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Du, Heshan; Dimitrova, Vania; Magee, Derek; Stirling, Ross; Curioni, Giulio; Reeves, Helen; Clarke, Barry; Cohn, Anthony (2016)
Publisher: Springer
Languages: English
Types: Unknown
Assessing the Underworld (ATU) is a large interdisciplinary UK research project, which addresses challenges in integrated inter-asset maintenance. As assets on the surface of the ground (e.g. roads or pavements) and those buried under it (e.g. pipes and cables) are supported by the ground, the properties and processes of soil affect the performance of these assets to a significant degree. In order to make integrated decisions, it is necessary to combine the knowledge and expertise in multiple areas, such as roads, soil, buried assets, sensing, etc. This requires an underpinning knowledge model, in the form of an ontology. Within this context, we present a new ontology for describing soil properties (e.g. soil strength) and processes (e.g. soil compaction), as well as how they affect each other. This ontology can be used to express how the ground affects and is affected by assets buried under the ground or on the ground surface. The ontology is written in OWL 2 and openly available from the University of Leeds data repository: http://​doi.​org/​10.​5518/​54.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • 1. Eionet GEMET Thesaurus. http://www.eionet.europa.eu/gemet, 2015.
    • 2. AGROVOC Multilingual agricultural thesaurus. http://aims.fao.org/standards/agrovoc, 2016.
    • 3. Cambridge Dictionaries Online. http://dictionary.cambridge.org, 2016.
    • 4. Oxford Dictionaries. http://www.oxforddictionaries.com, 2016.
    • 5. SWEET: Semantic Web for Earth and Environmental Terminology. https://sweet.jpl.nasa.gov, 2016.
    • 6. F. Baader, D. Calvanese, D. L. McGuinness, D. Nardi, and P. F. Patel-Schneider, editors. The Description Logic Handbook. Cambridge University Press, 2007.
    • 7. P. L. Buttigieg, N. Morrison, B. Smith, C. J. Mungall, and S. E. Lewis. The environment ontology: contextualising biological and biomedical entities. Journal of Biomedical Semantics, 4:43, 2013.
    • 8. C. Deb, S. Marwaha, P. Malhotra, S. Wahi, and R. Pandey. Strengthening soil taxonomy ontology software for description and classification of USDA soil taxonomy up to soil series. In Proceedings of the 2nd International Conference on Computing for Sustainable Global Development, pages 1180-1184, 2015.
    • 9. A. dos Santos Apar´ıcio, O. L. M. de Farias, and N. dos Santos. Integration of Heterogeneous Databases and Ontologies. Cadernos do IME-S´erie Informa´tica, 21:4-10, 2006.
    • 10. H. Du and A. Cohn. A Tutorial of Viewing and Querying the Ontology of Soil Properties and Processes. Technical report, University of Leeds, 2016.
    • 11. H. Du and A. Cohn. An Ontology of Soil Properties and Processes. University of Leeds. [Dataset]. http://doi.org/10.5518/54, 2016.
    • 12. T. Heeptaisong and A. Shivihok. Soil Knowledge-based Systems Using Ontology. In Proceedings of the International MultiConference of Engineers and Computer Scientists, pages 1-5, 2012.
    • 13. M. Horridge. Justification Based Explanation in Ontologies. PhD thesis, University of Manchester, 2011.
    • 14. M. Horridge and P. F. Patel-Schneider. OWL 2 Web Ontology Language Manchester Syntax. https://www.w3.org/TR/owl2-manchester-syntax, 2012.
    • 15. J. Knappett and R. Craig. Craig's Soil Mechanics. CRC Press, 2012.
    • 16. R. Lal and M. K. Shukla. Principles of Soil Physics. CRC Press, 2004.
    • 17. R. G. Raskin and M. J. Pan. Knowledge representation in the semantic web for Earth and environmental terminology (SWEET). Computers & Geosciences, 31(9):1119-1125, 2005.
    • 18. P. Shivananda and P. S. Kumar. Building Rules Based Soil Classification Ontology. International Journal of Computer Science and Information Technology & Security, 3(2), 2013.
    • 19. M. C. Su´arez-Figueroa, A. Go´mez-P´erez, and M. Ferna´ndez-Lo´pez. The NeOn Methodology for Ontology Engineering. In Ontology Engineering in a Networked World, pages 9-34. 2012.
    • 20. M. Zhao, Q. Zhao, D. Tian, P. Qian, and X. Zhang. Ontology-based intelligent retrieval system for soil knowledge. WSEAS Transactions on Information Science and Applications, 6(7):1196-1205, 2009.
  • Inferred research data

    The results below are discovered through our pilot algorithms. Let us know how we are doing!

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