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SUMMARY:­WiNoDa x DiSSCo Online Hackathon: Advancing Specimen Data
DTSTART:20261014T070000Z
DTEND:20261015T120000Z
DTSTAMP:20260719T210800Z
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:\n\nSoftware engineers\, data scientists and people who work with ob
 ject-based scientific collection data and are interested in developing and
  connecting Machine Annotation Services (MAS) directly to the DiSSCo infra
 structure.\n\nDescription:\n\nWorking in small teams\, you will learn how 
 to develop and connect Machine Annotation Services (MAS) directly to the D
 iSSCo infrastructure. These automated services act on Digital Specimens to
  provide critical data quality assessments\, error corrections\, or links 
 to derived scientific data (such as gene sequences). You can work with spe
 cimen data provided by the platform or bring your own datasets (which must
  be integrated into the infrastructure prior to the event).\nOur experts w
 ill be on hand to provide both technical and conceptual support.\nFor this
  Hackathon we specifically encourage MAS applications that do ground work 
 for other MAS services by annotating image quality and improving AI readin
 ess. Potential MAS applications include\, but are not limited to:\n \n\n\
 n\n\nROI Segmentation: Automatically identifying and isolating areas in an
  image containing labels\, stamps\, organisms\, mounting materials\, ruler
 s\, or color bars.\n\n\nAI-Readiness & Image Quality Auditing: Evaluating 
 image clarity (blur detection)\, lighting uniformity\, and the orientation
  or display state of the organism.\n\n\nSpecimen Condition Analysis: Detec
 ting physical damage\, fragmentation\, or signs of pest infestation on phy
 sical objects.\n\n\nTechnical Metadata Enrichment: Extracting and validati
 ng extended metadata\, such as color spaces\, compression levels\, resolut
 ion\, and ruler to pixel calculation.\n\n\nHistorical & Contextual Analysi
 s: Identifying collectors and curators based on handwriting recognition or
  identifying languages on labels.\n\n\n\n \nThe data will be processed in
  accordance to the Privacy Policy of the German Federation for Biological 
 Data (GFBio). The detailed version can be found here: https://www.gfbio.o
 rg/privacy-policy.\nFeel free to contact winoda@gfbio.org if you have spec
 ific inquiries. \nPlease fill in the questionnaire\; it will help us to o
 rganise the event more effectively.\n\nhttps://events.gfbio.org/event/202/
URL:https://events.gfbio.org/event/202/
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