Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: NL

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: N

Requirements for Information Extraction for Knowledge Management

Knowledge Management (KM) systems inherently suffer from the knowledge acquisition bottleneck - the difficulty of modeling and formalizing knowledge relevant for specific domains. A potential solution to this problem is Information Extraction (IE) technology. However, IE was originally developed for database population and there is a mismatch between what is required to successfully perform KM and what current IE technology provides. In this paper we begin to address this issue by outlining requirements for IE based KM

Knowledge formalization in experience feedback processes : an ontology-based approach

Because of the current trend of integration and interoperability of industrial systems, their size and complexity continue to grow making it more difficult to analyze, to understand and to solve the problems that happen in their organizations. Continuous improvement methodologies are powerful tools in order to understand and to solve problems, to control the effects of changes and finally to capitalize knowledge about changes and improvements. These tools involve suitably represent knowledge relating to the concerned system. Consequently, knowledge management (KM) is an increasingly important source of competitive advantage for organizations. Particularly, the capitalization and sharing of knowledge resulting from experience feedback are elements which play an essential role in the continuous improvement of industrial activities. In this paper, the contribution deals with semantic interoperability and relates to the structuring and the formalization of an experience feedback (EF) process aiming at transforming information or understanding gained by experience into explicit knowledge. The reuse of such knowledge has proved to have significant impact on achieving themissions of companies. However, the means of describing the knowledge objects of an experience generally remain informal. Based on an experience feedback process model and conceptual graphs, this paper takes domain ontology as a framework for the clarification of explicit knowledge and know-how, the aim of which is to get lessons learned descriptions that are significant, correct and applicable

Supporting collaboration in multilingual ontology specification: the conceptME approach

Despite the availability of tools, resources and techniques aimed at the construction of ontological artifacts, developing a shared conceptualization of a given reality still raises questions about the principles and methods that support the initial phases of conceptualization. These questions become more complex when the conceptualization occurs in a multilingual setting. To tackle these issues a collaborative platform – conceptME - was developed where terminological and knowledge representation processes support domain experts throughout a conceptualization framework, allowing the inclusion of multilingual data to promote knowledge sharing and enhance conceptualization.info:eu-repo/semantics/publishedVersio

Hypotheses, evidence and relationships: The HypER approach for representing scientific knowledge claims

Biological knowledge is increasingly represented as a collection of (entity-relationship-entity) triplets. These are queried, mined, appended to papers, and published. However, this representation ignores the argumentation contained within a paper and the relationships between hypotheses, claims and evidence put forth in the article. In this paper, we propose an alternate view of the research article as a network of 'hypotheses and evidence'. Our knowledge representation focuses on scientific discourse as a rhetorical activity, which leads to a different direction in the development of tools and processes for modeling this discourse. We propose to extract knowledge from the article to allow the construction of a system where a specific scientific claim is connected, through trails of meaningful relationships, to experimental evidence. We discuss some current efforts and future plans in this area

Ontology Localization

nternational organizations (e.g., FAO1 , WHO2 , etc.) are increasingly expressing the need for multilingual ontologies for di®erent purposes, e.g., ontology-based multilingual machine translation, multilingual informa- tion retrieval. However, most of the ontologies built so far have mainly English or another natural language as basis. Since multilingual ontology building is a very ex- pensive and time-consuming undertaking, we propose methods for guiding users in the localization of ontolo- gies, and provide tools for supporting the process. The main contributions of this paper are: i) the descrip- tion of a generic Ontology Localization Activity and a methodology for guiding in the localization of ontolo- gies; ii) the description of a tool built according to the guidelines proposed for an automatic localization of on- tologies; and iii) a set of experiments used to evaluate the methodological and technological aspects of the On- tology Localization Activity

Applying ONTOCOM to DILIGENT

Ontology Engineering is currently advancing from a pure research topic to real applications. This state of the art is emphasized by the wide range of European projects with major industry involvement and, in the same time, by the evergrowing interest of small and medium size enterprizes asking for consultancy in this domain. A core requirement in all of these efforts is, however, the availability of proved and tested methods which allow an efficient engineering of high-quality ontologies, be that by reuse, new building or automatic extraction methods. Several elaborated methodologies, which aid the development of ontologies for particular application requirements, emerged in the last decades. Nevertheless, in order for ontologies to be built and deployed at a large scale, beyond the boundaries of the academic community, one needs not only technologies and tools to assist the engineering process, but also means to estimate and control its overall costs. These issues are addressed only marginally by current engineering approaches though their importance is well recognized in the community. Different approaches exist to estimate costs for engineering processes. We will present the parametric cost estimation model ONTOCOM and its alignment with the DILIGENT engineering methodology. Based on the resulting cost function some analytical evaluations of application scenarios for the DILIGENT model are provided

First Attempt towards a Standard Glossary of Ontology Engineering Terminology

In this paper we present the consensus reaching process followed within the NeOn consortium for the identification and definition of the activities involved in the ontology network development process. This work was conceived due to the lack of standardization in the Ontology Engineering terminology, which clearly contrasts with the Software Engineering field that boasts the IEEE Standard Glossary of Software Engineering Terminology. The paper also includes the NeOn Glossary of Activities, which is the result of the consensus reaching process here explained. Our future aim is to standardize the NeOn Glossary of Activities