Eva Klien

Ontology‐based retrieval of geographic information

Discovering and accessing suitable geographic information (GI) in the open and distributed environments of current Spatial Data Infrastructures (SDIs) is a crucial task. Catalogues provide searchable repositories of information descriptions, but the mechanisms to support GI retrieval are still insufficient. Problems of semantic heterogeneity caused by the ambiguity of natural language can arise during keyword‐based search in catalogues and when formulating a query to access the discovered data. In this paper, we present an approach to ontology‐based GI retrieval that contributes to solving existing problems of semantic heterogeneity and hides most of the complexity of the required procedure from the requester. A query language and graphical user interface allow a requester to intuitively formulate a query using a well‐known domain vocabulary. From this query, an ontology concept is derived, which is then used to search a catalogue for a data source that provides all the information required to answer the requesters query. If a suitable data source is discovered, the relevant data are accessed through a standardized interface. The approach is implemented through several components that can be used as an extension to standard SDIs.

Ontology-based discovery of geographic information services- : An application in disaster management

Finding suitable information in the open and distributed environment of current geographic information web services is a crucial task. Service brokers (or catalogue services) provide searchable repositories of service descriptions but the mechanisms to support the task of service discovery are still insufficient. One of the main challenges is to overcome semantic heterogeneity caused by synonyms and homonyms during keyword-based search in catalogues. This paper presents a practical case study to what extent ontology-based service discovery can solve these semantic heterogeneity problems. To this end, we apply the Bremen University Semantic Translator for Enhanced Retrieval as a service broker. The approach combines ontology-based metadata with an ontology-based search. Based on a scenario of finding geographic information services for estimating potential storm damage in forests, it is shown that through terminological reasoning the request finds an appropriate match in a service on storm hazard classes. However, the approach reveals some limitations in the context of geographic web service discovery, which are discussed at the end.

Overcoming semantic heterogeneity in spatial data infrastructures

In current spatial data infrastructures (SDIs), it is still often difficult to effectively exchange or re-use geographic data sets. A main reason for this is semantic heterogeneity, which occurs at different levels: at the metadata, the schema and the data content level. It is the goal of the work presented in this paper to overcome the problems caused by semantic heterogeneity on all three levels. We present a method based on ontologies and logical reasoning, which enhances the discovery, retrieval, interpretation and integration of geographic data in SDIs. Its benefits and practical use are illustrated with examples from the domains of geology and hydrology.

The role of spatial relations in automating the semantic annotation of geodata

How can the usability of distributed and heterogeneous geographic data sets be enhanced? Semantic interoperability is a prerequisite for effectively finding and accessing relevant data in different application contexts. By using geospatial domain ontologies and semantic annotations of geodata based on these ontologies semantic interoperability can be achieved. However, since no automated methods for the semantic annotation of geodata exist this remains a laborious task, which data providers are neither willing nor capable to perform. In this paper we propose a method for automating the annotation process based on spatial relations. At the domain level, spatial relations play an important role for defining and identifying geospatial concepts. At the data level, spatial relations may be expressed through spatial processing methods, as we can calculate relations like topology, direction or distance between two spatial entities. We show how this potential can be exploited for automating the semantic annotation of geodata. The approach is illustrated by introducing a case study for annotating data containing representations of floodplains.

A Rule-Based Strategy for the Semantic Annotation of Geodata

The ability to represent geospatial semantics is of great importance when building geospatial applications for the Web. This ability will enhance discovery, retrieval and translation of geographic information as well as the reuse of geographic information in different contexts. The problem of generating semantic annotations has been recognized as one of the most serious obstacles for realizing the Geospatial Semantic Web vision. We present a rule-based strategy for the semantic annotation of geodata that combines Semantic Web and Geospatial Web Services technology. In our approach, rules are employed to partially automate the annotation process. Rules define conditions for identifying geospatial concepts. Based on these rules, spatial analysis procedures are implemented that allow for inferring whether or not a feature in a dataset represents an instance of a geospatial concept. This automated evaluation of features in the dataset generates valuable information for the creation and refinement of semantic annotations on the concept level. The approach is illustrated by a case study on annotating data sources containing representations of lowlands. The presented strategy lays the foundations for the specification of a semantic annotation tool for geospatial web services that supports data providers in annotating their sources according to multiple domain views.

Functional description of geoprocessing services as conjunctive datalog queries

Discovery of suitable web services is a crucial task in Spatial Data Infrastructures (SDI). In this work, we develop a novel approach to the discovery of geoprocessing services (WPS). Discovery requests and Web Processing Services are annotated as conjunctive queries in a logic programming (LP) language and the discovery process is based on Logic Programming query containment checking between these descriptions. Besides the types of input and output, we explicitly formalise the relation between them and hence are able to capture the functionality of a WPS more precisely. The use of Logic Programming query containment allows for effective reasoning during discovery. Furthermore, the relative simplicity of the semantic descriptions is advantageous for their creation by non-logics experts. The developed approach is applicable in the Web Service Modeling Framework (WSMF), a state-of-the-art semantic web service framework.

Using Term-Matching Algorithms for the Annotation of Geo-services

This paper presents an approach to automating semantic annotation within service-oriented architectures that provide interfaces to databases of spatialinformation objects. The automation of the annotation process facilitates the transition from the current state-of-the-art architectures towards semantically-enabled architectures. We see the annotation process as the task of matching an arbitrary word or term with the most appropriate concept in the domain ontology. The term matching techniques that we present are based on text mining. To determine the similarity between two terms, we first associate a set of documents [that we obtain from a Web search engine] with each term. We then transform the documents into feature vectors and thus transition the similarity assessment into the feature space. After that, we compute the similarity by training a classifier to distinguish between ontology concepts. Apart from text mining approaches, we also present an alternative technique, namely Google Distance, which proves less suitable for our task. The paper also presents the results of an extensive evaluation of the presented term matching methodswhich shows that these methodswork best on synonymous nouns from a specific vocabulary. Furthermore, the fast and simple centroid-based classifier is shown to perform very well for this task. The main contribution of this paper is thus in proposing a term matching algorithm based on text mining and information retrieval. Furthermore, the presented evaluation should give a notion of how the algorithm performs in various scenarios.

SWING: an integrated environment for geospatial semantic web services

Geospatial Web services allow to access and to process Geospatial data. Despite significant standardisation efforts, severe heterogeneity and interoperability problems remain. The SWING environment leverages the Semantic Web Services (SWS) paradigm to address these problems. The environment supports the entire life-cycle of Geospatial SWS. To this end, it integrates a genuine end-user tool, a tool for developers of new Geospatial Web services, a commercial service Catalogue, the Web Service Execution Environment platform (WSMX), as well as an annotation tool. The demonstration includes three usage scenarios of increasing complexity, involving the semantic annotation of a legacy service, the semantic discovery of a Geospatial SWS, as well as the composition of a new Geospatial SWS.