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talk · Tuesday 22 September · 16:45–⁠17:00 · SAL C

Assessing record quality and completeness in geoscience collections

Adam Mansur · State of the Collections Description Interest Group. What's Happening and What's Not!

Recording time 8:12:47–8:26:49Open on Vimeo ↗

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

The short versionElement-level views of MIDS information elements are more useful than raw scores for targeting data improvement in large geoscience collections.

Overview

What this was about

Adam Mansur compared the Smithsonian's internal Collection Digitization Reporting System (CDRS) with MIDS for assessing record completeness in the Mineral Sciences (about 500,000 records, largely digitised) and Paleobiology (about 800,000 records against an estimated 10-13 million needed) collections. CDRS rules vary by department, are conditional and opaque, and barely move with large projects, whereas MIDS scores are consistent but cluster tightly around MIDS 1 because of the large jump required to reach MIDS 2. He argued that element-level breakdowns (e.g. via the MIDS calculator) are more useful for targeting work: Mineral Sciences lacks stratigraphic context in most records regardless of acquisition decade, while Paleobiology has gaps in names and object type concentrated in particular collections.

Why it matters. Offers practical guidance for using MIDS to plan digitisation and enhancement work, and highlights needs such as signalling checked-but-null values.

Key ideas

In the room

  • NMNH holds an estimated 140 million objects across seven departments, two geology-focused.
  • Geology metadata resembles biological metadata plus geologic context (unit, age).
  • CDRS measures completeness against a 'standard record' by presence/absence checks per primary collection.
  • Departmental CDRS rules are inconsistent, conditional and hard to interpret; big projects barely change collection-wide scores.
  • Departments mostly treat media as an enhancement, unlike MIDS; CDRS also includes internal elements like storage location and accession number.
  • MIDS scores cluster around level 1, so they are only sensitive to large changes.
  • Stratigraphic context is present in only 5-20% of Mineral Sciences records across acquisition decades, an intrinsic feature of incoming data.
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Transcript

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Programme abstract

Assessing record quality and completeness in geoscience collections

Adam Mansur

The Minimum Information about a Digital Specimen (MIDS) standard allows collections to assess digitization progress using a numeric, discipline-specific score. Here we describe efforts to assess this type of data quality score in collections of geological specimens at the Smithsonian National Museum of Natural History (NMNH). We examine MIDS scores for subsets of the collection and compare them to established, internal record quality scores from the Smithsonian's Collections and Digitization Reporting System (CDRS). Our goal is to determine how to best implement MIDS, while also reviewing potential updates to CDRS. MIDS scores can range from 0 (Bare) to 3 (Extended). Most records from the geology collections score 1 (Basic) or 2 (Intermediate). No records score above 2. Low scores largely reflect 1) a lack of detailed metadata for older specimens and 2) incomplete data from ongoing digitization projects. Certain subcollections have more complete data but recently acquired collections score similarly to older collections. CDRS scores are calculated in the collections database using discipline-specific rulesets. Like MIDS, CDRS assesses digitization progress, but it differs from MIDS in four key ways: 1) it includes elements for physical collections management, like storage location and accession status; 2) it excludes some properties that appear in MIDS; 3) it may include data quality checks, which were omitted from MIDS by design; and 4) inconsistent rulesets make comparisons between disciplines difficult. We expect MIDS to be most useful for improving the completeness of published datasets and allowing comparisons between organizations, whereas CDRS scores will better capture internal data quality and collections management concerns.

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