Catálogo de publicaciones - libros

Knowledge related to Shape Modelling is multi-faceted because of the complexity and heterogeneity of the involved resources and because different applications may cast different semantics on them. A fast evolution of the field is now conditioned by how research teams will be able to communicate and share resources and knowledge. The field needs to be formalized in order to achieve a shared conceptualization accessible by the whole scientific community and eventually to ensure an actual exploitation of its knowledge within the Semantic Web. In this context, the main objective of the Network of Excellence AIM@SHAPE is twofold: on the one hand to devise tools to capture the implicit semantics of digital shapes, and on the other hand to encode and formalize the domain knowledge into context-dependent ontologies. The paper describes the first results in the direction of developing an ontology for shape acquisition and reconstruction and its effective use in the Digital Shape Workbench, a searching framework for sharing resources (shapes, tools and publications) and their related knowledge.

Ontologies have seen quite an enormous development and application in many domains within the last years, especially in the context of the next web generation, the Semantic Web. Besides the work of countless researchers across the world, industry starts developing ontologies to support their daily operative business. Currently, most ontologies exist in pure form without any additional information, e.g. authorship information, such as provided by Dublin Core for text documents. This burden makes it difficult for academia and industry e.g. to identify, find and apply – basically meaning to reuse – ontologies effectively and efficiently. Our contribution consists of (i) a proposal for a metadata standard, so called Ontology Metadata Vocabulary (OMV) which is based on discussions in the EU IST thematic network of excellence Knowledge Web and (ii) two complementary reference implementations which show the benefit of such a standard in decentralized and centralized scenarios, i.e. the Oyster P2P system and the Onthology metadata portal.

In this paper we proposed a Protein Ontology to integrate protein data and information from various Protein Data Sources. Protein Ontology provides the technical and scientific infrastructure and knowledge to allow description and analysis of relationships between various proteins. Protein Ontology uses relevant protein data sources of information like PDB, SCOP, and OMIM. Protein Ontology describes: Protein Sequence and Structure Information, Protein Folding Process, Cellular Functions of Proteins, Molecular Bindings internal and external to Proteins, and Constraints affecting the Final Protein Conformation. We also created a database of 10 Major Prion Proteins available in various Protein data sources, based on the vocabulary provided by Protein Ontology. Details about Protein Ontology are available online at http://www.proteinontology.info/.

The Web Ontology Language OWL has been advocated as a suitable model for semantic data integration. Data integration requires expressive means to map between heterogeneous OWL schemas. This paper introduces SWQL (Semantic Web Query Language), a strictly typed query language for OWL, and shows how it can be used for mapping between heterogeneous schemas. In contrast to existing RDF query languages which focus on selection and navigation, SWQL also supports construction and user-defined functions to allow for instantiating integrated global schemas in OWL.

The emergence of Semantic Web (SW) and the related technologies promise to make the web a meaningful experience.  Yet, high level modeling, design and querying techniques proves to be a challenging task for organizations that are hoping utilize the SW paradigm for their industrial applications, which are still using traditional database techniques. To address such an issue, in this paper, we propose a view model for the SW (SW-View), to SW-enable traditional solutions. First we outline the view model, its properties and some modeling issues, followed by some discussions on modeling such views (at the conceptual level). We also provide a brief discussion on how this view model is utilized in the design and construction of materialized ontology views to support extraction of sub-ontologies.

In this paper we discuss aspects of cardinality constraints in schema matching. A new cardinality classification is proposed, emphasizing the challenges in schema matching that evolve from cardinality constraints. We also offer a new research direction for automating schema matching to manage cardinality constraints.

The growing development of web-based reputation systems in the 21 century will have a powerful social and economic impact on both business entities and individual customers, because it makes transparent quality assessment on products and services to achieve customer assurance in the distributed web-based Reputation Systems. The web-based reputation systems will be the foundation for web intelligence in the future. Trust and Reputation help capture business intelligence through establishing customer trust relationships, learning consumer behavior, capturing market reaction on products and services, disseminating customer feedback, buyers’ opinions and end-user recommendations. It also reveals dishonest services, unfair trading, biased assessment, discriminatory actions, fraudulent behaviors, and un-true advertising. The continuing development of these technologies will help in the improvement of professional business behavior, sales, reputation of sellers, providers, products and services. Given the importance of reputation in this paper, we propose ontology for reputation. In the business world we can consider the reputation of a product or the reputation of a service or the reputation of an agent. In this paper we propose ontology for these entities that can help us unravel the components and conceptualize the components of reputation of each of the entities.

Translating XML data into ontologies is the problem of finding an instance of an ontology, given an XML document and a specification of the relationship between the XML schema and the ontology. Previous study [8] has investigated the approach used in XML data integration. In this paper, we consider to translate an XML web document to an instance of an OWL-DL ontology in the Semantic Web. We use the semantic mapping discovered by our prototype tool [1] for the relationship between the XML schema and the ontology. Particularly, we define the of the translation problem and develop an algorithm for computing a which enables the ontology to answer queries by using data in the XML document.

Reliability is a well-known concern in the field of personalization technologies. We propose the extension of an ontology-based retrieval system with semantic-based personalization techniques, upon which automatic mechanisms are devised that dynamically gauge the degree of personalization, so as to benefit from adaptivity but yet reduce the risk of obtrusiveness and loss of user control. On the basis of a common domain ontology KB, the personalization framework represents, captures and exploits user preferences to bias search results towards personal user interests. Upon this, the intensity of personalization is automatically increased or decreased according to an assessment of the imprecision contained in user requests and system responses before personalization is applied.

In this paper we describe a clustering process selecting a set of typical instances from a document flow. These representatives are viewed as semi-structured descriptions of domain categories expressed in a standard semantic web format, such as OWL [15]. The resulting bottom-up ontology may be used to check and/or update existing domain ontologies used by the e-business infrastructure.