Detecting Ontological Conflicts in Protocols between Semantic Web Services

The task of verifying the compatibility between interacting web services has traditionally been limited to checking the compatibility of the interaction protocol in terms of message sequences and the type of data being exchanged. Since web services are developed largely in an uncoordinated way, different services often use independently developed ontologies for the same domain instead of adhering to a single ontology as standard. In this work we investigate the approaches that can be taken by the server to verify the possibility to reach a state with semantically inconsistent results during the execution of a protocol with a client, if the client ontology is published. Often database is used to store the actual data along with the ontologies instead of storing the actual data as a part of the ontology description. It is important to observe that at the current state of the database the semantic conflict state may not be reached even if the verification done by the server indicates the possibility of reaching a conflict state. A relational algebra based decision procedure is also developed to incorporate the current state of the client and the server databases in the overall verification procedure

Enriching Ontologies with Multilingual Information

Multilinguality in ontologies has become an impending need for institutions worldwide that have to deal with data and linguistic resources in different natural languages. Since most ontologies are developed in one language, obtaining multilingual ontologies implies to localize or adapt them to a concrete language and culture community. As the adaptation of the ontology conceptualization demands considerable efforts, we propose to modify the ontology terminological layer by associating an external repository of linguistic data to the ontology. With this aim we provide a model called Linguistic Information Repository (LIR) that associated to the ontology meta-model allows terminological layer localization

Issues in the Design of a Pilot Concept-Based Query Interface for the Neuroinformatics Information Framework

This paper describes a pilot query interface that has been constructed to help us explore a "concept-based" approach for searching the Neuroscience Information Framework (NIF). The query interface is concept-based in the sense that the search terms submitted through the interface are selected from a standardized vocabulary of terms (concepts) that are structured in the form of an ontology. The NIF contains three primary resources: the NIF Resource Registry, the NIF Document Archive, and the NIF Database Mediator. These NIF resources are very different in their nature and therefore pose challenges when designing a single interface from which searches can be automatically launched against all three resources simultaneously. The paper first discusses briefly several background issues involving the use of standardized biomedical vocabularies in biomedical information retrieval, and then presents a detailed example that illustrates how the pilot concept-based query interface operates. The paper concludes by discussing certain lessons learned in the development of the current version of the interface

Towards automated knowledge-based mapping between individual conceptualisations to empower personalisation of Geospatial Semantic Web

Geospatial domain is characterised by vagueness, especially in the semantic disambiguation of the concepts in the domain, which makes defining universally accepted geo- ontology an onerous task. This is compounded by the lack of appropriate methods and techniques where the individual semantic conceptualisations can be captured and compared to each other. With multiple user conceptualisations, efforts towards a reliable Geospatial Semantic Web, therefore, require personalisation where user diversity can be incorporated. The work presented in this paper is part of our ongoing research on applying commonsense reasoning to elicit and maintain models that represent users' conceptualisations. Such user models will enable taking into account the users' perspective of the real world and will empower personalisation algorithms for the Semantic Web. Intelligent information processing over the Semantic Web can be achieved if different conceptualisations can be integrated in a semantic environment and mismatches between different conceptualisations can be outlined. In this paper, a formal approach for detecting mismatches between a user's and an expert's conceptual model is outlined. The formalisation is used as the basis to develop algorithms to compare models defined in OWL. The algorithms are illustrated in a geographical domain using concepts from the SPACE ontology developed as part of the SWEET suite of ontologies for the Semantic Web by NASA, and are evaluated by comparing test cases of possible user misconceptions

Gap analysis of ontology mapping tools and techniques

Mapping between ontologies provides a way to overcome any dissimilarities in the terminologies used in two ontologies. Some tools and techniques to map ontologies are available with some semi-automatic mapping capabilities. These tools are employed to join the similar concepts in two ontologies and overcome the possible mismatches.Several types of mismatches have been identified by researchers and certain overlaps can easily be seen in their description. Analysis of the mapping tools and techniques through a mismatches framework reveals that most of the tools and techniques just target the explication side of the concepts in ontologies and a very few of them opt for the conceptualization mismatches. Research therefore needs to be done in the area of detecting and overcoming conceptualization mismatches that may occur during the process of mapping. The automation and reliability of these tools are important because they directly affect the interoperatbility between different knowledge sources

Cross-lingual Linking on the Multilingual Web of Data (position statement)

Recently, the Semantic Web has experienced signi�cant advancements in standards and techniques, as well as in the amount of semantic information available online. Even so, mechanisms are still needed to automatically reconcile semantic information when it is expressed in di�erent natural languages, so that access to Web information across language barriers can be improved. That requires developing techniques for discovering and representing cross-lingual links on the Web of Data. In this paper we explore the different dimensions of such a problem and reflect on possible avenues of research on that topic

Enriching Ontologies with Multilingual Information

This paper presents a novel approach to ontology localization with the objective of obtaining multilingual ontologies. Within the ontology development process, ontology localization has been defined as the activity of adapting an ontology to a concrete linguistic and cultural community. Depending on the ontology layers – terminological and/or conceptual – involved in the ontology localization activity, three heterogeneous multilingual ontology metamodels have been identified, of which we propose one of them. Our proposal consists in associating the ontology metamodel to an external model for representing and structuring lexical and terminological data in different natural languages. Our model has been called Linguistic Information Repository (LIR). The main advantages of this modelling modality rely on its flexibility by allowing (1) the enrichment of any ontology element with as much linguistic information as needed by the final application, and (2) the establishment of links among linguistic elements within and across different natural languages. The LIR model has been designed as an ontology of linguistic elements and is currently available in Web Ontology Language (OWL). The set of lexical and terminological data that it provides to ontology elements enables the localization of any ontology to a certain linguistic and cultural universe. The LIR has been evaluated against the multilingual requirements of the Food and Agriculture Organization of the United Nations in the framework of the NeOn project. It has proven to solve multilingual representation problems related to the establishment of well-defined relations among lexicalizations within and across languages, as well as conceptualization mismatches among different languages. Finally, we present an extension to the Ontology Metadata Vocabulary, the so-called LexOMV, with the aim of reporting on multilinguality at the ontology metadata level. By adding this contribution to the LIR model, we account for multilinguality at the three levels of an ontology: data level, knowledge representation level and metadata level

An ontological approach to federated data integration

During the last years a lot of projects and lines of research have emerged from different proposals trying to find the best way to reach data integration. Two powerful techniques have appeared separately – ontology and contextual information – in order to help solve semantic heterogeneity problems. In our proposal we combine both techniques exploiting the advantages of each of them. We propose a new approach, in which three main components work together in order to achieve a consistent integration. Each component contains some type of semantic information modeled by ontologies and contexts. Our approach helps the building of each of the components and address other types of heterogeneity such as ontological heterogeneity.Eje: Ingeniería de Software y Bases de Datos (ISBD)Red de Universidades con Carreras en Informática (RedUNCI