74 research outputs found
Results of Taxonomic Evaluation of RDF(S) and DAML+OIL Ontologies using RDF(S) and DAML+OIL Validation Tools and Ontology Platforms Import Services
Before using RDF(S) and DAML+OIL ontologies in Semantic Web applications, its content should be evaluated from a knowledge representation point of view. In recent years, some RDF(S) and DAML+OIL ‘checkers’, ‘validators’, and ‘parsers’ have been created and several ontology platforms are able to import RDF(S) and DAML+OIL ontologies. Two are the experiments presented in this paper. The first one reveals that the majority of RDF(S) and DAML+OIL parsers (Validating RDF Parser, RDF Validation Service, DAML Validator, and DAML+OIL Ontology Checker) do not detect taxonomic mistakes in ontologies implemented in such languages. So, if such ontologies are imported by ontology platforms, are they able to detect such problems? The second experiment presented in this paper reveals that the majority of the ontology platforms (OilEd, OntoEdit, Protégé-2000, and WebODE) only detect a few of mistakes in concept taxonomies before importing them
Ontology Evaluation Functionalities of RDF(S), DAML+OIL, and OWL Parsers and Ontology Platforms
Before using ontologies in Semantic Web applications, ontology content and ontology tools (parsers, platforms, etc.) should be evaluated. In this paper we evaluate ontology evaluation functionalities of RDF(S), DAML+OIL, and OWL parsers and import services for such languages within ontology platforms. In recent years, some RDF(S), DAML+OIL, and OWL parsers have been created and several ontology platforms are able to import ontologies implemented in such languages. In this paper we present two experiments. The first one reveals that most RDF(S), DAML+OIL, and OWL parsers studied do not detect taxonomic problems, from a knowledge representation point of view, in ontologies implemented in such languages. So, if such ontologies are imported by ontology platforms, the question is: are they able to detect such problems? The second experiment presented in this paper reveals that most ontology platforms analyzed only detect a few of problems in concept taxonomies during ontology import
ODEval: a Tool for Evaluating RDF(S), DAML+OIL, and OWL Concept Taxonomies
Ontologies implemented in RDF(S), DAML+OIL, and OWL should be evaluated from the point of view of knowledge representation before using them in Semantic Web applications. Several language-dependent ontology validation tools and ontology platforms, such as OilEd with FaCT, can be used in order to evaluate RDF(S), DAML+OIL and OWL ontologies. This paper offers two main contributions. The first of these exams whether previous ontology tools detect knowledge representation problems in RDF(S), DAML+OIL, and OWL concept taxonomies. Indeed, such tools do not focus on detecting inconsistencies and redundancies in concept taxonomies. The second contribution is ODEval, a language-dependent tool for evaluating, from the point of view of knowledge representation, concept taxonomies in ontologies implemented in such languages. ODEval complements previous ontology tools when we want to evaluate RDF(S), DAML+OIL, and OWL concept taxonomie
Methodologies, tools and languages for building ontologies. Where is their meeting point?
In this paper we review and compare the main methodologies, tools and languages for building ontologies that have been reported in the literature, as well as the main relationships among them. Ontology technology is nowadays mature enough: many methodologies, tools and languages are already available. The future work in this field should be driven towards the creation of a common integrated workbench for ontology developers to facilitate ontology development, exchange, evaluation, evolution and management, to provide methodological support for these tasks, and translations to and from different ontology languages. This workbench should not be created from scratch, but instead integrating the technology components that are currently available
A semantic and agent-based approach to support information retrieval, interoperability and multi-lateral viewpoints for heterogeneous environmental databases
PhDData stored in individual autonomous databases often needs to be combined and
interrelated. For example, in the Inland Water (IW) environment monitoring domain,
the spatial and temporal variation of measurements of different water quality indicators
stored in different databases are of interest. Data from multiple data sources is more
complex to combine when there is a lack of metadata in a computation forin and when
the syntax and semantics of the stored data models are heterogeneous. The main types
of information retrieval (IR) requirements are query transparency and data
harmonisation for data interoperability and support for multiple user views. A
combined Semantic Web based and Agent based distributed system framework has
been developed to support the above IR requirements. It has been implemented using
the Jena ontology and JADE agent toolkits. The semantic part supports the
interoperability of autonomous data sources by merging their intensional data, using a
Global-As-View or GAV approach, into a global semantic model, represented in
DAML+OIL and in OWL. This is used to mediate between different local database
views. The agent part provides the semantic services to import, align and parse
semantic metadata instances, to support data mediation and to reason about data
mappings during alignment. The framework has applied to support information
retrieval, interoperability and multi-lateral viewpoints for four European environmental
agency databases.
An extended GAV approach has been developed and applied to handle queries that can
be reformulated over multiple user views of the stored data. This allows users to
retrieve data in a conceptualisation that is better suited to them rather than to have to
understand the entire detailed global view conceptualisation. User viewpoints are
derived from the global ontology or existing viewpoints of it. This has the advantage
that it reduces the number of potential conceptualisations and their associated
mappings to be more computationally manageable. Whereas an ad hoc framework
based upon conventional distributed programming language and a rule framework
could be used to support user views and adaptation to user views, a more formal
framework has the benefit in that it can support reasoning about the consistency,
equivalence, containment and conflict resolution when traversing data models. A
preliminary formulation of the formal model has been undertaken and is based upon
extending a Datalog type algebra with hierarchical, attribute and instance value
operators. These operators can be applied to support compositional mapping and
consistency checking of data views. The multiple viewpoint system was implemented
as a Java-based application consisting of two sub-systems, one for viewpoint
adaptation and management, the other for query processing and query result
adjustment
Ontology-based infrastructure for intelligent applications
Ontologies currently are a hot topic in the areas of knowledge management and enterprise application integration. In this thesis, we investigate how ontologies can also be used as an infrastructure for developing applications that intelligently support a user with various tasks. Based on recent developments in the area of the Semantic Web, we provide three major contributions. We introduce inference engines, which allow the execution of business logic that is specified in a declarative way, while putting strong emphasis on scalability and ease of use. Secondly, we suggest various solutions for interfacing applications that are developed under this new paradigm with existing IT infrastructure. This includes the first running solution, to our knowledge, for combining the emerging areas of the Semantic Web Services. Finally, we introduce a set of intelligent applications, which is built on top of onologies and Semantic Web standards, providing a proof of concept that the engineering effort can largely be based on standard components.Ontologien sind derzeit ein viel diskutiertes Thema in Bereichen wie Wissensmanagement oder Enterprise Application Integration. Diese Arbeit stellt dar, wie Ontologien als Infrastruktur zur Entwicklung neuartiger Applikationen verwendet werden können, die den User bei verschiedenen Arbeiten unterstützen.
Aufbauend auf den im Rahmen des Semantischen Webs entstandenen Spezifikationen, werden drei wesentliche Beiträge geleistet. Zum einen stellen wir Inferenzmaschinen vor, die das Ausführen von deklarativ spezifizierter Applikationslogik erlauben, wobei besonderes Augenmerk auf die Skalierbarkeit gelegt wird. Zum anderen schlagen wir mehrere Lösungen zum Anschluss solcher Systeme an bestehende IT Infrastruktur vor. Dies beinhaltet den, unseres Wissens
nach, ersten lauffähigen Prototyp der die beiden aufstrebenden Felder des Semantischen Webs und Web Services verbindet. Schließlich stellen wir einige
intelligente Applikationen vor, die auf Ontologien basieren und somit großteils
von Werkzeugen automatisch generiert werden können
- …