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SUMMARY:DiSSCo x WiNoDa Hackathon 2026: on machine annotation services
DTSTART:20261014T070000Z
DTEND:20261015T120000Z
DTSTAMP:20260706T234600Z
UID:indico-event-202@events.gfbio.org
CONTACT:winoda@gfbio.org
DESCRIPTION:DiSSCo x WiNoDa Hackathon 2026: on machine annotation service
 s (MAS)\nWhen: 14 - 15 October (Hackathon)\; 14 September (Kick-Off)Where:
  onlineCredit: no creditsCharges: no chargesLanguage: English\nOrganisatio
 n:\n\nThe hackathon is jointly organised by the German Federation for Biol
 ogical Data (GFBio) and the Naturalis Biodiversity Center.\nGFBio is a lea
 ding initiative for biological data management operating across Germany an
 d serves as a core partner of the WiNoDa Knowledge Lab (Data Science in Na
 tural History Collections).\nNaturalis Biodiversity Center\, located in Le
 iden\, The Netherlands\, is a world-class research institute and natural h
 istory museum dedicated to documenting global biodiversity. Naturalis lead
 s the development of the core data infrastructure for DiSSCo (Distributed 
 System of Scientific Collections)\, which creates digital proxies of speci
 mens in natural history collections known as Digital Specimens.\n\nTarget 
 Group:\nPeople who work with object-based scientific collection data and a
 re interested in developing and connecting Machine Annotation Services (MA
 S) directly to the DiSSCo infrastructure.\nDescription:\n\nWorking in smal
 l teams\, you will learn how to develop and connect Machine Annotation Ser
 vices (MAS) directly to the DiSSCo infrastructure. These automated service
 s act on Digital Specimens to provide critical data quality assessments\, 
 error corrections\, or links to derived scientific data (such as gene sequ
 ences). You can work with specimen data provided by the platform or bring 
 your own datasets (which must be integrated into the infrastructure prior 
 to the event).\nOur experts will be on hand to provide both technical and 
 conceptual support.\nFor this Hackathon we specifically encourage MAS appl
 ications that do ground work for other MAS services by annotating image qu
 ality and improving AI readiness. Potential MAS applications include\, but
  are not limited to:\n \n\n\n\n\nROI Segmentation: Automatically identify
 ing and isolating areas in an image containing labels\, stamps\, organisms
 \, mounting materials\, rulers\, or color bars.\n\n\nAI-Readiness & Image 
 Quality Auditing: Evaluating image clarity (blur detection)\, lighting uni
 formity\, and the orientation or display state of the organism.\n\n\nSpeci
 men Condition Analysis: Detecting physical damage\, fragmentation\, or sig
 ns of pest infestation on physical objects.\n\n\nTechnical Metadata Enrich
 ment: Extracting and validating extended metadata\, such as color spaces\,
  compression levels\, resolution\, and ruler to pixel calculation.\n\n\nHi
 storical & Contextual Analysis: Identifying collectors and curators based 
 on handwriting recognition or identifying languages on labels.\n\n\n\n \n
 The data will be processed in accordance to the Privacy Policy of the Germ
 an Federation for Biological Data (GFBio). The detailed version can be fou
 nd here: https://www.gfbio.org/privacy-policy.\nFeel free to contact wino
 da@gfbio.org if you have specific inquiries. \nPlease fill in the questio
 nnaire\; it will help us to organise the event more effectively.\n\nhttps:
 //events.gfbio.org/event/202/
URL:https://events.gfbio.org/event/202/
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