Vlad Tanasescu

IRS-III: A broker-based approach to semantic Web services

A factor limiting the take up of Web services is that all tasks associated with the creation of an application, for example, finding, composing, and resolving mismatches between Web services have to be carried out by a software developer. Semantic Web services is a combination of semantic Web and Web service technologies that promise to alleviate these problems. In this paper we describe IRS-III, a framework for creating and executing semantic Web services, which takes a semantic broker-based approach to mediating between service requesters and service providers. We describe the overall approach and the components of IRS-III from an ontological and architectural viewpoint. We then illustrate our approach through an application in the eGovernment domain.

IRS-III: a broker for semantic web services based applications

In this paper we describe IRS-III which takes a semantic broker based approach to creating applications from Semantic Web Services by mediating between a service requester and one or more service providers. Business organisations can view Semantic Web Services as the basic mechanism for integrating data and processes across applications on the Web. This paper extends previous publications on IRS by providing an overall description of our framework from the point of view of application development. More specifically, we describe the IRS-III methodology for building applications using Semantic Web Services and illustrate our approach through a use case on e-government.

Deploying semantic web services-based applications in the e-government domain

Joining up services in e-Government usually implies governmental agencies acting in concert without a central control regime. This requires to the sharing scattered and heterogeneous data. Semantic Web Service (SWS) technology can help to integrate, mediate and reason between these datasets. However, since a few real-world applications have been developed, it is still unclear which are the actual benefits and issues of adopting such a technology in the e-Government domain. In this paper, we contribute to raising awareness of the potential benefits in the e-Government community by analyzing motivations, requirements and expected results, before proposing a reusable SWS-based framework. We demonstrate the application of this framework by showing how integration and interoperability emerge from this model through a cooperative and multi-viewpoint methodology. Finally, we illustrate added values and lessons learned by two compelling case studies: a change of circumstances notification system and a GIS-based emergency planning system, and describe key challenges which remain to be addressed.

Geospatial Data Integration with Semantic Web Services: The eMerges Approach

Geographic space still lacks the semantics allowing a unified view of spatial data. Indeed, as a unique but all encompassing domain, it presents specificities that geospatial applications are still unable to handle. Moreover, to be useful, new spatial applications need to match human cognitive abilities of spatial representation and reasoning. In this context, eMerges, an approach to geospatial data integration based on Semantic Web Services (SWS), allows the unified representation and manipulation of heterogeneous spatial data sources. eMerges provides this integration by mediating legacy spatial data sources to high-level spatial ontologies through SWS and by presenting for each object context dependent affordances. This generic approach is applied here in the context of an emergency management use case developed in collaboration with emergency planners of public agencies.

Spatial semantics in difference spaces

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 GIScientists 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.

Service Selection via Extreme Geotagging

Location of services plays an important role in the process of service selection. Geotagging emerged as a technique for attaching location information to Web elements, including Web services. In this context, this paper proposes a Web service selection framework based on geotagging. First, we introduce tagging and geotagging as an operation that emphasizes processes and the dynamic aspects of the environment. Then, we propose a conceptual model that defines a set of relations between tags. Furthermore, we develop a service selection technique based on this model and give an example of service selection. An overview of a system that implements geotagging-based service selection is presented at the end.