
This record contains materials for a hackathon (open discussion) or a series of hackathons organized by ABRIR, focused on decolonizing data governance in Big Team Science projects. The goal of the event is to lay the groundwork for future guidelines on trustworthy and responsible sharing, ownership, and reuse of data collected by Majority World researchers in Big Team Science collaborations. The materials include a detailed plan outlining the purpose and rationale of the event, the intended audience, the proposed format and logistics, and the structure of the session, with notes for moderators and discussion prompts. The materials also include a glossary of relevant terms such as JEDI, FAIR Data principles, CARE principles, the TRUST code, ethics dumping, extractive research, and helicopter research, as well as a set of suggested articles, books, and further training resources.
This content was developed through a project funded by the Open Scholarship Catalytic Awards Program (Award Number: #20160-2025-10), with support from the Open Research Community Accelerator (ORCA) and the Chan Zuckerberg Initiative.
open science, big team science, collaborative research, research data management
open science, big team science, collaborative research, research data management
| 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 |
