Evaluating Knowledge Representation and Reasoning Capabilites of Ontology Specification Languages

The interchange of ontologies across the World Wide Web (WWW) and the cooperation among heterogeneous agents placed on it is the main reason for the development of a new set of ontology specification languages, based on new web standards such as XML or RDF. These languages (SHOE, XOL, RDF, OIL, etc) aim to represent the knowledge contained in an ontology in a simple and human-readable way, as well as allow for the interchange of ontologies across the web. In this paper, we establish a common framework to compare the expressiveness of "traditional" ontology languages (Ontolingua, OKBC, OCML, FLogic, LOOM) and "web-based" ontology languages. As a result of this study, we conclude that different needs in KR and reasoning may exist in the building of an ontology-based application, and these needs must be evaluated in order to choose the most suitable ontology language(s)

A roadmap to ontology specification languages

The interchange of ontologies across the World Wide Web (WWW) and the cooperation among heterogeneous agents placed on it is the main reason for the development of a new set of ontology specification languages, based on new web standards such as XML or RDF. These languages (SHOE, XOL, RDF, OIL, etc) aim to represent the knowledge contained in an ontology in a simple and human-readable way, as well as allow for the interchange of ontologies across the web. In this paper, we establish a common framework to compare the expressiveness and reasoning capabilities of "traditional" ontology languages (Ontolingua, OKBC, OCML, FLogic, LOOM) and "web-based" ontology languages, and conclude with the results of applying this framework to the selected languages

Guidelines to Study Differences in Expressiveness between Ontology Specification Languages: A Case Of Study

We focus on our experiences on translating ontologies between two ontology languages, FLogic and Ontolingua, in the framework of Methontology and ODE. Rather than building "ad hoc" translators between languages or using KIF, our option consists of translating through ODE intermediate representations. So, we have built direct translators from ODE intermediate representations to Ontolingua and FLogic, and we have also built reverse translators from these two languages to ODE intermediate representations. Expressiveness of the target languages is the main feature to analyse when automatically generating ontologies from ODE intermediate representations. Therefore, we analyse the expressiveness of Ontolingua and FLogic for creating classes, instances, relations, functions and axioms, which are the essential components in ontologies. The motivation for this analysis can be found in the (KA)² initiative and can be easily extended to any other domains and languages

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

Woleaian-English Dictionary

Humanities Open Book Program, a joint initiative of the National Endowment for the Humanities and the Andrew W. Mellon FoundationThis was the first dictionary compiled for the language spoken on Woleai Atoll in the Caroline Islands. The dictionary contains some 6,200 Woleaian entries and an English-Woleaian finder list of about 4,000 entries. The Woleaian entries are based on an alphabetic system of orthography developed by the authors. Each entry also contains, where appropriate, the following parts: loan source, alternant forms, part of speech or word-class, grammatical notes, definitions, phrase examples, sentence examples, synonyms, antonyms, and cross-references

Reusing ontologies in Competence Development programmes: RuleML and its capabilities

We want to solve several tasks with this paper - to show how different domain ontologies can be used in Learning Networks for Lifelong Competence Development (LN4LCD), to design experiments with reusing of a given domain ontology in different LN4LCD, to analyse the existing ontology languages in order to choose a suitable one (supporting the process of reuse of a domain ontology), and to show how how such ontology can be incorporated in different Learning Designs

Formalizing Knowledge by Ontologies: OWL and KIF

During the last years, the activities of knowledge formalization and sharing useful to allow for semantically enabled management of information have been attracting growing attention, expecially in distributed environments like the Web. In this report, after a general introduction about the basis of knowledge abstraction and its formalization through ontologies, we briefly present a list of relevant formal languages used to represent knowledge: CycL, FLogic, LOOM, KIF, Ontolingua, RDF(S) and OWL. Then we focus our attention on the Web Ontology Language (OWL) and the Knowledge Interchange Format (KIF). OWL is the main language used to describe and share ontologies over the Web: there are three OWL sublanguages with a growing degree of expressiveness. We describe its structure as well as the way it is used in order to reasons over asserted knowledge. Moreover we briefly present three relevant OWL ontology editors: Prot?eg?e, SWOOP and Ontotrack and two important OWL reasoners: Pellet and FACT++. KIF is mainly a standard to describe knowledge among different computer systems so as to facilitate its exchange. We describe the main elements of KIF syntax; we also consider Sigma, an environment for creating, testing, modifying, and performing inference with KIF ontologies. We comment some meaningful example of both OWL and KIF ontologies and, in conclusion, we compare their main expresive features

Developing an advanced collision risk model for autonomous vehicles

Aiming at improving road safety, car manufacturers and researchers are verging upon autonomous vehicles. In recent years, collision prediction methods of autonomous vehicles have begun incorporating contextual information such as information about the traffic environment and the relative motion of other traffic participants but still fail to anticipate traffic scenarios of high complexity. During the past two decades, the problem of real-time collision prediction has also been investigated by traffic engineers. In the traffic engineering approach, a collision occurrence can potentially be predicted in real-time based on available data on traffic dynamics such as the average speed and flow of vehicles on a road segment. This thesis attempts to integrate vehicle-level collision prediction approaches for autonomous vehicles with network-level collision prediction, as studied by traffic engineers. [Continues.