Identifier Persistence and Version Consistency in the OSPAR Offshore Installations Inventory, 2001–2023
Longitudinal analyses of administrative infrastructure inventories depend on stable entity identifiers. This study audits identifier persistence and version consistency across selected historical OSPAR Offshore Installations Inventories from 2001 to 2023. The analysis combines snapshot-level identifier audits, literal identifier overlap, a conservative country–name crosswalk, syntax normalization, an identifier-reuse diagnostic and coordinate-based plausibility checks. The results show episodic rather than continuous instability. No 2001 identifier recurs unchanged in 2003 among unambiguous matched records. A second major break occurs from 2005 to 2007, when 676 of 1,098 unambiguous country–name matches receive different identifiers. The 2009–2011 transition shows a strongly Norway-specific discontinuity: 218 of 219 unambiguous Norwegian matches change identifier. Critically, 99.3% of the 2009 ID values recur somewhere in 2011, yet 437 of 1,331 overlapping unique IDs are attached to a different normalized country–name record. This shows that set-level ID overlap can mask reassignment. A long-range 2013–2023 check distinguishes syntactic from substantive change: 576 of 1,002 literal identifier differences are formatting-only, while 426 are substantive renumberings. The 2023 snapshot also contains repeated identifier values, most notably NO0. The study demonstrates that within-snapshot uniqueness, identifier-set overlap, syntactic consistency and longitudinal entity persistence are distinct properties. Reproducible longitudinal use of the OSPAR inventory therefore requires version-aware normalization and explicit entity reconciliation rather than direct joins on the published ID field.
Authors
- Stephan Graf Mueller (ORCID: https://orcid.org/0009-0000-8167-3079)
Institutions
- Versitech (United States) (US)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-09-18
- DOI
- https://doi.org/10.5281/zenodo.22829554
- Primary Topic
- Data Quality and Management
- Type
- preprint