A view of OWL from the field: Use cases and experiences

Abstract. OWL is the ontology language recommended by the W3C. OWL is heavily based on the knowledge representation languages called Description Logic, which provide the basic representation features of OWL. OWL also includes facilities that integrate it into the mainstream of the Web, including use of IRIs as names, XML Schema datatypes, and ontologies as Web documents, which can then import other OWL ontologies over the Web.

The success of the Semantic Web will largely depend on whether W3C's Web Ontology Language can reach broad acceptance and a critical mass of industry-strength applications. We have been exploiting the use of OWL with a particular focus on tool support for ontology authoring and on providing access to the Semantic Web for mobile applications. In the latter case our vision is to overlay the Semantic Web on ubiquitous computing environments making it possible to represent and interlink content and services as well as users, devices, their capabilities and the functionality they offer. In this paper we present our first experiences and lessons learned from early work and try to give constructive feedback for possible enhancements of OWL and its tools.

2004

Abstract The OWL Web Ontology Language is designed for use by applications that need to process the content of information instead of just presenting information to humans. OWL facilitates greater machine interpretability of Web content than that supported by XML, RDF, and RDF Schema (RDF-S) by providing additional vocabulary along with a formal semantics. OWL has three increasingly-expressive sublanguages: OWL Lite, OWL DL, and OWL Full.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2013

Tool development for and empirical experimentation in OWL ontology engineering require a wide variety of suitable ontologies as input for testing and evaluation purposes and detailed characterisations of real ontologies. Empirical activities often resort to (somewhat arbitrarily) hand curated corpora available on the web, such as the NCBO BioPortal and the TONES Repository, or manually selected sets of well-known ontologies. Findings of surveys and results of benchmarking activities may be biased, even heavily, towards these datasets. Sampling from a large corpus of ontologies, on the other hand, may lead to more representative results. Current large scale repositories and web crawls are mostly uncurated and suffer from duplication, small and (for many purposes) uninteresting ontology files, and contain large numbers of ontology versions, variants, and facets, and therefore do not lend themselves to random sampling. In this paper, we survey ontologies as they exist on the web and describe the creation of a corpus of OWL DL ontologies using strategies such as web crawling, various forms of de-duplications and manual cleaning, which allows random sampling of ontologies for a variety of empirical applications.

2007

In this paper, an object-oriented model and a software environment for the management of OWL ontologies is presented. The object-oriented model allows a simple and complete representation of ontologies defined by using OWL DL profile. The software environment, called OWLET, implements this object-oriented model and provides a complete set of reasoning functions together with a graphical editor for the creation and modification of ontologies. OWLET can be very useful for realizing heterogeneous and distributed semantic systems where nodes differ for their capabilities (i.e., CPU power, memory size, …); in fact, it offers a layered reasoning API that allows to deploy a system where high power nodes take advantages of all the OWLET reasoning capabilities, medium power nodes take advantages of a limited set of OWLET reasoning capabilities (e.g., reasoning about individuals) and low power nodes delegate reasoning tasks to the other nodes of the system.

2009

The OWL 2 Web Ontology Language, informally OWL 2, is an ontology language for the Semantic Web with formally defined meaning. OWL 2 ontologies provide classes, properties, individuals, and data values and are stored as Semantic Web documents. OWL 2 ontologies can be used along with information written in RDF, and OWL 2 ontologies themselves are primarily exchanged as RDF documents. The OWL 2 Document Overview describes the overall state of OWL 2, and should be read before other OWL 2 documents. This document is a simple introduction to the new features of the OWL 2 Web Ontology Language, including an explanation of the differences between the initial version of OWL and OWL 2. The document also presents the requirements that have motivated the design of the main new features, and their rationale from a theoretical and implementation perspective. OWL 2 Web Ontology LanguageNew Features and Rationale W3C Editor's Draft

International Journal of Computer Applications, 2011

In The World Wide Web (WWW) serves the human with vast amount of data and information.The usage pattern or user base has multiplied many folds since its origin. Despite the increasing importance gained by the WWW, to serve the human, it lacks the feature to serve meaningful information to machine this means that limited support for utilization of data and information is achieved. Thus the web needs to be made Semantic wherein different applications, agents, Web services and the web sites can exchange information to their full potential. This calls for representing the knowledge residing on WWW in a uniform manner understandable by both man and machine. Thus some taxonomy is needed to make representations of the web contents which can be machine readable and usable .This paper proposes to relate the need for Ontology and relate it to Web ontology language (OWL) and identify its position in making the Semantic Web. It is also felt that ontological support is needed for the semantic web in order to make the information ready for machine consumption. The ontological structure using the Web Ontology Language (OWL) which is used for modeling ontologies of context and for supporting Context reasoning is explored in this paper.The Web Ontology Language is designed for use by applications that need to process the content of information instead of just presenting information to humans. OWL facilitates greater machine interpretability of Web content

2003

The OWL Web Ontology Language is a new formal language for representing ontologies in the Semantic Web. OWL has features from several families of representation languages, including primarily Description Logics and frames. OWL also shares many characteristics with RDF, the W3C base of the Semantic Web. In this paper, we discuss how the philosophy and features of OWL can be traced back to these older formalisms, with modifications driven by several other constraints on OWL.

2016

This paper presents our work on development of OWL-driven systems for formal representation and reasoning about terminological knowledge and facts in petrology. The long-term aim of our project is to provide solid foundations for a large-scale integration of various kinds of knowledge, including basic terms, rock classification algorithms, findings and reports. We describe three steps we have taken towards that goal here. First, we develop a semi-automated procedure for transforming a database of igneous rock samples to texts in a controlled natural language (CNL), and then a collection of OWL ontologies. Second, we create an OWL ontology of important petrology terms currently described in natural language thesauri. We describe a prototype of a tool for collecting definitions from domain experts. Third, we present an approach to formalization of current industrial standards for classification of rock samples, which requires linear equations in OWL 2. In conclusion, we discuss a range of opportunities arising from the use of semantic technologies in petrology and outline the future work in this area.

Cambridge University Press eBooks, 2007