The analogy of Semantic Reference Systems proposed in (Kuhn in press) is being explored here with respect to the computational mechanisms it suggests. Semantic referencing, grounding in a semantic datum, semantic projection, and semantic transformation are defined and demonstrated through an implementation of a semantic reference system for a simple vehicle navigation model. The idea of wrapping legacy data or services is shown to correspond to semantic referencing, which suggests a straightforward procedure to derive wrappers from semantic reference systems. 1.

The construction of natural language interfaces to computers continues to be a major challenge. The need for such interfaces is growing now that speech recognition technology is becoming more readily available, and people cannot speak those computer-oriented formal languages that are frequently used to interact with computer applications. Much of the research related to the design and implementation of natural language interfaces has involved the use of high-level declarative programming languages. This is to be expected as the task is extremely difficult, involving syntactic and semantic analysis of potentially ambiguous input. The use of LISP and Prolog in this area is well documented. However, research involving the relatively new lazy functional programming paradigm is less well known. This paper provides a comprehensive survey of that research.

Abstract. What prevents the Geospatial Semantic Web from taking off is not a missing architecture and protocol stack but, beside other aspects, the question of how Web services can be semi-automatically discovered and whether and to what degree they satisfy user requirements. Two approaches turned out to be useful for semanticenabled geospatial information retrieval: subsumption reasoning and similarity measurement. However, while the former one can be applied to query service ontologies described in OWL-S or WSMO/WSML, most existing similarity theories are not able to cope with logic-based service descriptions. This chapter presents initial results on developing a directed and context-aware similarity measure that compares WSML concept descriptions for overlap and therefore supports retrieval within the upcoming Geospatial Semantic Web. 1

Abstract. Sharing information through the web is a practice that many organizations and users do daily. This generates a need of methodologies and tools for semantic integrating the obtained information. With the GIS community the scenario is not different, but the needs are a little different because of the particularities of the geographic data. In this paper we present G-Match, an algorithm and implementation for integration of geographic ontologies. Our proposal combines some mathematical foundations and existing technologies in order to achieve expressive results. Resumo. O compartilhamento de informações através da web é uma prática utilizada diariamente por pessoas e organizações. Esta prática gera uma necessidade por metodologias e ferramentas que façam a integração semântica das informações obtidas. Na comunidade de SIG o cenário não é diferente, com o agravante das particularidades inerentes aos dados geográficos. Neste artigo nós apresentamos o G-Match, um algoritmo e implementação para a integração de ontologias geográficas. Nossa proposta combina alguns aspectos matemáticos com tecnologias existentes com o objetivo de alcançar resultados expressivos. 1.

Abstract. Matching descriptions of user requirements against descriptions of service capabilities is crucial for the discovery of appropriate services for a given task. To improve the precision of approaches that consider only syntactical aspects of matchmaking (e.g. UDDI) several approaches for semantic matchmaking have been proposed. We compare two approaches with respect to their potentials for matchmaking between semantic descriptions of geoinformation services. The State-based Approach uses the Web Ontology Language and the Rule Markup Language to describe inputs, outputs, preconditions and effects. In the Algebraic Approach, abstract data types are specified to capture domain knowledge. The specific data types used in a service model referred to these shared concepts. In order to make the specifications executable and to enable matchmaking a functional programming language (Haskell) is used in this approach. For a scenario from the domain of disaster management, both approaches are tested for one specific type of match. 1

The construction of natural-language interfaces to computers continues to be a major challenge. The need for such interfaces is growing now that speech-recognition technology is becoming morereadily available, and people cannot speak those computer-oriented formal languages that are frequently used to interact with computer applications. Much of the research related to the design and implementation of natural-language interfaces has involved the use of high-level declarative programming languages. This is to be expected as the task is extremely difficult, involving syntactic and semantic analysis of potentially-ambiguous input. The use of LISP and Prolog in this area is well documented. However, research involving the relatively-new lazy functional-programming paradigm is less well known. This paper provides a comprehensive survey of that research.

Abstract. Higher level semantics are considered useful in the geospatial domain, yet there is no general consensus on the form these semantics should take. Indeed, knowledge representation paradigms such as classification based ontologies do not always pay tribute to the complexity of geospatial semantics. Other approaches, originating from psychology, linguistics, philosophy or cognitive sciences are regularly investigated to enrich the GIScientist’s representational toolbox. However, each of these techniques is often used to the exclusion of others, creating new representational difficulties, or merely as a useful addendum to host theories with which they only superficially integrate. The present work is an attempt to introduce a common ground to these techniques by reducing them to the notion of differences or difference spaces. Differences are discernible properties of the environment, detected or produced by a computational process. I describe the following semantic frameworks: category-based ontologies, conceptual spaces, affordance based models, image schemata, and multi representation, explaining how each of them can be projected to a model based on differences. Illustrative examples from table top and geographic space are produced in order to show the model in use. 1

A method to map heterogeneity between near but non-equivalent semantic attributes in multiple health data registries

Abstract. We introduce ontological blending as a method for combining ontologies. Compared with existing combination techniques that aim at integrating or assimilating categories and relations of thematically related ontologies, blending aims at creatively generating (new) categories and ontological definitions; this is done on the basis of input ontologies whose domains are thematically distinct but whose specifications share structural or logical properties. As a result, ontological blending can generate new ontologies and concepts and it allows a more flexible technique for ontology combination compared to existing methods. Our approach to computational creativity in conceptual blending is inspired by methods rooted in cognitive science (e.g., analogical reasoning), ontological engineering, and algebraic specification. Specifically, we introduce the basic formal definitions for ontological blending, and show how the distributed ontology language DOL (currently being standardised within the OntoIOp—Ontology Integration and Interoperability—activity of ISO/TC 37/SC 3) can be used to declaratively specify blending diagrams. 1