Deborah L. McGuinness

Bringing semantics to web services: the OWL-S approach

Service interface description languages such as WSDL, and related standards, are evolving rapidly to provide a foundation for interoperation between Web services. At the same time, Semantic Web service technologies, such as the Ontology Web Language for Services (OWL-S), are developing the means by which services can be given richer semantic specifications. Richer semantics can enable fuller, more flexible automation of service provision and use, and support the construction of more powerful tools and methodologies. Both sets of technologies can benefit from complementary uses and cross-fertilization of ideas. This paper shows how to use OWL-S in conjunction with Web service standards, and explains and illustrates the value added by the semantics expressed in OWL-S.

OIL: an ontology infrastructure for the Semantic Web

Researchers in artificial intelligence first developed ontologies to facilitate knowledge sharing and reuse. Ontologies play a major role in supporting information exchange across various networks. A prerequisite for such a role is the development of a joint standard for specifying and exchanging ontologies. The authors present OIL, a proposal for such a standard. Ontologies applied to the World Wide Web are creating the Semantic Web.

Bringing Semantics to Web Services with OWL-S

Current industry standards for describing Web Services focus on ensuring interoperability across diverse platforms, but do not provide a good foundation for automating the use of Web Services. Representational techniques being developed for the Semantic Web can be used to augment these standards. The resulting Web Service specifications enable the development of software programs that can interpret descriptions of unfamiliar Web Services and then employ those services to satisfy user goals. OWL-S (“OWL for Services”) is a set of notations for expressing such specifications, based on the Semantic Web ontology language OWL. It consists of three interrelated parts: a profile ontology, used to describe what the service does; a process ontology and corresponding presentation syntax, used to describe how the service is used; and a grounding ontology, used to describe how to interact with the service. OWL-S can be used to automate a variety of service-related activities involving service discovery, interoperation, and composition. A large body of research on OWL-S has led to the creation of many open-source tools for developing, reasoning about, and dynamically utilizing Web Services.

LIVING WITH CLASSIC: When and How to Use a KL-ONE-Like Language

Abstract CLASSIC is a recently developed knowledge representation system that follows the paradigm originally set out in the KL-ONE system: It concentrates on the definition of structured concepts, their organization into taxonomies, the creation and manipulation of individual instances of such concepts, and the key inferences of subsumption and classification. Rather than simply presenting a description of CLASSIC, we complement a brief system overview with a discussion of how to live within the confines of a limited object-oriented deductive system. By analyzing the representational strengths and weaknesses of CLASSIC, we consider the circumstances under which it is most appropriate to use (or not use) it. We elaborate a knowledge engineering methodology for building KL-ONE-style knowledge bases, with emphasis on the modeling choices that arise in the process of describing a domain. We also address some of the key difficult issues encountered by new users, including primitive vs. defined concepts, and differences between roles and concepts, as well as representational “tricks-of-the-trade,” which we believe to be generally useful. Much of the discussion should be relevant to many of the current systems based on KL-ONE.

Web Ontology Language

McGuinness, D., van Harmelen, F. (2004). OWL Web Ontology Language - W3C Recommendation. Retrieved June 14, 2009, http://www.w3.org/TR/owl-features/

DAML+OIL: an ontology language for the Semantic Web

By all measures, the Web is enormous and growing at a staggering rate, which has made it increasingly difficult-and important-for both people and programs to have quick and accurate access to Web information and services. The Semantic Web offers a solution, capturing and exploiting the meaning of terms to transform the Web from a platform that focuses on presenting information, to a platform that focuses on understanding and reasoning with information. To support Semantic Web development, the US Defense Advanced Research Projects Agency launched the DARPA Agent Markup Language (DAML) initiative to fund research in languages, tools, infrastructure, and applications that make Web content more accessible and understandable. Although the US government funds DAML, several organizations-including US and European businesses and universities, and international consortia such as the World Wide Web Consortium-have contributed to work on issues related to DAMLs development and deployment. We focus on DAMLs current markup language, DAML+OIL, which is a proposed starting point for the W3Cs Semantic Web Activitys Ontology Web Language (OWL). We introduce DAML+OIL syntax and usage through a set of examples, drawn from a wine knowledge base used to teach novices how to build ontologies.

When owl: sameAs isn't the same: an analysis of identity in linked data

In Linked Data, the use of owl:sameAs is ubiquitous in interlinking data-sets. There is however, ongoing discussion about its use, and potential misuse, particularly with regards to interactions with inference. In fact, owl:sameAs can be viewed as encoding only one point on a scale of similarity, one that is often too strong for many of its current uses. We describe how referentially opaque contexts that do not allow inference exist, and then outline some varieties of referentially-opaque alternatives to owl:sameAs. Finally, we report on an empirical experiment over randomly selected owl:sameAs statements from the Web of data. This theoretical apparatus and experiment shed light upon how owl:sameAs is being used (and misused) on the Web of data.

The Description Logic Handbook: Contents

This introduction presents the main motivations for the development of Description Logics (DLs) as a formalism for representing knowledge, as well as some important basic notions underlying all systems that have been created in the DL tradition. In addition, we provide the reader with an overview of the entire book and some guidelines for reading it. We first address the relationship between Description Logics and earlier semantic network and frame systems, which represent the original heritage of the field. We delve into some of the key problems encountered with the older efforts. Subsequently, we introduce the basic features of DL languages and related reasoning techniques. DL languages are then viewed as the core of knowledge representation systems, considering both the structure of a DL knowledge base and its associated reasoning services. The development of some implemented knowledge representation systems based on Description Logics and the first applications built with such systems are then reviewed. Finally, we address the relationship of Description Logics to other fields of Computer Science.We also discuss some extensions of the basic representation language machinery; these include features proposed for incorporation in the formalism that originally arose in implemented systems, and features proposed to cope with the needs of certain application domains.

An intelligent personal assistant for task and time management

We describe an intelligent personal assistant that has been developed to aid a busy knowledge worker in managing time commitments and performing tasks. The design of the system was motivated by the complementary objectives of (1) relieving the user of routine tasks, thus allowing her to focus on tasks that critically require human problem-solving skills, and (2) intervening in situations where cognitive overload leads to oversights or mistakes by the user. The system draws on a diverse set of AI technologies that are linked within a Belief-Desire-Intention (BDI) agent system. Although the system provides a number of automated functions, the overall framework is highly user centric in its support for human needs, responsiveness to human inputs, and adaptivity to user working style and preferences.

A proof markup language for Semantic Web services

The Semantic Web is being designed to enable automated reasoners to be used as core components in a wide variety of Web applications and services. In order for a client to accept and trust a result produced by perhaps an unfamiliar Web service, the result needs to be accompanied by a justification that is understandable and usable by the client. In this paper, we describe the proof markup language (PML), an interlingua representation for justifications of results produced by Semantic Web services. We also introduce our Inference Web infrastructure that uses PML as the foundation for providing explanations of Web services to end users. We additionally show how PML is critical for and provides the foundation for hybrid reasoning where results are produced cooperatively by multiple reasoners. Our contributions in this paper focus on technological foundations for capturing formal representations of term meaning and justification descriptions thereby facilitating trust and reuse of answers from web agents.