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OntoNanoMat: A Semantic Dataset and Ontology for Green-Synthesized Nanomaterials in Environmental Remediation

Author

Listed:
  • Carolina L. Recio-Colmenares

    (Departamento de Ciencias Básicas y Aplicadas, Centro Universitario de Tonalá, Universidad de Guadalajara, Guadalajara 44100, Mexico)

  • Roxana B. Recio-Colmenares

    (Departamento de Ciencias Básicas y Aplicadas, Centro Universitario de Tonalá, Universidad de Guadalajara, Guadalajara 44100, Mexico)

  • F. E. Castillo-Barrera

    (Facultad de Ingeniería, Universidad Autónoma de San Luís Potosí, San Luis Potosi 78000, Mexico)

  • Cesar A. Garcia-Garcia

    (Departamento de Ciencias de la Información y Desarrollos Tecnológicos, Centro Universitario de Tonalá, Universidad de Guadalajara, Guadalajara 44100, Mexico)

Abstract

Background: Research on green-synthesized nanomaterials (GSNs) for environmental remediation is growing rapidly, yet data remains fragmented in non-interoperable formats. Methods: We present OntoNanoMat, a comprehensive semantic resource consisting of a modular OWL 2 DL ontology and a curated dataset of two illustrative case studies serving as proof-of-concept demonstrations. The data was structured into five thematic modules: Identification, Synthesis, Mechanism, Performance, and Provenance. Results : The dataset is provided in three interoperable formats: CSV, JSON, and Turtle (RDF) and is validated through SHACL shapes to ensure structural integrity and FAIR compliance. Conclusions: OntoNanoMat provides a FAIR-compliant (Findable, Accessible, Interoperable, and Reusable) foundation for future machine learning applications and knowledge graph integration in sustainable nanotechnology.

Suggested Citation

  • Carolina L. Recio-Colmenares & Roxana B. Recio-Colmenares & F. E. Castillo-Barrera & Cesar A. Garcia-Garcia, 2026. "OntoNanoMat: A Semantic Dataset and Ontology for Green-Synthesized Nanomaterials in Environmental Remediation," Data, MDPI, vol. 11(4), pages 1-9, March.
    • Handle: RePEc:gam:jdataj:v:11:y:2026:i:4:p:71-:d:1910221
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