{
  "annotation_id": "ad05d3be-da64-46dd-a594-f818b02b5cfc",
  "date_created": "2026-02-17T05:53:11.552000Z",
  "date_modified": "2026-02-17T05:53:11.552000Z",
  "file_hash": "f6aae7a63b4c44449ac0e26aebf733d9f7eb5ff16471acc90492d0368dccf1bf",
  "private": false,
  "record": {
    "abstract": "Academic libraries struggle to find and access faculty expertise across disciplines. This research proposes a faculty expertise ontology with a hierarchical structure based on Prot\\\u0027eg\\\u0027e to enhance library services and knowledge organisation. The ontology classifies relationships between departments, subject areas, faculty members, and contact data into layers including Top, Middle, and Bottom levels. The academic structure that this tiered form takes enables discovery of expertise in departments. The ontology which answers competency questions generated from the subject matter experts can answer real-world questions like which faculties are in the specific areas, how to collaborate with other disciplines and search contact information and so on. Competency questions act as design and test instruments to show that the ontology will fulfil the information needs of Researchers, Librarians and Administrators. The ontology is able to cope with semantically-enhanced queries, as shown by SPARQL implementations. The model works effectively in initiating referrals to an expert, aligning research with the strength of a department and allowing academics to partner up. The ontology delivers a scalable platform that adapts to institutional change. In the future, we intend to integrate with institutional databases and library systems for automatic API updates, as well as develop user interfaces and visualisations.",
    "arxiv_id": "2601.07451",
    "authors": [
      "Snehasish Paul"
    ],
    "categories": [
      "cs.DL"
    ],
    "license": "http://creativecommons.org/licenses/by-sa/4.0/",
    "title": "Building Faculty Expertise Ontology using Protege: Enhancing Academic Library Research Services",
    "url": "https://arxiv.org/abs/2601.07451",
    "version": "v1"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "e5f30866-a498-40eb-b026-2b6f79c12165",
    "id": "arXiv Dataset",
    "type": "Model",
    "variant": "snapshot-2026-01-17",
    "version": "0.1.0"
  },
  "user_id": 1000002
}