Volker Haarslev

RACER System Description

RACER implements a TBox and ABox reasoner for the logic SHIQ. RACER was the first full-fledged ABox description logic system for a very expressive logic and is based on optimized sound and complete algorithms. RACER also implements a decision procedure for modal logic satisfiability problems (possibly with global axioms).

Theory and Application of Diagrams

This presentation will address the representation of geospatial information in the context of group work. The focus is on visual representations that mediate between human collaborators who are participating in a joint reasoning process, within a place and/or space-based problem context. The perspective developed for addressing the challenges involved builds upon the cognitive-semiotic approach outlined in How Maps Work, extending it to consider the issues that underlie creation of maps and related diagrams that work in a group work context. This context requires representations that depict not only geospatial information but also individual perspectives on that information, the process of negotiation among those perspectives, and the behaviors (work) of individuals participating in that negotiation. M . An d e rson , P. Ch e n g, an d V. Haarsl e v (E d s. ) : D i agram s 2000, LNAI 1889, p . 1, 2000. c

The RacerPro knowledge representation and reasoning system

RacerPro is a software system for building applications based on ontologies. The backbone of RacerPro is a description logic reasoner. It provides inference services for terminological knowledge as well as for representations of knowledge about individuals. Based on new optimization techniques and techniques that have been developed in the research field of description logics throughout the years, a mature architecture for typical-case reasoning tasks is provided. The system has been used in hundreds of research projects and industrial contexts throughout the last twelve years. W3C standards as well as detailed feedback reports from numerous users have influenced the design of the system architecture in general, and have also shaped the RacerPro knowledge representation and interface languages. With its query and rule languages, RacerPro goes well beyond standard inference services provided by other OWL reasoners.

On the Scalability of Description Logic Instance Retrieval

Practical description logic systems play an ever-growing role for knowledge representation and reasoning research even in distributed environments. In particular, the ontology layer of the often-discussed semantic web is based on description logics (DLs) and defines important challenges for current system implementations. The article introduces and evaluates optimization techniques for the instance retrieval problem w.r.t. the description logic

A Description Logic with Concrete Domains and a Role-forming Predicate Operator ∗

\mathcal{SHIQ}(\mathcal{D}_{n})^{-}

Exploiting Pseudo Models for TBox and ABox Reasoning in Expressive Description Logics

, which covers large parts of the Web Ontology Language (OWL). We demonstrate that sound and complete query engines for OWL-DL can be built for practically significant query classes. Experience with ontologies derived from database content has shown that it is often necessary to effectively solve instance retrieval problems with respect to huge amounts of data descriptions that make up major parts of ontologies. We present and analyze the main results about how to address this kind of scalability problem.

The Description Logic ALCNHR+ Extended with Concrete Domains: A Practically Motivated Approach

This article presents the description logic ALCRP(D) with concrete domains and a roleforming predicate operator as its prominent aspects. We demonstrate the feasibility of ALCRP(D) for reasoning about spatial objects and their qualitative spatial relationships and provide an appropriate concrete domain for spatial objects. The general signicance of ALCRP(D) is demonstrated by adding temporal reasoning to spatial and terminological reasoning using a combined concrete domain. The theory is motivated as a basis for knowledge representation and query processing in the domain of geographic information systems. In contrast to existing work in this domain, which mainly focuses either on conceptual reasoning or on reasoning about qualitative spatial relations, we integrate reasoning about spatial information with terminological reasoning.

Semantic web infrastructure for fungal enzyme biotechnologists

This paper investigates optimization techniques and data structures exploiting the use of so-called pseudo models. These techniques are applied to speed up TBox and ABox reasoning for the description logics ALCNHR+ and ALC(D). The advances are demonstrated by an empirical analysis using the description logic system RACE that implements TBox and ABox reasoning for ALCNHR+.

Consistency Testing: The RACE Experience

In this paper the description logic ALCNHR+(D)- is introduced. Prominent language features beyond conjunction, full negation, and quantifiers are number restrictions, role hierarchies, transitively closed roles, generalized concept inclusions, and concrete domains. As in other languages based on concrete domains (e.g. ALC(D)) a so-called existential predicate restriction is provided. However, compared to ALC(D) only features and no feature chains are allowed in this operator. This results in a limited expressivity w.r.t. concrete domains but is required to ensure the decidability of the language. We show that the results can be exploited for building practical description logic systems for solving e.g. configuration problems.

Formal semantics of visual languages using spatial reasoning

The FungalWeb Ontology seeks to support various data integration needs of enzyme biotechnology from inception to product roll. Serving as a knowledgebase for decision support, the conceptualization seeks to link fungal species with enzymes, enzyme substrates, enzyme classifications, enzyme modifications, enzyme related intellectual property, enzyme retail and applications. The ontology, developed in the OWL language, is the result of the integration of numerous biological database schemas, web accessible text resources and components of existing ontologies. We assess the quantity of implicit knowledge in the FungalWeb Ontology by analyzing the range of tags in the OWL files and along with other description logic (DL) computable metrics of the ontology, contrast it with other publicly available bio-ontologies. Thereafter, we demonstrate how the FungalWeb Ontology supports its broad remit required in fungal biotechnology by (i) presenting application scenarios (ii) presenting the conceptualizations of the ontological frame able to support these scenarios and (iii) suggesting semantic queries typical of a fungal enzymologist involved in product development. Recognizing the complexity of the ontology query process for the non-technical manager we introduce a simplified query tool, Ontoligent Interactive Query (OntoIQ) that allows the user to browse and build queries from a selection of query patterns and ontology content. The OntoIQ interface supports users not familiar with writing DL syntax allowing them access to the ontology with expressive description logic reasoning tools. Finally we discuss the challenges encountered during the development of semantic infrastructure for fungal enzyme biotechnologists.