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talk · Thursday 24 September · 09:12–⁠09:25 · SAL C

Digitize, Standardize, Mobilize: Wildlife Biodiversity Biobanking with Specify

Kim Labuschagne · Meeting Biodiversity Data Standards Using Specify Software

Recording time 1:31:29–1:44:48Open on Vimeo ↗

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

The short versionSpecify's hierarchical trees and attachments turned a fragmented wildlife biobank into a traceable extended-specimen data system.

Overview

What this was about

Kim Labuschagne presented the SANBI Wildlife Biobank, which holds samples and e-vouchers rather than whole specimens. It has over 250,000 samples from more than 110,000 animals in 46 countries, covering about 1,900 species including many threatened ones. She explained why an extended-specimen data model is needed to link samples, derivatives, permits, storage history, molecular data and publications, and how implementing Specify around 2013 replaced disconnected spreadsheets and records. Key features are the taxon, storage (bank→freezer→rack→box→position) and geography trees, attachments for permits and chain-of-custody photos, and customisable workflows.

Why it matters. Biobanks are growing conservation and genomics infrastructure, and their value depends on tracing every aliquot, permit and derived dataset back to the individual animal.

Key ideas

In the room

  • The biobank was established in 1994 and holds over 250,000 samples from more than 110,000 individual animals from 46 countries, spanning 14 phyla and nearly 1,900 species.
  • Many holdings are threatened on the IUCN Red List, including the extinct western black rhino.
  • 79 different sample types are stored from room temperature down to -196 °C. Every freezer-to-freezer move is a QC point that must be recorded.
  • The data model has moved from 'tissue sample + catalogue number' to an extended specimen with voucher, field metadata, permits, storage history, DNA extraction, genome sequence, disease screening and publications.
  • Specify was implemented around 2013, with support from SAIAB, to replace disconnected systems.
  • The storage tree locates samples down to position in a box. Catalogue numbers plus barcodes prevent searching through hundreds of boxes.
  • Attachments hold permits (including CITES and disease regulations), data sheets and chain-of-custody photographs.
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Notable moments

In their words

Transcript

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Programme abstract

Digitize, Standardize, Mobilize: Wildlife Biodiversity Biobanking with Specify

Kim Labuschagne

Biodiversity biobanks are increasingly recognized as critical research infrastructures supporting conservation, genomics, species management, and One Health initiatives through the long-term preservation of samples and associated metadata. While the physical preservation and curation of samples remains central to biobanking, the scientific value of these collections depends on the generation of high-quality, standardized, and interoperable data. As biodiversity research advances toward implementation of FAIR (Findable, Accessible, Interoperable, and Reusable) principles and the Extended Specimen concept, these biobanks face challenges in managing multidimensional datasets that extend beyond individual samples to include taxonomic, spatial, genetic, regulatory, and derivative information. Within the SANBI Wildlife Biobank, collections include diverse taxa and sample types such as blood, tissues, DNA extracts, and cell cultures linked to permits, storage records, images, molecular data, and metadata. Historically, these data were distributed across disconnected spreadsheets, paper records, folders, and external drives, creating challenges in data consistency, accessibility, and long-term sustainability. The implementation of Specify has transformed collection workflows from fragmented data management practices into an integrated relational framework capable of linking specimens, tissue collections, storage information, compliance documentation, and taxonomic data within a single system. The use of hierarchical taxonomy structures, controlled vocabularies, unique identifiers, and customizable workflows has improved data consistency, sample traceability, quality control processes, and transformed biodiversity biobanks from static repositories into dynamic digital resources.

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