Catálogo de publicaciones - libros

This paper views the Semantic Web as a means to improve the interoperability between systems, applications, and information sources. Emerging personal computing paradigms such as ubiquitous and mobile computing will benefit from better interoperability, as this is an enabler for a higher degree of automation of many tasks that would otherwise require the end-users’ attention. Specific application areas of Semantic Web technologies with direct ramifications to these new paradigms include Web Services, context-awareness and policy modeling.

Semantic web technology is more and more often applied to a large spectrum of applications where domain knowledge is conceptualized and formalized (Ontology) as a support for diversified processing (Reasoning) operated by machines. Moreover through a subtle joining of human reasoning (cognitive) and mechanical reasoning (logic-based), it is possible for humans and machines to share complementary tasks. To name few of those applications areas: Corporate Portals and Knowledge Management, E-Commerce, E-Work, Healthcare, E-Government, Natural Language understanding and Automated Translation, Information search, Data and Services Integration, Social networks and collaborative filtering, Knowledge Mining, etc. From a social and economic perspective, this emerging technology should contribute to growth in economic wealth, but it must also show clear cut value in our everyday activities in being technology transparent and efficient. The uptake of Semantic Web technology by industry is progressing slowly. One of the problems is that academia is not always aware of the concrete problems that arise in industry. Conversely, industry is not often well informed about the academic developments that can potentially meet its needs. In this paper we present an ongoing work in the cross-fertilization between industry and academy. In particular, we present a collection of applications fields and use cases from enterprises which are interested in the promises of Semantic Web technology. We explain our approach in the analysis of the industry needs. We summarize industrial knowledge processing requirements in the form of a typology of knowledge processing tasks. These results are intended to focus academia on the development of plausible knowledge-based solutions for concrete industrial problems, and therefore, facilitate the uptake of Semantic Web technology within industry.

Semantic Web is in the transition from vision and research to reality. In this early state, it is important to study the technical capabilities in the context of real-world applications, and how applications built using the Semantic Web technology meet the real market needs. Beyond push from research, it is the market pull and the ability of the technology to meet real business needs that is a key to ultimate success of any technology. In this paper, we discuss the market of Risk and Compliance which presents unique market opportunity combined with challenging technical requirements. We discuss how the Semantic Web technology with an ontology driven approach is especially well suited to support the demanding requirements of the applications in this market. We also discuss the capabilities of a commercial semantic technology that has origins in academic research, as it is utilized in a significant Risk and Compliance application deployed at large financial institutions. Core capabilities of this technology include the ability to develop and maintain focused but large populated ontologies, automatic semantic metadata extraction supported by disambiguation techniques, ability to process heterogeneous information and provide semantic integration combined with link identification and analysis through rule specification and execution, as well as organization and domain specific scoring and ranking. These semantic capabilities are coupled with enterprise software capabilities which are necessary for success of an emerging technology for meeting the needs of demanding enterprise customers.

This paper presents one approach for developing enterprise ontologies. The underlying research framework is pursuing a methodology that will aid the process of knowledge structuring and practical ontology design, with emphasis on visual techniques. For illustration of the proposed technique, the development of a practical ontology of information technology skills for a human resources knowledge management system is described.

Agent-oriented approach has proven to be very efficient in engineering complex distributed software environments with dynamically changing conditions. The efficiency of underlying modelling framework for this domain is undoubtedly of a crucial importance. Currently, a model-driven architecture has been the most popular and developed for purposes of modelling different aspects of multi-agent systems, including behaviour of individual agents. UML is utilized as a basis for this modelling approach and variety of existing UML-based modelling tools after slight extension are reused. This paper proposes an ontology-driven approach to modelling agent behaviour as an emerging paradigm that originates from the Semantic Web wave. The proposed approach aims at modelling a proactive behaviour of (web-)resources through their representatives: software agents. In general, the presented research puts efforts into investigation of beneficial features of ontology-based agent modelling in comparison with conventional model-driven approaches.

In present day, there are a number of image data in the web because of the development of the image acquisition devices. So, many researchers have been studying about the image retrieval and management. Keyword matching, contents-based and concept-based methods are the basic studies for the image retrieval. In this paper, we suggest the new image retrieval methodology using the cognitive spatial relationships between the objects in the image. There were the similar studies already using the spatial relationships. However, the studies have the limitations and don’t give the good search results. We think to need the new methodology for representing the spatial relationships. It is the cognitive spatial relationships. In our study, we newly define the cognitive spatial relationships and apply it to the image retrieval system. At the result, we realized that our methodology makes possible the semantic image retrieval. Key words: Cognitive Spatial Relationships, Ontology, Semantic Web, Image Retrieval

Information overload is mainly the result of the combination of four factors: the enormous amount of information available; the heterogeneity of information sources and information channels; the generation of a significant percentage of redundant information; and inefficient mechanisms for filtering, searching and classifying information. Given that the former factor cannot be changed, and current forecast expects that information grows exponentially in the next years, research and industry efforts are focusing to overcome the other three. The association of machine-understandable semantics to formally describe data published on the Web and the development of appropriate tools that can handle this method to describe data are the approaches that the promoters of the Semantic Web have suggested to overcome the problem of information overload in the Web. Although, the Semantic Web promises a new level of service with regard to the current Web, a more drastic approach is required. Conceptual Spaces (CSpaces) envision the future of the Semantic Web as a cooperative environment where communication between humans, machines, and human-and-machines will be reduced to the acts of publishing and reading machine processable semantics in a persistent collection of individual and shared information spaces. Decreasing the amount of syntactic data representation in the Semantic Web, and therefore, make machine processable semantics the prevalent representation formalism will facilitate interoperation between heterogeneous applications, web services, agents, humans and so on. Natural language generation and graphical knowledge visualization techniques will make possible that humans deal with this “purest semantic” Web. In addition, CSpaces will also decrease redundancy of the information stored and will provide a better organization of the data articulated around ontologies.

Although UDDI does not provide support for semantic search, retrieval and storage, it is already accepted as an industrial standard and a huge number of services already store their service specifications in UDDI. Objective of this paper is to analyze possibilities and ways to use UDDI registry to allow utilization of meta-data encoded according to Semantic Web standards for semantic-based description, discovery and integration of web resources in the context of needs of two research projects: “Adaptive Services Grid” and “SmartResource”. We present an approach of mapping RDFS upper concepts to UDDI data model using tModel structure, which makes possible to store semantically annotated resources internally in UDDI. We consider UDDI as an enabling specification for creation of a semantic registry for not only services, but also for web resources in general.

This paper discusses potential usage of Semantic Web in business applications and provides one way to proceed faster.

Current situation in Semantic Web application area is discussed. General appropriate trends in technology development and in communication industry and industry general are reviewed in order to see how Semantic Web technology fits with these trends.

Finally this paper suggests that, to get the technology into use, a common application framework should be formed. This framework shall look not only the technology, but also application, ICT architectures and business models this technology makes relevant. Definition of this framework is proposed to be a part of a road map process for which guidelines are provided.

A logistics information service manages a large amount of products and product transport flow. Many applications request logistics information from a logistics information service. For effective sharing of logistics information and knowledge, the design of a logistics information management system is important. The current web is changing to a semantic web that provides a common framework for data sharing. In this paper, we present a logistics information service architecture that supports a semantic web. Our logistics information service deals with RFID-sensed data and product-related data such as attribute, and containments. Logistics data is represented using the RDF for service to various applications.