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talk · Tuesday 22 September · 11:00–⁠11:15 · SAL B

Open Digital Curation Needs: openness, interoperability, provenance

Deborah Paul · Responsible AI, Open Digital Curation, and Round-Tripping for Biodiversity Data

Recording time 2:29:31–2:44:41Open on Vimeo ↗

Summaries and key moments are machine-produced. Check the recording for the speaker’s exact words.

The short versionOpen digital curation increases transparency, agency and trust and reduces latency, but needs new provenance practices for AI.

Overview

What this was about

Deborah (Debbie) Paul, from the team behind TaxonWorks, Catalogue of Life work and Global Names, argued that open digital curation - built on openness, interoperability, provenance and identifiers - empowers wider participation and shortens the path from spotting an error to fixing it. Examples included Bionomia profiles that keep deceased collectors' expertise attributed, an iNaturalist user fixing names directly in the Orthoptera Species File, and TaxonWorks features letting projects search and clone each other's controlled vocabularies linked to ontologies. She welcomed agents (including LLMs) with roles in the Darwin Core Data Package, raised questions about what provenance we must now track for AI use, and asked how shifting openness (API keys, CC0 to CC BY, logins) will affect interoperability.

Why it matters. Frames the symposium's themes and poses concrete open questions for standards around AI provenance and openness.

Key ideas

In the room

  • Her team works on TaxonWorks, Catalogue of Life and Global Names; about 25% of Catalogue of Life names reaching the GBIF backbone come from TaxonWorks workbenches.
  • Openness, interoperability and provenance all depend on identifiers and TDWG standards; most interoperability pieces now exist.
  • Bionomia lets expertise of people no longer active continue to be credited; an early-career researcher's Zenodo dataset updated via the Bionomia API has been downloaded over 1,000 times.
  • Human-mediated round-tripping: an iNaturalist user reports Orthoptera name issues directly in the Orthoptera Species File GitHub repo, shortening the time to fix.
  • TaxonWorks lets projects create controlled vocabulary terms linked to ontology URIs (e.g. 'petiole' in plants vs insects), and search and clone other projects' terms.
  • Darwin Core Data Package agents can be LLMs; agents need identifiers and roles, which aligns with TaxonWorks' person-role model.
  • Journal policies (e.g. Pensoft) ask authors to state AI use in methods and forbid reviewers putting unpublished manuscripts through AI.
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Notable moments

In their words

Transcript

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Programme abstract

Open Digital Curation Needs: openness, interoperability, provenance

Deborah Paul

Moving toward open digital curation to make round-tripping possible, consider the necessary interplay of three facets: openness, interoperability, and provenance. Via open application programming interfaces (APIs), data becomes accessible to humans and AI. Given openness, interoperability becomes possible and offers opportunities to contribute and collaborate. We share three examples here: [iNaturalist (iNat)](https://www.inaturalist.org/), the [Catalogue of Life (COL)](https://www.catalogueoflife.org/), and the [Global Biodiversity Information Facility (GBIF](https://www.gbif.org/)). With iNat's open APIs, our researchers using [TaxonWorks (TW)](https://taxonworks.org/) can pull images and related data into TW. In the other direction, iNat curators submit or point their users to the specific gitHub repository to log taxonomic inquiries directly to those curating these data. This reduces steps (e. g. emails) needed to get to round-tripping. From TW, our collections data go straight to GBIF. We grab the GBIF-related ingestion feedback directly into TW to again reduce the human mental data curation burden and imagine future automated validation. Our taxonomic data flow interoperably between TW to COL via [Checklist Bank](https://www.checklistbank.org/). To do all of the above, we must decide on and use identifiers (e. g. [ORCiD](https://orcid.org/)s, [Wikidata Q numbers] (https://www.wikidata.org/wiki/Q43649390)) and the related metadata that helps us ensure we have a provenance trail. Understanding our data through these breadcrumbs provides the foundation for round-tripping. In TW, imagine extracting data from literature using large language models (LLMs). Our communities need software and APIs to vet the resulting data, along with robust provenance. We find it's these decisions, usually human-mediated, that are difficult to capture in context, for example, with the user interface. When we connect via our APIs for data exchange, what must we persist? What can be temporary?

Submitted to the conference programme before the talk, so the talk itself may differ.