GATE workshop - "Implementing Open Science for Communities" which was held on July 1, 2025 at the Metascience Conference 2025 (interactive Unconference session). The GATE Workshop aimed to collaboratively identify the needs of specific Open Science target groups using GATE Data and to develop targeted ACTIONS to advance Open Science within various communities. This focus is crucial, as one of the key findings from the GATE Data highlights that transparent, collaborative, and accessible science is a valuable means to foster trust, equity, and innovation, but real change requires both individual action and systemic reform. Before the GATE Workshop, Open Science Knowledge Creators connected their resources to GATE. They provided information about the guiding thoughts implemented into their materials via the GATE Service. This information, known as GATE Data, formed the basis of the workshop's content and included data and resources from organisations/projects such as NFDI, CLARIN, ZBW, the OPTIMA Project, and EOSC. At the workshop the GATE members welcomed 18 participants from research and funding. After an introduction into the GATE Initiative, its collaborators and features GATE Service and GATE Report, the participants engaged into lively discussions. They grouped into three groups and collaboratively identified challenges and needs specific to their Open Science community using GATE Data (two to three guiding thoughts that they have identified to be relevant for their communities). Each group developed targeted ACTIONS to advance Open Science collectively: For ERCs: Open-lab Workbooks providing a better overview and documentation of ERC's progress and best practice examples For Senior researchers: Organising internal “code checks” at departments and institutions before publishing that reduce the likelihood of mistakes left in researchers' own codes and thus increase the willingness to share the code. Working in trusted repositories to maintain data confidentiality. Leveraging existing “federated data systems” that analyse the data submitted, while the data stays in the system and ensures data confidentiality. For Open Access Officers: Establishing persistent identifiers and requirements to allow optimum traceability, including leveraging AI to capture additional information. Submitting data into existing databases and connecting to other repositories. Developing tools (including AI) supporting reproducibility checks (including the validity of data and the analysis). Establishing processes for funders and fundees to support Open Science. The workshop showcased GATE’s features for collective efforts to advance Open Science, enabling representatives from different communities to identify needs and challenges and co-create supporting ACTIONS that foster Open Science for their target groups. The GATE initiative, as a cooperative, transparent, and non-profit effort, continues to establish itself as a trustworthy solution to build and maintain Open Science capacities. For more information or to join the GATE service, visit www.openscienceGATE.com.

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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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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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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
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