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SUMMARY:Angebot 3: When FAIR Goes Wrong: Learning from Bad Examples in Ele
 ctronic Lab Notebooks
DTSTART:20261125T150000Z
DTEND:20261125T163000Z
DTSTAMP:20261021T025800Z
UID:indico-event-381@events.academiccloud.de
CONTACT:datadays2026@uni-oldenburg.de
DESCRIPTION:Speakers: Benjamin Golub-Overbeck\, Lea Löhn\n\n \n\nWhat ca
 n we learn from a laboratory record that is not FAIR?\nThis interactive wo
 rkshop takes a deliberately unconventional approach to FAIR Data Principle
 s: instead of starting with best practices\, we start with bad examples. P
 articipants will examine selected examples of poorly documented entries in
  an electronic lab notebook (ELN) and work together to identify what makes
  these records difficult to understand\, reuse\, or interpret.\nUsing eLab
 FTW as a practical environment\, the workshop focuses on questions that ar
 e relevant beyond any specific ELN system or research discipline: What inf
 ormation is missing? What would someone else need to understand or reuse t
 his record? Which elements affect its Findability\, Accessibility\, Intero
 perability\, and Reusability?\nParticipants will critically assess the exa
 mples from different disciplinary perspectives and then compare their obse
 rvations with an existing template guide for creating FAIR laboratory reco
 rds. This provides an opportunity not only to identify gaps in individual 
 records\, but also to reflect on whether existing guidance addresses the c
 hallenges researchers encounter in practice.\nNo prior knowledge of eLabFT
 W or the FAIR principles is required. The workshop is designed as a collab
 orative exercise in which different disciplinary perspectives are explicit
 ly welcome. By turning bad examples into a starting point for discussion\,
  we aim to make FAIR principles tangible\, identify common documentation c
 hallenges\, and explore practical ways to improve the quality and reusabil
 ity of research records.\nJoin us in looking at what went wrong — and di
 scover what it takes to make entries in eLabFTW FAIR.\n\nAcknowledgement:\
 n\nThe abstract was written with the help of AI (Chat AI\,Qwen 3 30B A3B I
 nstruct 2507)\n\n---\nDie Veranstaltung wird von der Landesinitiative Fors
 chungsdatenmanagement Niedersachsen (FDM-NDS) organisiert. FDM-NDS ist ein
  Verbundprojekt unter dem Dach der Hochschule.digital Niedersachsen und wi
 rd im Rahmen von zukunft.niedersachsen\, einem Förderprogramm von Nieders
 ächsischem Ministerium für Wissenschaft und Kultur (MWK) und VolkswagenS
 tiftung gefördert.\n\nhttps://events.academiccloud.de/event/381/
IMAGE;VALUE=URI:https://events.academiccloud.de/event/381/logo-1451852843.
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LOCATION:Rechnerraum im BIS (B147) (Carl von Ossietzky Universität )
URL:https://events.academiccloud.de/event/381/
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