| Y. Voutos, D. Sklavounos, Ph. Mylonas |
| A Standards-Aligned Semantic Infrastructure for Urban Air Quality Monitoring: Provenance-Aware Knowledge Graph Design for IoT Sensor Data |
| 11th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM 2026), Thessaloniki, Greece, September 18-20, 2026 |
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ABSTRACT
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| This paper presents a standards-aligned ontology for the Pune Smart City air-quality monitoring dataset. The ontology transforms 28-column flat CSV sensor records comprising 103,205 rows from ten monitoring stations during 1 May 2019 to 31 August 2019 into a knowledge graph grounded in SOSA/SSN, GeoSPARQL, OWL-Time and PROV-O. Its design models pollutant and ambient-condition measurements as observation resources with reusable measurement-interval results, preserves the dataset MIN/MAX polling-cycle semantics, represents monitoring stations as both sensor platforms and geospatial features and separates raw sensor records from derived Air Quality Index observations. Because the source data contain no pre-computed AQI field, AQI values are modeled as provenance-bearing derived entities generated by a CPCB AQI calculation activity. The ontology also captures data-quality annotations for missingness and completeness, station geometry and timestamps and validation constraints through SHACL node shapes and SPARQL-based rules. The resulting model supports interoperable environmental data integration, provenance-aware AQI computation, GeoSPARQL querying and reproducible semantic validation for urban airquality analytics.
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| 18 September, 2026 |
| Y. Voutos, D. Sklavounos, Ph. Mylonas, "A Standards-Aligned Semantic Infrastructure for Urban Air Quality Monitoring: Provenance-Aware Knowledge Graph Design for IoT Sensor Data", 11th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM 2026), Thessaloniki, Greece, September 18-20, 2026 |
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