WorldFAIR (D9.2) Community consultation and finalisation of Biodiversity FAIR data impact: Final data model and training materials completed and shared
Creators: name: Miller, Joe
name: Robertson, Tim
name: Wieczorek, John
Publisher: name: Zenodo
Year: 2023
Subjects: biodiversity
data interoperability
research data
data models
community standards

description: Biodiversity standards are essential for FAIR data, in particular for interoperability.  Current standards need to be improved with new data models to better reflect the complexity of biodiversity and serve the information needed to address biodiversity loss and climate change. This Deliverable D9.2 is focussed on the results of Task 9.2: 'Community consultation and finalisation of Biodiversity FAIR Data Impact'.
Facilitated via WorldFAIR, Global Biodiversity Information Facility (GBIF)'s engagement with the biodiversity community has led to this Deliverable – a new community-approved data standard that has progressed through a long community-led process. This Deliverable details the importance of collaboration and getting broad uptake of a new standard by the primary user community. This aligns with the overall objectives of WorldFAIR by focusing development on improving the interoperability of biodiversity data. Our FAIR Implementation Profile (FIP) will be enhanced by this improved functionality. This work promotes cross-domain interaction as the Unified Data Model will enhance sharing of data in related Work Packages such as Agricultural Biodiversity, Oceans, and Geochemistry in the final portion of the WorldFAIR grant period. This work has been undertaken in alignment with the overall WorldFAIR goals, in particular WP02 on Engagement, Synthesis, Recommendations and FAIR Assessment.
The new model, CamTrap DB, has been incorporated into the new and evolving GBIF Unified Data Model (see WorldFAIR D9.1).  CamTrap DB is an important update to the previous camera trap data models.  The use is growing of camera traps to non-invasively monitor biodiversity.  Cameras are set in nature and take images of organisms with the resulting images being processed into GBIF occurrences - the evidence of a species at a particular place and time. Technologies have greatly improved in recent years and a plethora of new camera traps have been deployed, alongside the advent of AI technologies to more easily and rapidly identify organisms on the camera trap images.  Camera traps are set to become major tools for biodiversity monitoring. In order to meet these goals, the image data management needed improvement: data management rather than data collection is now the limiting factor.
GBIF, through WorldFAIR, helped the camera trap research community rapidly take the updated model and facilitate adoption of best practices and the development of new GBIF infrastructure for FAIR data publication. This work is now adopted as part of the GBIF Unified Data Model. This work is an example of a research infrastructure facilitating a community standard development and making sure their best practices are codified and used within the research infrastructure.
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WorldFAIR is funded by the EC HORIZON-WIDERA-2021-ERA-01-41 Coordination and Support Action under Grant Agreement No. 101058393.