CIAO-WPS - Utilizing Semantic Web (Web 3.0) Techniques to Assist in the Automatic Orchestration of Geospatial Processes and Datasets
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Current geospatial datasets and web services are disparate, obscure and difficult to expose to the world. With the advent of geospatial processes utilizing temporal data and big data, along with datasets continually increasing in size, the problem of under-exposed datasets and web services is amplified. This paper proposes the integration of Semantic Web concepts and technologies into geospatial datasets and web services, making it possible to link these datasets and services via functionality, the inputs required and the outputs produced. To do so requires the extensive use of metadata to allow for a standardised form of description of their function. This research also visits the concept of using ontologies to store processes. A simple prototype termed CIAO-WPS (Chet’s Intelligent, Automatically-Orchestrated Web Processing Services) is created as a proof of concept, using the Python programming language. The prototype seeks to reinforce ideas in regards to pathing and cost constraints, as well as explore overlooked designs.
KeywordsSemantic Web Web 3.0 Ontologies Metadata Web Processing Services WPS CIAO-WPS
The work has been supported by the Cooperative Research Centre for Spatial Information, whose activities are funded by the Business Cooperative Research Centres Program. The work has been supported by the Cooperative Research Centre for Spatial Information, whose activities are funded by the Australian Commonwealth’s Cooperative Research Centres Programme.
- 1.ACIL Tasman: The Value of Spatial Information - the impact of modern spatial information technologies on the Australian economy. Technical report (2008). http://www.crcsi.com.au/assets/Resources/7d60411d-0ab9-45be-8d48-ef8dab5abd4a.pdf
- 7.Granell, C., Díaz, L., Tamayo, A., Huerta, J.: Assessment of OGC web processing services for REST principles. Int. J. Data Min. Model. Manage. 6(4), 391–412 (2012). (Special Issue on Spatial Information Modelling, Management and Mining)Google Scholar
- 11.Huhns, M.N., Singh, M.P.: Service-oriented computing: key concepts and principles service-oriented computing: key concepts and principles. IEEE Internet Comput. 9(1), 75–81 (2005). http://scholarcommons.sc.edu/csce_facpub, http://ieeexplore.ieee.org/servlet/opac?punumber=4236
- 12.Janowicz, K., Blomqvist, E.: The use of Semantic Web technologies for decision support - a survey. Semant. Web J. 5(3), 177–201 (2012)Google Scholar
- 14.Kauppinen, T., Mira De Espindola, G., Jones, J., Sánchez, A., Gräler, B., Bartoschek, T.: Linked Brazilian Amazon rainforest data. Semant. Web 5(2), 151–155 (2014)Google Scholar
- 18.Papazoglou, M., Georgakopoulos, D.: Introduction: service-oriented computing. Commun. ACM - Service-Oriented Comput. 46(10), 24–28 (2003)Google Scholar
- 21.World Wide Web Consortium: W3C Semantic Web FAQ (2001). http://www.w3.org/2001/sw/SW-FAQ
- 22.Wu, Z.: Service discovery. In: Service Computing - Concept, Method and Technology, Chap. 4, pp. 79–104 (2015)Google Scholar
- 23.Wu, Z.: Service-oriented architecture and web services. In: Service Computing - Concept, Method and Technology, Chap. 2, pp. 17–42 (2015)Google Scholar
- 24.Yu, L., Liu, Y.: Using linked data in a heterogeneous sensor web: challenges, experiments and lessons learned. Int. J. Digital Earth 8(1), 17–37 (2013). http://www.scopus.com/inward/record.url?eid=2-s2.0-84920191714&partnerID=tZOtx3y1 CrossRefGoogle Scholar