OWL DL Research Articles

REA-based Enterprise Business Domain Ontology Construction

Business domain ontology construction is of great significance to improving business modeling and knowledge management. B ased on REA business process model ing method and integrated with enterprise strategy information, the paper proposes a REA-based two- layer enterprise business information architecture. And then the business domain ontology infrastructure is constructed in OWL DL language. To demonstrate and implement the method and architecture, an example of t obacco trading company is taken. The proposed architecture abstracts enterprise business information from strategic and operational level, covering the main business elements of enterprise operation . By adopting the business domain ontology the paper provide s a foundation for the conservation and reuse of business modeling and improves enterprise business modeling knowledge management .

Construct Ontology-based Enterprise Information Metadata Framework

The standardization and unification of metadata has a significant impact on enterprise’s information integration and sharing. In this paper, information engineering and cluster analysis method is used to define the concepts and relationships of enterprises business meta-data, after that an algorithm is designed to map meta-data to OWL DL ontology and construct ontology-based enterprise information meta-data framework. The proposed framework can unify the definition of enterprise business information and provide a basis for information exchange and system interoperation, as well as provide a premise for knowledge management.

Formal semantics-preserving translation from fuzzy ER model to fuzzy OWL DL ontology

Ontology is an important part of the W3C standards for the Semantic Web, and how to quickly and cheaply construct Web ontologies has become a key technology to enable the Semantic Web. However, information imprecision and uncertainty exist in many real-world applications, thus constructing fuzzy ontology by extracting domain knowledge from fuzzy database models (e.g., fuzzy ER model) can profitably support fuzzy ontology development. In this paper, we propose an approach for constructing fuzzy ontology from fuzzy ER model, in which the fuzzy ontology consists of fuzzy ontology structure and instances. Firstly, we give the formal definition and the semantics of fuzzy ER models. Then, we introduce the fuzzy extension of ontology language OWL DL, i.e., fuzzy OWL DL. Based on the fuzzy OWL DL, a kind of fuzzy ontology called fuzzy OWL DL ontology is presented. Furthermore, we consider the fuzzy ER schema and the corresponding database instances, and translate them into the fuzzy ontology structure and the fuzzy ontology instances, respectively. Finally, since a fuzzy OWL DL ontology is equivalent to a fuzzy Description Logic f-SHOIN(D) knowledge base, how the reasoning problems of fuzzy ER models (e.g., satisfiability, subsumption, and redundancy) may be reduced to reasoning on f-SHOIN(D) knowledge bases is investigated, which will further contribute to constructing fuzzy OWL DL ontology that exactly meet application's needs. Of course, the correctness of the translation and reasoning problems are proved completely.

SSWAP: A Simple Semantic Web Architecture and Protocol for semantic web services.

BackgroundSSWAP (Simple Semantic Web Architecture and Protocol; pronounced "swap") is an architecture, protocol, and platform for using reasoning to semantically integrate heterogeneous disparate data and services on the web. SSWAP was developed as a hybrid semantic web services technology to overcome limitations found in both pure web service technologies and pure semantic web technologies.ResultsThere are currently over 2400 resources published in SSWAP. Approximately two dozen are custom-written services for QTL (Quantitative Trait Loci) and mapping data for legumes and grasses (grains). The remaining are wrappers to Nucleic Acids Research Database and Web Server entries. As an architecture, SSWAP establishes how clients (users of data, services, and ontologies), providers (suppliers of data, services, and ontologies), and discovery servers (semantic search engines) interact to allow for the description, querying, discovery, invocation, and response of semantic web services. As a protocol, SSWAP provides the vocabulary and semantics to allow clients, providers, and discovery servers to engage in semantic web services. The protocol is based on the W3C-sanctioned first-order description logic language OWL DL. As an open source platform, a discovery server running at (as in to "swap info") uses the description logic reasoner Pellet to integrate semantic resources. The platform hosts an interactive guide to the protocol at , developer tools at , and a portal to third-party ontologies at (a "swap meet").ConclusionSSWAP addresses the three basic requirements of a semantic web services architecture (i.e., a common syntax, shared semantic, and semantic discovery) while addressing three technology limitations common in distributed service systems: i.e., i) the fatal mutability of traditional interfaces, ii) the rigidity and fragility of static subsumption hierarchies, and iii) the confounding of content, structure, and presentation. SSWAP is novel by establishing the concept of a canonical yet mutable OWL DL graph that allows data and service providers to describe their resources, to allow discovery servers to offer semantically rich search engines, to allow clients to discover and invoke those resources, and to allow providers to respond with semantically tagged data. SSWAP allows for a mix-and-match of terms from both new and legacy third-party ontologies in these graphs.

Alignment of the UMLS semantic network with BioTop: methodology and assessment.

Motivation: For many years, the Unified Medical Language System (UMLS) semantic network (SN) has been used as an upper-level semantic framework for the categorization of terms from terminological resources in biomedicine. BioTop has recently been developed as an upper-level ontology for the biomedical domain. In contrast to the SN, it is founded upon strict ontological principles, using OWL DL as a formal representation language, which has become standard in the semantic Web. In order to make logic-based reasoning available for the resources annotated or categorized with the SN, a mapping ontology was developed aligning the SN with BioTop.Methods: The theoretical foundations and the practical realization of the alignment are being described, with a focus on the design decisions taken, the problems encountered and the adaptations of BioTop that became necessary. For evaluation purposes, UMLS concept pairs obtained from MEDLINE abstracts by a named entity recognition system were tested for possible semantic relationships. Furthermore, all semantic-type combinations that occur in the UMLS Metathesaurus were checked for satisfiability.Results: The effort-intensive alignment process required major design changes and enhancements of BioTop and brought up several design errors that could be fixed. A comparison between a human curator and the ontology yielded only a low agreement. Ontology reasoning was also used to successfully identify 133 inconsistent semantic-type combinations.Availability: BioTop, the OWL DL representation of the UMLS SN, and the mapping ontology are available at http://www.purl.org/biotop/.Contact: stschulz@uni-freiburg.de

Ontology-supported scientific data frameworks: The Virtual Solar-Terrestrial Observatory experience

We have developed a semantic data framework that supports interdisciplinary virtual observatory projects across the fields of solar physics, space physics and solar-terrestrial physics. This work required a formal, machine understandable representation for concepts, relations and attributes of physical quantities in the domains of interest as well as their underlying data representations. To fulfill this need, we developed a set of solar-terrestrial ontologies as formal encodings of the knowledge in the Ontology Web Language–Description Logic (OWL–DL) format. We present our knowledge representation and reasoning needs motivated by the context of Virtual Observatories, from fields spanning upper atmospheric terrestrial physics to solar physics, whose intent is to provide access to observational datasets. The resulting data framework is built upon semantic web methodologies and technologies and provides virtual access to distributed and heterogeneous sets of data as if all resources appear to be organized, stored and retrieved from a local environment. Our conclusion is that the combination of use case-driven, small and modular ontology development, coupled with free and open-source software tools and languages provides sufficient expressiveness and capabilities for an initial production implementation and sets the stage for a more complete semantic-enablement of future frameworks.

Employing description logics in Ambient Intelligence for modeling and reasoning about complex situations

Ambient Intelligence systems need to represent information about their environment and recognize relevant situations to perform appropriate actions proactively and autonomously. The context information gathered by these systems comes with imperfections such as incompleteness or incorrectness. These characteristics need to be handled gracefully by the Ambient Intelligence system. Moreover, the represented information must allow for a fast and reliable recognition of the current situation. To solve these problems we propose a method for situation modeling using the Description Logics based ontology language OWL DL and a framework for employing Description Logics reasoning services to recognize the current situation based on context. The benefits from the approach are manifold: the semantics of Description Logics allow for graceful handling of incomplete knowledge. The well-investigated reasoning services do not only allow recognizing the current situation, but also can add to the reliability of the overall system. Moreover optimized reasoning systems are freely available and ready to use. We underpin the feasibility of our approach by providing a case study based on a smart home application conducting an evaluation of different Description Logics reasoners with respect to our application ontology as well as a discussion of Description Logics systems in Ambient Intelligence.

FOAFing the music: Bridging the semantic gap in music recommendation

In this paper we give an overview of the Foafing the Music system. The system uses the Friend of a Friend (FOAF) and RDF Site Summary (RSS) vocabularies for recommending music to a user, depending on the user’s musical tastes and listening habits. Music information (new album releases and reviews, podcast sessions, audio from MP3 blogs, related artists’ news, and upcoming gigs) is gathered from thousands of RSS feeds. The presented system provides music discovery by means of: user profiling (defined in the user’s FOAF description), context-based information (extracted from music related RSS feeds) and content-based descriptions (extracted from the audio itself), based on a common ontology (OWL DL) that describes the music recommendation domain. The system is available at: http://foafing-the-music.iua.upf.edu.

On the Relationship between Description Logic-based and F-Logic-based Ontologies

Many popular ontology languages are based on (subsets of) first-order predicate logic, with classes represented by unary predicates and properties by binary predicates. Specifically, the SemanticWeb ontology language OWL DL is based on the Description Logic SHOIN. F-Logic is an ontology language which is also based on first-order logic, but classes and properties are modeled as terms rather than predicates. Our goal is to enable interoperation between predicate-based and F-Logic-based ontology languages. To this end, we define an intuitive translation from predicate-based ontologies to F-Logic ontologies and show that this translation preserves entailment for large classes of ontology languages, including most of OWL DL. Specifically, we define the class of equality-safe (E-safe) formulas, show that the Description Logic SHIQ is E-safe, and show that the translation preserves validity of E-safe formulas. We use these results to close the open problem of layering F-Logic programming on top of Description Logic Programs and we show that our results apply to HILOG, a syntactically higher-order, but semantically first-order language. Finally, we show that our results also apply to a meta-modeling extension for Description Logics (v-semantics).

Representing the NCI Thesaurus in OWL DL

The National Cancer Institute's NCI Thesaurus is a biomedical reference ontology. The NCI Thesaurus is represented using description logic, more specifically Ontylog, a description logic implemente...

The ontology of biological taxa

Motivation: The classification of biological entities in terms of species and taxa is an important endeavor in biology. Although a large amount of statements encoded in current biomedical ontologies is taxon-dependent there is no obvious or standard way for introducing taxon information into an integrative ontology architecture, supposedly because of ongoing controversies about the ontological nature of species and taxa.Results: In this article, we discuss different approaches on how to represent biological taxa using existing standards for biomedical ontologies such as the description logic OWL DL and the Open Biomedical Ontologies Relation Ontology. We demonstrate how hidden ambiguities of the species concept can be dealt with and existing controversies can be overcome. A novel approach is to envisage taxon information as qualities that inhere in biological organisms, organism parts and populations.Availability: The presented methodology has been implemented in the domain top-level ontology BioTop, openly accessible at http://purl.org/biotop. BioTop may help to improve the logical and ontological rigor of biomedical ontologies and further provides a clear architectural principle to deal with biological taxa information.Contact: stschulz@uni-freiburg.de

Constructing Integrated Corpus and Lexicon Models for Multi-Layer Annotation in OWL DL

We present a general approach to formally modelling corpora with multi-layered annotation in a typed logical representation language, OWL DL. By defining abstractions over the corpus data, we can generalise from a large set of individual corpus annotations, thereby inducing a lexicon model. The resulting combined corpus and lexicon model can be interpreted as a graph structure that offers flexible querying functionality beyond current XML-based query languages. Its powerful methods for characterising and checking consistency can be used for incremental model refinement. In addition, the formalisation in a graph-based structure offers the means of defining flexible lexicon views over the corpus data. These views can be tailored for linguistic inspection or to define clean interfaces with other linguistic resources. We illustrate our approach by applying it to the syntactically and semantically annotated SALSA/TIGER corpus, a collection of German newspaper text.

Combining answer set programming with description logics for the Semantic Web

We propose a combination of logic programming under the answer set semantics with the description logics SHIF ( D ) and SHOIN ( D ) , which underly the Web ontology languages OWL Lite and OWL DL, respectively. To this end, we introduce description logic programs (or dl-programs), which consist of a description logic knowledge base L and a finite set P of description logic rules (or dl-rules). Such rules are similar to usual rules in nonmonotonic logic programs, but they may also contain queries to L, possibly under default negation, in their bodies. They allow for building rules on top of ontologies but also, to a limited extent, building ontologies on top of rules. We define a suite of semantics for various classes of dl-programs, which conservatively extend the standard semantics of the respective classes and coincide with it in absence of a description logic knowledge base. More concretely, we generalize positive, stratified, and arbitrary normal logic programs to dl-programs, and define a Herbrand model semantics for them. We show that they have similar properties as ordinary logic programs, and also provide fixpoint characterizations in terms of (iterated) consequence operators. For arbitrary dl-programs, we define answer sets by generalizing Gelfond and Lifschitz's notion of a transform, leading to a strong and a weak answer set semantics, which are based on reductions to the semantics of positive dl-programs and ordinary positive logic programs, respectively. We also show how the weak answer sets can be computed utilizing answer sets of ordinary normal logic programs. Furthermore, we show how some advanced reasoning tasks for the Semantic Web, including different forms of closed-world reasoning and default reasoning, as well as DL-safe rules, can be realized on top of dl-programs. Finally, we give a precise picture of the computational complexity of dl-programs, and we describe efficient algorithms and a prototype implementation of dl-programs which is available on the Web.

Intelligent support of the preprocessing stage of engineering analysis using case-based reasoning

The process of engineering analysis, especially its preprocessing stage, comprises some knowledge-based tasks which influence the quality of the results greatly, require considerable level of expertise from an engineer; the support for these tasks by the contemporary CAE systems is limited. Analysis of the knowledge and reasoning involved in solving these tasks shows that the appropriate support for them by an automated system can be implemented using case-based reasoning (CBR) technology. In this paper the automated knowledge-based system for intelligent support of the preprocessing stage of engineering analysis in the contact mechanics domain is presented which employs the CBR mechanism. The case representation model is proposed which is centered on the structured qualitative model of a technical object. The model is formally represented by the Ontology Web Language Description Logics (OWL DL) ontology. Case retrieval and adaptation algorithms for this model are described which according to the initial tests perform better in the chosen domain then the known prototypes. The automated system is described and a sample problem-solving scenario from the contact mechanics domain is presented. Use of such system can potentially lower costs of engineering analysis by reducing the number of inappropriate decisions and analysis iterations and facilitate knowledge transfer from research into industry.

Representing the NCI Thesaurus in OWL DL: Modeling tools help modeling languages

The National Cancer Institute's (NCI) Thesaurus is a biomedical reference ontology. The NCI Thesaurus is represented using Description Logic, more specifically Ontylog, a Description logic implemented by Apelon, Inc. We are exploring the use of the DL species of the Web Ontology Language (OWL DL)-a W3C recommended standard for ontology representation-instead of Ontylog for representing the NCI Thesaurus. We have studied the requirements for knowledge representation of the NCI Thesaurus, and considered how OWL DL (and its implementation in Protégé-OWL) satisfies these requirements. In this paper, we discuss the areas where OWL DL was sufficient for representing required components, where tool support that would hide some of the complexity and extra levels of indirection would be required, and where language expressiveness is not sufficient given the representation requirements. Because many of the knowledge-representation issues that we encountered are very similar to the issues in representing other biomedical terminologies and ontologies in general, we believe that the lessons that we learned and the approaches that we developed will prove useful and informative for other researchers.

An ontology-based architecture for implementing semantic integration of supply chain management

Efficient supply chain management (SCM) requires consistent exchange and sharing of information semantics, which is often hindered by semantic clashes among heterogeneous applications. This paper proposes an ontology-based architecture for addressing the problem of semantic integration. A supply chain ontology (SCO) is developed by using the skeletal method to capture concepts and relationships common to SCM. Moreover, it is formally defined in OWL DL, a web-based ontology language, to serve as an interlingua for an architecture enabling information integration of SCM. Syntactic transformation between XML Schema and OWL in the architecture is implemented by syntactic translators that are developed by using XSLT. Furthermore, a rule-based approach is presented to map semantically similar terminologies between SCO and application ontologies with the aim of enabling semantic interoperability among applications in supply chains. The mapping rules are represented by SWRL, a rule description language that is independent of the rule languages specific to inference engines. In addition, a case study of a printer supply chain is illustrated to demonstrate the proposed methodology. Finally, a prototype system is developed using the Java platform to implement the SCO-based approach to semantic integration of SCM.

Foafing the Music: Bridging the Semantic Gap in Music Recommendation

In this paper we give an overview of the Foafing the Music system. The system uses the Friend of a Friend (FOAF) and RDF Site Summary (RSS) vocabularies for recommending music to a user, depending on the user’s musical tastes and listening habits. Music information (new album releases, podcast sessions, audio from MP3 blogs, related artists’ news and upcoming gigs) is gathered from thousands of RSS feeds. The presented system provides music discovery by means of: user profiling (defined in the user’s FOAF description), context based information (extracted from music related RSS feeds) and content based descriptions (extracted from the audio itself), based on a common ontology (OWL DL) that describes the music domain.

The bio-zen plus ontology

Bio-zen plus is an OWL DL ontology for the domain of biomedical research. It incorporates several existing Semantic Web ontologies: the DOLCE foundational ontology, the Simple Knowledge Organisation System (SKOS), the Semantically Interlinked Online Communities ontology (SIOC), FOAF ontology, the Dublin Core metadata schema and the Creative Commons Metadata schema. The contents of many biomedical taxonomies and ontologies are available as extension packages. Bio-zen plus is the first ontology in the domain of life sciences that is optimized for practical use on the Semantic Web and makes extensive use of existing Semantic Web ontologies.

Translating the Foundational Model of Anatomy into OWL

The Foundational Model of Anatomy (FMA) represents the result of manual and disciplined modeling of the structural organization of the human body. It is a tremendous resource in bioinformatics that facilitates sharing of information among applications that use anatomy knowledge. The FMA was developed in Protégé and the Protégé frames language is the canonical representation language for the FMA. We present a translation of the original Protégé frame representation of the FMA into OWL. Our effort is complementary to the earlier efforts to represent FMA in OWL and is focused on two main goals: (1) representing only the information that is explicitly present in the frames representation of the FMA or that can be directly inferred from the semantics of Protégé frames; (2) representing all the information that is present in the frames representation of the FMA, thus producing an OWL representation for the complete FMA. Our complete representation of the FMA in OWL consists of two components: an OWL DL component that contains the FMA constructs that are compatible with OWL DL; and an OWL Full component that imports the OWL DL component and adds the FMA constructs that OWL DL does not allow.

Expressive probabilistic description logics

The work in this paper is directed towards sophisticated formalisms for reasoning under probabilistic uncertainty in ontologies in the Semantic Web. Ontologies play a central role in the development of the Semantic Web, since they provide a precise definition of shared terms in web resources. They are expressed in the standardized web ontology language OWL, which consists of the three increasingly expressive sublanguages OWL Lite, OWL DL, and OWL Full. The sublanguages OWL Lite and OWL DL have a formal semantics and a reasoning support through a mapping to the expressive description logics SHIF ( D ) and SHOIN ( D ) , respectively. In this paper, we present the expressive probabilistic description logics P- SHIF ( D ) and P- SHOIN ( D ) , which are probabilistic extensions of these description logics. They allow for expressing rich terminological probabilistic knowledge about concepts and roles as well as assertional probabilistic knowledge about instances of concepts and roles. They are semantically based on the notion of probabilistic lexicographic entailment from probabilistic default reasoning, which naturally interprets this terminological and assertional probabilistic knowledge as knowledge about random and concrete instances, respectively. As an important additional feature, they also allow for expressing terminological default knowledge, which is semantically interpreted as in Lehmann's lexicographic entailment in default reasoning from conditional knowledge bases. Another important feature of this extension of SHIF ( D ) and SHOIN ( D ) by probabilistic uncertainty is that it can be applied to other classical description logics as well. We then present sound and complete algorithms for the main reasoning problems in the new probabilistic description logics, which are based on reductions to reasoning in their classical counterparts, and to solving linear optimization problems. In particular, this shows the important result that reasoning in the new probabilistic description logics is decidable/computable. Furthermore, we also analyze the computational complexity of the main reasoning problems in the new probabilistic description logics in the general as well as restricted cases.