{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T22:58:26Z","timestamp":1772837906255,"version":"3.50.1"},"reference-count":74,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2025,9,8]],"date-time":"2025-09-08T00:00:00Z","timestamp":1757289600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computers"],"abstract":"<jats:p>The digitisation of law-enforcement archives is examined with the aim of moving from static analogue records to interoperable semantic information systems. A step-by-step framework for optimal digitisation is proposed, grounded in archival best practice and enriched with artificial-intelligence and semantic-web technologies. Emphasis is placed on semantic data representation, which renders information actionable, searchable, interlinked, and automatically processed. As a proof of concept, a large language model\u2014OpenAI ChatGPT, version o3\u2014was applied to a corpus of narrative police reports, extracting and classifying key entities (metadata, persons, addresses, vehicles, incidents, fingerprints, and inter-entity relationships). The output was converted to Resource Description Framework triples and ingested into a triplestore, demonstrating how unstructured text can be transformed into machine-readable, interoperable data with minimal human intervention. The approach\u2019s challenges\u2014technical complexity, data quality assurance, information-security requirements, and staff training\u2014are analysed alongside the opportunities it affords, such as accelerated access to records, cross-agency interoperability, and advanced analytics for investigative and strategic decision-making. Combining systematic digitisation, AI-driven data extraction, and rigorous semantic modelling ultimately delivers a fully interoperable information environment for law-enforcement agencies, enhancing efficiency, transparency, and evidentiary integrity.<\/jats:p>","DOI":"10.3390\/computers14090376","type":"journal-article","created":{"date-parts":[[2025,9,9]],"date-time":"2025-09-09T12:15:17Z","timestamp":1757420117000},"page":"376","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Interoperable Semantic Systems in Public Administration: AI-Driven Data Mining from Law-Enforcement Reports"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5056-1952","authenticated-orcid":false,"given":"Alexandros Z.","family":"Spyropoulos","sequence":"first","affiliation":[{"name":"Department of Physics, School of Science, Kavala\u2019s Campus, Democritus University of Thrace (DUTH), 65404 Kavala, Greece"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6317-4284","authenticated-orcid":false,"given":"Vassilis","family":"Tsiantos","sequence":"additional","affiliation":[{"name":"Department of Physics, School of Science, Kavala\u2019s Campus, Democritus University of Thrace (DUTH), 65404 Kavala, Greece"}]}],"member":"1968","published-online":{"date-parts":[[2025,9,8]]},"reference":[{"key":"ref_1","first-page":"133","article-title":"A Semantic Model for Enterprise Digital Transformation Analysis","volume":"63","author":"Wang","year":"2023","journal-title":"J. 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