We just finished a substantially extended and rewritten version of the poster accepted for EuroSSC 2009 (update: the paper was accepted, see below):

Abstract Building on abstract reference models, the Open Geospatial Consortium (OGC) has established standards for storing, discovering, and processing geographical information. These standards act as basis for the implementation of specific services and Spatial Data Infrastructures (SDI). Research on geo-semantics plays an increasing role to support complex queries and retrieval across heterogeneous information sources, as well as for service orchestration, semantic translation, and on-the-fly integration. So fa r, this research targets individual solutions or focuses on the Semantic Web, leaving the integration into SDI aside. What is missing is a shared and transparent semantic enablement layer for Spatial Data Infrastructures which also integrates reasoning services known from the Semantic Web. Focusing on Sensor Web Enablement (SWE) we outline how Spatial Data Infrastructures in general can benefit from such a semantic enablement layer. Instead of developing new semantically enabled services from scratch, we propose to create profiles of existing services that implement a transparent mapping between the OGC and the Semantic Web world.

Janowicz, K. Schade, S., Bröring, A., Keßler, C., and Stasch, C. (2009; forthcomming): A Transparent Semantic Enablement Layer for the Geospatial Web. Terra Cognita 2009 Workshop In conjunction with the 8th International Semantic Web Conference (ISWC 2009), October 26, 2009.

Abstract. While semantic similarity plays a crucial role for human categorization and reasoning, computational similarity measures have also been applied to fields such as semantics-based information retrieval or ontology engineering. Several measures have been developed to compare concepts specified in various description logics. In most cases, these measures are either structural or require a populated ontology. Structural measures fail with an increasing expressivity of the used description logic, while several ontologies, e.g., geographic feature type ontologies, are not populated at all. In this paper, we present an approach to reduce inter-concept to inter-instance similarity and thereby avoid the canonization problem of structural measures. The novel approach, called SIM-DL_A, reuses existing similarity functions such as co-occurrence or network measures from our previous SIM-DL measure. The required instances for comparison are derived from the completion tree of a slightly modified DL-tableau algorithm as used for satisfiability checking. Instead of trying to find one (clash-free) model, the new algorithm generates a set of proxy individuals used for comparison. The paper presents the algorithm, alignment matrix, and similarity functions as well as a detailed example.

Janowicz, K. and Wilkes, M. (2009; forthcoming): SIM-DL_A: A Novel Semantic Similarity Measure for Description Logics Reducing Inter-Concept to Inter-Instance Similarity. The 6th Annual European Semantic Web Conference (ESWC2009). Lecture Notes in Computer Science 5554, Springer. pp. 353-367, 2009.