Catálogo de publicaciones - libros

One of the most important characteristics of today’s society is that a huge amount of information is shared by many participants (people, applications). This information must be characterized by a uniformity of terms. This means that, in similar contexts, everyone should understand the same meaning when reading or hearing the same word and everyone should use the same word to refer to the same concept. In different Computer Science disciplines one of the methods that satisfies this need for “common understanding” of concepts is the creation of . Curiously, there are different interpretations of what ontology is. In this chapter, we show the way that the concept of ontology has expanded from Philosophy into Computer Science.

This chapter describes the role of ontologies and corporate taxonomies in managing the content and knowledge within organizations. Managing content in a reusable and effective manner is becoming increasingly important in knowledge centric organizations as the amount of content generated, both text based and rich media, is growing exponentially. Search, categorization and document characterization, content staging and content delivery are the key technology challenges in knowledge management systems. This chapter describes how corporate taxonomies and ontologies can help in making sense of huge amount of content that gets generated across the locations in different languages and formats Different information silos can be connected and workflow and collaboration can be achieved using ontologies. As the KM solutions are moving from a centralized approach to a distributed approach, a framework where multiple taxonomies and ontologies can co-exist with uniform interfaces is needed.

The majority of current information systems were implemented using traditional paradigms which include business modeling techniques applied during the analysis phase such as System Flow Charts, Data Flow Diagrams and Entity-Relationship Diagrams. These legacy systems are now struggling to cope with recent developments, particularly trends towards e-Commerce applications, platform independence, reusability of pre-built components, capacity for reconfiguration and higher reliability. Many organizations now realize they need to re-engineer their systems using new component-based systems approaches and object-oriented computer languages. Although the traditional and component-based approaches have different grammars for representing business models, these business models can be compared, based on their ontological grammars. This paper illustrates how an ontological evaluation of business models can be used to compare them for equivalency of representation of business requirements, when re-engineering legacy systems into component-based information systems.

The Semantic Web is well recognized as an effective infrastructure to enhance visibility of knowledge on the Web. The core of the Semantic Web is “ontology”, which is used to explicitly represent our conceptualizations. Ontology engineering in the Semantic Web is primarily supported by languages such as RDF, RDFS and OWL. This chapter discusses the requirements of ontology in the context of the Web, compares the above three languages with existing knowledge representation formalisms, and surveys tools for managing and applying ontology. Advantages of using ontology in both knowledge-base-style and database-style applications are demonstrated using three real world applications.

This paper revisits the debate between positivism and its alternatives in the field of information systems from a philosophical point of view. It will argue that the heart of the debate is the ontological difference between the views of reality as observer-independent versus observer-dependent. The logical axiom of the excluded third () informs us that two contradictory options cannot simultaneously be true. The paper will discuss what the incompatibility of the ontological positions of positivism and its alternatives means for IS research. It will discuss why scholars attempt to mix the two and will spell out the consequences of an acceptance of their incompatibility. The paper will end by arguing that this debate needs to be contextualized with the problem of positivism versus non-positivism in society and it will ask whether a tolerant coexistence of the two approaches is feasible. Without this contextualized understanding of ontology in general, regional ontologies in IS are not likely to be successful as they will be based on unclear bases.

This paper discusses the influence which philosophical ontology has on the ascription of responsibility in IS. It starts out with a description of two ontological positions which are treated under the heading of “positivism” and “life-world”. Positivism is defined as being based on the assumption of an observer-independent objective reality whereas the life-world represents a reality that is created by intentional perception and hermeneutic interaction. In the subsequent section the paper introduces the concept of responsibility as a possible approach to the ethical and moral questions raised by the use of information systems. The final part then proceeds to discuss the influence that the ontological underpinning has on the ascription of responsibility. In conclusion it will be argued that these questions are of fundamental importance to information systems and that philosophical ontology therefore deserves a more explicit place in IS than it currently has.

Our approach to Case Based Reasoning (CBR) is towards integrated applications that combine case specific knowledge with models of general domain knowledge. In this paper, we describe a domain independent architecture to help in the design of knowledge intensive CBR systems. It is based on knowledge acquisition from a library of application-independent ontologies and the use of CBROnto, ontology with the common CBR terminology that guides case representation; allows the description of flexible, generic and reusable CBR Problem Solving Methods; and allows to reason about the description of CBR systems.

Ontologies and Model-Driven Architecture (MDA) are two modeling approaches being developed in parallel, but by different communities. They have common points and issues and can be brought closer together. Many authors have so far attempted to bridge gaps and have proposed several solutions. The result of these efforts is the recent OMG’s initiative for defining an ontology development platform. In this chapter, we are giving an overview of the state-of-the-art research on the subject of applications of MDA standards for ontology development. The chapter is a result of our experience in developing the MDA-based ontology infrastructure as well as a series of tutorials we gave at many international conferences. The chapter tries to indicate the most important definition for both of the considered modeling approaches. Using those definitions, we depict their mutual similarities and differences. Then, we show the present solution pursuing to apply MDA standard to ontology development with the main stress on OMG’s standardization efforts.

An ontology designed for multimedia applications should enable integration of the conceptual and media spaces. We present M-OWL, a new ontology language, that supports this capability. M-OWL supports explicit definition of media properties for the concepts. The language has been defined as an extension of OWL, the standard ontology language for the web. We have proposed a new Bayesian Network based probabilistic reasoning framework with M-OWL for semantic interpretation of multimedia data. We have also proposed a new model for ontology integration, based on the similarity of the concepts in the media domain. It can be used to integrate several multimedia and traditional ontologies.

One of the difficulties in the development of ontology is the issue of revising ontology. When the system accepts new information or knowledge, this new information may contradict what was initially agreed or defined in the ontology. When this happens, the ontology may need to be revised to reflect the changes. The belief revision theory provides a way that ensures new information does not cause inconsistencies with the existing system when it is introduced. This paper discusses the feasibility of using the concept of belief revision as a basis for ontology revision.