05-30, 11:55–12:20 (Europe/Amsterdam), Fluor podium
"Transparency does not guarantee credibility; it guarantees you get the credibility you deserve" (Vazire, 2021)
We introduce Transparency Check: a set of tools that researchers, data support professionals, educators, journal editors, peer reviewers and research funders can use to automatically assess the transparency and comprehensiveness of documentation of data and methods. The tools consist of rule based checks, supervised learning models that assess the presence of information about data help science evaluate the transparency of research reports. In addition, AI-powered Large Language Models can suggest improvements to documentation of data and methods. In the session we invite participants to try out the tools we have developed and rank priorities for characteristics of research reports that could be assessed with tools to be developed in the future.
Professor at VU Amsterdam