Abstract—Semantic similarity measurement gained attention over the last years as a non-standard inference service for various kinds of knowledge representations including description logics. Most existing similarity measures compute an undirected overall similarity, i.e., they do not take the context of the similarity query into account. If they do, the notion of context is usually reduced to the selection of particular concepts for comparison (instead of comparing all concepts within an examined ontology). The importance of context in deriving meaningful similarity judgments is beyond question and has been examined within recent research. This paper argues that there are several kinds of contexts. Each of them has its own impact on the resulting similarity values, but also on their interpretation. To support this view, the paper introduces definitions for the examined contexts and illustrates their influence by example. I.

Abstract. The goal of the Sensor Web Enablement (SWE) initiative of the Open Geospatial Consortium (OGC) is the definition of web service interfaces and data encodings to make sensors discoverable, taskable and accessible on the World Wide Web. The SWE specifications enable a standardized communication and interaction with arbitrary types of sensors and sensor systems. The central concepts within OGC’s Sensor Web architecture are sensors, observations and features of interest. Sensors and their observations can be registered and stored through the Sensor Observation Service (SOS) to make them accessible for clients. So far, mechanisms are missing which support a semantic matching between features of interest stored in a database and referred to by an observation. The same applies for the matching between observations as sensor outputs and the properties of the features of interest. By taking a use case from disaster management, we outline the challenges and demonstrate how semantically annotated SWE data models and service interfaces support semantic matching. The result is a roadmap towards a semantically enabled sensor plug & play within the Sensor Web. 1

Gazetteers are key components of georeferenced information systems, including applications such as Web-based mapping services. Existing gazetteers lack the capabilities to fully integrate user-contributed and vernacular geographic information, as well as to support complex queries. To address these issues, a next generation gazetteer should leverage formal semantics, harvesting of implicit geographic information – such as geotagged photos – as well as models of trust for contributors. In this paper, we discuss these requirements in detail. We elucidate how existing standards can be integrated to realize a gazetteer infrastructure allowing for bottom-up contribution as well as information exchange between different gazetteers. We show how to ensure the quality of user-contributed information and demonstrate how to improve querying and navigation using semantics-based information retrieval.

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 interconcept to inter-instance similarity and thereby avoid the canonization problem of structural measures. The novel approach, called SIM-DLA, 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. 1

janowicz|patrick.maue|marc.wilkes|sven.schade|franca.scherer|m.braun|soeren.dupke|kuhn

The workshop on The Cultural Heritage of Historic European Cities and Public Participatory GIS aims at outlining the challenges to develop a ppGIS which can integrate data from different ages, authorities, and formats. This data ranges from archival catalogs, maps, photographs, film, aural archives over archaeological data to interpretative studies. With respect to spatial resolution, data should be available down to the level of single streets or even specific properties. Instead of a static approach, users should also be able to contribute new data to the system. This raises a couple of questions which are also relevant in a broader context, namely the ontological representation of and reasoning about geographic places. This paper introduces the challenges of modeling places in such a heterogeneous setting, outlines steps towards a three layered solution on how to represent, reference, and reason about geographic places, and finally sketches how to deal with inconsistent and contradictory knowledge.

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 far, 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. 1

Abstract. Reasoning about geographic features and feature types is a central functionality of spatial information retrieval and decision support systems. Measures of semantic similarity are such reasoning services which try to improve information retrieval by proposing similar features or types to a user’s query. A major challenge for similarity theories is the alignment process, i.e., how to determine which characteristics describing features or their types are compared. Most theories disregard the internal structure of features and types, i.e., the spatio-temporal sequence of their characteristics, and simply assume that they can be modeled as unstructured bags of characteristics. In this paper, we demonstrate how to account for the spatial sequence of characteristics without the need to alter the similarity measures as such. To demonstrate our approach, a climbing route recommendation portal is introduced which proposes similar climbing routes based on the user’s preferred routes. 1

Abstract. The Sensor Web provides access to observations and measurements through standardized interfaces defined by the Open Geospatial Consortium’s Sensor Web Enablement (SWE) initiative. While clients compliant to these standards have access to the generated sensor data, it remains partially hidden from other knowledge infrastructures building on higher-level W3C standards. To overcome this problem, it has been proposed to make sensor data accessible using Linked Data principles and RESTful services. This position paper discusses the embedding of such data into the Linked Data cloud with a focus on the outgoing links that hook them up with other data sources. We outline how such links can be generated in a semi-automatic way, and argue why curation of the links is required. Finally, we point to the query potential of such an additional interface to observation data, and outline the requirements for SPARQL endpoints. 1

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 far, 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. 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. Finally, we point out how to combine SDI with linked data. 1