Geospatial Web Services Discovery through Semantic Annotation of WPS

Abstract

This paper presents an approach to GWS (GeospatialWeb Service) discovery through the semantic annotation of WPS (Web Processing Service) service descriptions. The rationale behind this work is that search engines that use appropriate semantic-based similarity measures in the matching process are more accurate in terms of precision and recall than those based on syntactic matching alone. The lack of semantics in the description of services using a standard such as WPS prevents the use of such a matching process and is considered a limitation of GWS discovery. The GWS discovery approach presented is based on the consideration of semantics in the service description method and in the matching process. The description of services is based on a semantic lightweight meta-model instantiated in the WPS 2.0 standard, extending the description of the service through metadata tags. The matching process is performed in three steps (functionality matching step, I/O (Input/Output) matching step and non-functional matching step). Its core is a semantic similarity measure that combines logical and non-logical matching methods. Finally, the paper presents the results of an experiment applying the proposed discovery approach on a GWS corpus, showing promising results and the added value of the three-step matching process.

Search Engine for Open Geospatial Consortium Web Services Improving Discoverability through Natural Language Processing-Based Processing and Ranking

“…Dissimilar to other works [7,8] that focus on the development of a web crawler to discover data on the web, our paper focuses mainly on the semantic augmentation through Natural Language Processing and ranking methods to improve the search results presented to the user. This thematic has been marginally explored in other works, which focus on the generation of web ontologies [9][10][11] or the exploitation of such ontologies to describe and categorize web services [12]. However, all of these approaches rely on models to parse information from well-structured fields retrieved with GetCapabilites.…”