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talk · Thursday 24 September · 09:25–⁠09:40 · SAL A

Confronting legacy data for primary type specimens

Cailin Meyer · From Cabinets to Clouds - Bridging the gap between collection- and database management

Recording time 1:42:20–1:56:55Open on Vimeo ↗

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

The short versionDecades of database migrations left the second-largest insect collection's type catalogue unreliable, and only a full physical inventory is fixing it.

Overview

What this was about

The presenter traced the USNM Entomology primary type catalogue through handwritten ledgers (since 1896), the in-house INQUIRE type database (1980s), CRIS (mid-1990s) and EMu (migration 2007, full use by 2011). Poor field mapping from INQUIRE meant every migrated type record carried a public disclaimer as an 'INQUIRE type'. Migrated CRIS transaction records lacked objects and had odd dates. Barcodes were duplicated, and some types were never catalogued or linked to acquisitions. The department launched a multi-year, 100% specimen-level type inventory: curators compare EMu spreadsheets with specimens, and transaction discrepancies are resolved against paper records.

Why it matters. The talk is a frank case study of how legacy migrations degrade data and what a sustained, phased remediation looks like. Collections facing similar INQUIRE/CRIS/EMu-style histories can learn from it.

Key ideas

In the room

  • The USNM Insect Collection (est. 1881) holds about 35 million specimens, over 400,000 species and over 130,000 primary types, with a small staff.
  • Type ledgers in use since 1896 recorded catalogue number, name, sex, locality, year, sender, collector and entry date.
  • INQUIRE (1980s, in-house) was kept separate from CRIS; both were migrated to EMu in 2007, and INQUIRE fields mapped badly.
  • All migrated INQUIRE records carry a disclaimer until reviewed; a 'complete' record needs review, a USNM ENT barcode and an image.
  • Other problems: uncatalogued types, duplicate barcodes from an external printer, and workflow gaps leaving acquisitions unlinked.
  • Phase 1: curators check EMu spreadsheets against specimens. Phase 2: transaction linking and loan matching. Phase 3: vetting INQUIRE data and type citations. Phase 4: imaging.
  • Progress: almost 3,500 existing type records completed and over 500 new types added.
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Notable moments

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Transcript

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Programme abstract

Confronting legacy data for primary type specimens

Cailin Meyer

Often historic natural history collections pose great challenges such as tracking taxonomic changes between the database and the physical labels, properly recording specimen movements, and maintaining legacy databases. This is particularly true for the SI NMNH Entomology Department, which is home to ~150,000 primary types. In 2007, data was migrated from INQUIRE, a database designed by the department, to EMu, a Collection Information System (CIS) used museum wide. Due to structural incompatibilities of INQUIRE with EMu, the data migration faced challenges and significant nuances of INQUIRE data were lost. All type records migrated from INQUIRE were categorized as “INQUIRE TYPES” in EMu and publicly flagged, while new type records were categorized as “Entomology Types”. From the time of the migration, the department tried to remedy the lost nuance by updating INQUIRE Type records whenever a type was handled. Dubbed the Type Inventory Project for Entomology Specimens (TIPES) Project, Collections staff are working alongside Curators to reconcile primary type specimen records in EMu against registration files and the physical collection, while maintaining a list of what should be physically present. The project has created opportunities to redefine workflows and ensure proper data capture, physical specimen security, and legal accountability, while sharing up-to-date records online and on GBIF to mitigate future data loss. The goal is to develop a streamlined workflow that removes communication barriers and prevents bottlenecks from forming on any one role. Additionally, the department is exploring AI-driven tools to identify gaps in the Primary Type collection via automated literature reviews for keywords, compared against the existing known inventory after its completion.

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