The public and the press already expect to assess the trustworthiness of research relevant to pressing social and public health issues in terms of transparency. While widely recognized as a critical component of research reproducibility in principle, the promise of making research fully transparent—and scientific claims easier to evaluate—via reliable provenance has yet to be realized in full. In particular, it is still far from routine for researchers in the natural, social, and data sciences to assess the trustworthiness of reported results using automatically captured provenance information.
This workshop aims to engage Provenance Week 2021 attendees in a focused conversation about how methods for automated provenance capture, storage, query, inference, and visualization can make research more transparent and the trustworthiness of results easier to evaluate, both by other researchers and by the public.
In brief presentations speakers will propose actionable definitions of terms such as transparent, trustworthy, and traceable; identify needs of research communities and other stakeholders; prioritize desiderata for real-world system implementations; and highlight remaining challenges.
Everyone who attends the T7 Workshop is considered a participant. All attendees will be invited to comment and contribute their own definitions, priorities, and requirements in real time. The suggestions will be ranked both by generality across research domains and specificity to particular domains. The resulting recommendations and rankings will be included in a workshop report.
We ask that everyone planning to attend please read the Instructions for All T7 Workshop Participants to make the workshop as productive as possible.
SEEK ID: https://workflowhub.eu/events/8
Teams: FAIR Computational Workflows
22nd Jul 2021 at 22:28
22nd Jul 2021 at 22:28