talk · Thursday 24 September · 08:33–⁠08:46 · SAL C

SpecifyaaS: Managing Ephemeral Repositories in Collections-Based Research

Kevin Holston · Meeting Biodiversity Data Standards Using Specify Software

Recording time 50:54–1:03:53Open on Vimeo ↗

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

The short versionGiving researchers their own lightweight Specify instances early in the research process standardises data from the start and eases later exchange with the institutional collection.

Overview

What this was about

Kevin Holston explained how the Swedish Museum of Natural History runs its own local Specify 7 instances ('Specify as a Service') as ephemeral or semi-persistent repositories for researchers, rather than pushing them straight into the institutional collection database. He distinguished research-group collections of loaned, persistent vouchers from institutional programmes such as biobanks and the environmental specimen bank, whose semi-persistent vouchers are used up over time. As an example, he showed how a researcher's 16 years of Madagascar aquatic insect inventory became a Specify research database with 808 collecting events, organised event images and field sheets. He argued that these instances bring standards in early and act as laboratories of innovation for Specify.

Why it matters. Much specimen data is created in project spreadsheets before it ever reaches a collection database. Giving researchers compatible, low-commitment instances is a practical way to get standards and identifiers in early and to track derivatives and loaned material as their own objects.

Key ideas

In the room

  • NRM runs local Specify installations on its own infrastructure and spins up temporary instances, for example for visiting researchers, that are compatible with the institutional database.
  • Category 1 (research group/project): material is mostly on loan, vouchers are persistent, and the project repository has little motivation to record where things physically are.
  • Category 2 (research institution/programme, e.g. biobank, eDNA and environmental specimen bank): vouchers are semi-persistent and subject to depletion, and the repository must reflect the physical collection.
  • Historically, derivatives have been documented as voucher attributes rather than as independent objects, which limits tracking of objects, attributes and locations over time.
  • A researcher's Madagascar aquatic insect inventory became a Specify research database with 808 collecting events over 16 years of trips. An unexpected benefit was standardisation and the organisation of event images and field data sheets.
  • Holston repurposed the Specify storage tree to record provenance, i.e. loans, in his own research database, showing Specify's flexibility.
  • Instances can be 'furnished' (pre-loaded with collection data, like a furnished house or hotel) to give visitors a head start in digitising.
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Notable moments

In their words

Transcript

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Programme abstract

SpecifyaaS: Managing Ephemeral Repositories in Collections-Based Research

Kevin Holston

Specify 7 has substantially expanded the capacity of institutions to standardize efficient biodiversity data capture, management, and exchange during collections-based research. At the Swedish Museum of Natural History (NRM), data are maintained across multiple Specify instances, which includes databases for research programmes and projects. They support collaborative initiatives characterized by operational constraints that often differ greatly from those of the public repositories where research specimens will ultimately be deposited.

Here I describe the use of Specify 7 instances as “ephemeral repositories” within the biodiversity data network at the NRM. Although they are often broader in scope with respect to the data compiled, and less likely to persist as independent data aggregations, ephemeral repositories are critical staging arenas for data standardization, mobilization, and exchange. As an low-investment outcome from using Specify 7, that reduces reliance on bespoke or isolated data management solutions, Specify-as-a-Service is intended to support efficient transfer of information to downstream systems after phases of active research.

Investment in early standardization improves data quality and reduces duplication of effort during rounds of data capture. Extending IT infrastructure into the broader suite of institutional tools supporting collections-based research promotes the implementation of FAIR practices and consistent workflows. Providing SpecifyaaS to staff and research collaborators will strengthen data integration across research and collections systems, and increase the long-term data usability and applicability across a wider range of use cases.

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