Bijan Parsia

Pellet: A practical OWL-DL reasoner

In this paper, we present a brief overview of Pellet: a complete OWL-DL reasoner with acceptable to very good performance, extensive middleware, and a number of unique features. Pellet is the first sound and complete OWL-DL reasoner with extensive support for reasoning with individuals (including nominal support and conjunctive query), user-defined datatypes, and debugging support for ontologies. It implements several extensions to OWL-DL including a combination formalism for OWL-DL ontologies, a non-monotonic operator, and preliminary support for OWL/Rule hybrid reasoning. Pellet is written in Java and is open source.

HTN planning for Web Service composition using SHOP2

Automated composition of Web Services can be achieved by using AI planning techniques. Hierarchical Task Network (HTN) planning is especially well-suited for this task. In this paper, we describe how HTN planning system SHOP2 can be used with OWL-S Web Service descriptions. We provide a sound and complete algorithm to translate OWL-S service descriptions to a SHOP2 domain. We prove the correctness of the algorithm by showing the correspondence to the situation calculus semantics of OWL-S. We implemented a system that plans over sets of OWL-S descriptions using SHOP2 and then executes the resulting plans over the Web. The system is also capable of executing information-providing Web Services during the planning process. We discuss the challenges and difficulties of using planning in the information-rich and human-oriented context of Web Services.

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.

Trust Networks on the Semantic Web

The so-called “Web of Trust” is one of the ultimate goals of the Semantic Web. Research on the topic of trust in this domain has focused largely on digital signatures, certificates, and authentication. At the same time, there is a wealth of research into trust and social networks in the physical world. In this paper, we describe an approach for integrating the two to build a web of trust in a more social respect. This paper describes the applicability of social network analysis to the semantic web, particularly discussing the multi-dimensional networks that evolve from ontological trust specifications. As a demonstration of algorithms used to infer trust relationships, we present several tools that allow users to take advantage of trust metrics that use the network.

Automating DAML-S web services composition using SHOP2

The DAML-S Process Model is designed to support the application of AI planning techniques to the automated composition of Web services. SHOP2 is an Hierarchical Task Network (HTN) planner well-suited for working with the Process Model. We have proven the correspondence between the semantics of SHOP2 and the situation calculus semantics of the Process Model. We have also implemented a system which soundly and completely plans over sets of DAML-S descriptions using a SHOP2 planner, and then executes the resulting plans over the Web. We discuss the challenges and difficulties of using SHOP2 in the information-rich and human-oriented context of Web services.

Swoop: A Web Ontology Editing Browser

In this paper, we describe Swoop, a hypermedia inspired Ontology Browser and Editor based on OWL, the recently standardized Web-oriented ontology language. After discussing the design rationale and architecture of Swoop, we focus mainly on its features, using illustrative examples to highlight its use. We demonstrate that with its Web-metaphor, adherence to OWL recommendations and key unique features, such as Collaborative Annotation using Annotea, Swoop acts as a useful and efficient Web Ontology development tool. We conclude with a list of future plans for Swoop, that should further increase its overall appeal and accessibility.

Finding all justifications of OWL DL entailments

Finding the justifications of an entailment (that is, all the minimal set of axioms sufficient to produce an entailment) has emerged as a key inference service for the Web Ontology Language (OWL). Justifications are essential for debugging unsatisfiable classes and contradictions. The availability of justifications as explanations of entailments improves the understandability of large and complex ontologies. In this paper, we present several algorithms for computing all the justifications of an entailment in an OWL-DL Ontology and show, by an empirical evaluation, that even a reasoner independent approach works well on real ontologies.

Debugging OWL ontologies

As an increasingly large number of OWL ontologies become available on the Semantic Web and the descriptions in the ontologies become more complicated, finding the cause of errors becomes an extremely hard task even for experts. Existing ontology development environments provide some limited support, in conjunction with a reasoner, for detecting and diagnosing errors in OWL ontologies. Typically these are restricted to the mere detection of, for example, unsatisfiable concepts. We have integrated a number of simple debugging cues generated from our description logic reasoner, Pellet, in our hypertextual ontology development environment, Swoop. These cues, in conjunction with extensive undo/redo and Annotea based collaboration support in Swoop, significantly improve the OWL debugging experience, and point the way to more general improvements in the presentation of an ontology to new users.

The National Cancer Institute's thésaurus and ontology

The NCI Thysaurus is a public domain description logic-based terminology produced by the National Cancer Institute, and distributed as a component of the NCI Center for Bioinformatics caCORE distribution. It is deep and complex compared to most broad clinical vocabularies, implementing rich semantic interrelationships between the nodes of its taxonomies. The semantic relationships in the Thysaurus are intended to facilitate translational research and to support the bioinformatics infrastructure of the Institute.

Debugging unsatisfiable classes in OWL ontologies

As an increasingly large number of OWL ontologies become available on the Semantic Web and the descriptions in the ontologies become more complicated, finding the cause of errors becomes an extremely hard task even for experts. Existing ontology development environments provide some limited support, in conjunction with a reasoner, for reporting errors in OWL ontologies. Typically, these are restricted to the mere detection of, for example, unsatisfiable concepts. However, the diagnosis and resolution of the bug is not supported at all. For example, no explanation is given as to why the error occurs (e.g., by pinpointing the root clash, or axioms in the ontology responsible for the clash) or how dependencies between classes cause the error to propagate (i.e., by distinguishing root from derived unsatisfiable classes). In the former case, information from the internals of a description logic tableaux reasoner can be extracted and presented to the user (glass box approach); while in the latter case, the reasoner can be used as an oracle for a certain set of questions and the asserted structure of the ontology can be used to help isolate the source of the problems (black box approach). Based on the two approaches, we have integrated a number of debugging cues generated from our reasoner, Pellet, in our hypertextual ontology development environment, Swoop. A conducted usability evaluation demonstrates that these debugging cues significantly improve the OWL debugging experience, and point the way to more general improvements in the presentation of an ontology to users.