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Remodeling Clinical Examinations Using OWL∗

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Remodeling Clinical Examinations Using OWL∗ Representing Knowledge in Oral Medicine – Remodeling Clinical Examinations Using OWL∗ Technical Report HS-IKI-TR-06-009 School of Humanities and Informatics, University of Sk¨ovde Marie Gustafsson [email protected] School of Humanities and Informatics University of Sk¨ovde, Box 408, SE-541 28 Sk¨ovde, Sweden Department of Computer Science and Engineering Chalmers University of Technology, SE-412 96 G¨oteborg, Sweden Abstract This report describes the remodeling of the representation of clinical examinations in oral medicine, from the previous proprietary format used by the MedView project, to using the World Wide Web Consortium’s recommendations Web Ontology Language (OWL) and Resource Description Framework (RDF). This includes the representation of (1) ex- amination templates, (2) lists of values that can be included in individual examination records, and (3) aggregates of such values used for e.g., analyzing and visualizing data. It also includes the representation of (4) individual examination records. We describe how OWL and RDF are used to represent these different knowledge components of MedView, along with the design decisions made in the remodeling process. These design decisions are related to, among other things, whether or not to use the constructs of domain and range, appropriate naming in URIs, the level of detail to initially aim for, and appropriate use of classes and individuals. A description of how these new representations are used in the previous applications and code base is also given, as well as their use in the Swedish Oral Medicine Web (SOMWeb) online community. We found that OWL and RDF can be used to address most, but not all, of the requirements we compiled based on the limitations of the MedView knowledge model. Our experience in using OWL and RDF is that, while there is much useful support material available, there is some lack of support for important design decisions and best practice guidelines are still under development. At the same time, using OWL gives us access to a potentially beneficial array of externally developed tools and the ability to come back and refine the knowledge model after initial deployment. ∗The work presented in this report was supported by the Swedish Agency for Innovation Systems. 1 Contents 1 Introduction 4 1.1 Overview ...................................... 5 2 Knowledge Representation in Oral Medicine 5 2.1 MedView ...................................... 5 2.1.1 TheDefinitionalApproach . 6 2.1.2 Storing Templates and Values . 7 2.1.3 TreeFiles .................................. 8 2.1.4 ValueAggregates.............................. 8 2.2 Requirements for an Ontology for Oral Medicine . ........ 9 3 Ontologies, RDF, and OWL 9 3.1 Ontologies...................................... 9 3.2 W3C Recommendations for the Semantic Web . 10 3.2.1 RDF..................................... 10 3.2.2 OWL .................................... 11 3.2.3 Trade-offs in Making OWL . 12 3.3 ToolsforWorkingwithOWLandRDF . 13 3.3.1 Editors ................................... 13 3.3.2 Application Programming Interfaces . ..... 13 3.3.3 Visualizers ................................. 14 3.3.4 Reasoners.................................. 14 3.3.5 Validators.................................. 15 3.4 Reported Experiences in Using OWL and RDF . 15 3.4.1 OpenWorldAssumption ......................... 15 3.4.2 NoUniqueNamesAssumption . 16 3.4.3 Validation.................................. 17 3.4.4 NoSupportforDefaultReasoning . 19 3.4.5 ValueRanges ................................ 19 3.4.6 ReusingOtherOntologies . 20 3.4.7 Imports ................................... 20 3.4.8 UsingInstances............................... 20 3.4.9 TheXMLSyntax.............................. 21 3.4.10 UseofDomainandRange.. .. .. .. .. .. .. 21 3.4.11 OWL’sSublanguages. 22 3.4.12 Problems for Developers New to OWL . 23 4 Design and Development of the SOMWeb Ontologies 23 4.1 Relations between Structures of MedView and SOMWeb . ........ 24 4.2 DevelopmentProcess.. .. .. .. .. .. .. .. .. 24 4.3 Designing the Examination Template Ontologies . ......... 24 4.3.1 The Structure of the Examination Ontologies . ...... 26 4.3.2 DesignChoices ............................... 27 4.4 Designing the Value List Ontology . ..... 32 2 4.4.1 Structure of the Value List Ontology . 33 4.4.2 DesignChoices ............................... 36 4.5 Representing Individual Examinations . ........ 37 4.5.1 Validation.................................. 37 4.6 RepresentingAggregates. 38 4.7 End-userInput ................................... 39 5 Using the Ontologies 39 5.1 Constructing Input Forms from OWLExaminationTemplates. 40 5.2 MedViewDatahandling . .. .. .. .. .. .. .. .. 41 5.2.1 HandlingExaminations . 42 5.2.2 HandlingTerms .............................. 42 6 Discussion 43 6.1 Results in Relation to the Requirements for an OralMedicineOntology .............................. 43 6.2 OurExperiencesinUsingOWL. 44 6.3 Benefits and Constraints of Starting from an Existing Model ......... 46 6.4 End-User Control and Standardizations . ....... 46 6.5 StandardsinMedicine ............................. 47 6.5.1 Comparison with the openEHR Approach . 47 6.5.2 ExternalClassifications . 48 7 Conclusions 48 8 Future Work 49 A MedView XML Examination Template for Meeting Consultation 54 B SOMWeb OWL Examination Template for Meeting Consultation 55 C Part of the SOMWeb Value List 59 D Example Examination Instance 60 3 1 Introduction Basing clinical decisions on finding, evaluating, and using the latest research results is an essential premise of evidence-based medicine (EBM) [1]. A crucial part of the practice of EBM is the integration of the expertise of the individual clinicians with the best clinical evidence obtainable from external sources [2]. Processes necessary for EBM, such as the collection, analysis, validation, sharing, and harmonization of clinical knowledge, can in part be supported by information technology (IT). The MedView project [3] has aimed to provide IT-support for evidence-based oral medicine. This has been done by equipping the clinicians with a wide range of software tools, assisting in the various processes of EBM, and by providing a formal knowledge model on which to base these tools. However, as this model is only used within the MedView project, it is difficult to reuse external knowledge sources and to share the data collected by MedView tools with others. There is also a need to expand the current model and to reexamine how to best conceptualize examination data in oral medicine. Such an undertaking is also relevant for those areas of medicine that overlap with oral medicine. In knowledge representation, the term ontology is used to denote the definition of concepts and relations between them, for a given domain of interest. The Web Ontology Language1 (OWL) is a recommendation of the World Wide Web Consortium (W3C), along with the related Resource Description Framework2 (RDF). We want to investigate the development of ontologies in oral medicine using these recommendations, which will be studied by taking the previous representation of MedView as a starting point. The knowledge model of MedView includes the representation of (1) individual examination records, (2) examination templates describing the pattern from which the individual records are created and which are used in constructing user input forms, (3) value lists from which values can be chosen when filling out these forms, and (4) aggregates of values created and used when analyzing data from the examination records. Also, parts of the MedView applications will be adapted to handling the new OWL and RDF representations, which will also be used in the SOMWeb (Swedish Oral Medicine Web) online community. This online community serves as support for the discussion of interesting and difficult cases in oral medicine among geographically dispersed clinics in Sweden. The community is further described in [4]. In addition to the contributions of the developed ontologies, and the use of these in the online community, this work also serves as an experience report of using the RDF and OWL recommendations. In this report, we will refer to the original, definitional approach described in Sec. 2.1 as the MedView representation. The new OWL- and RDF-based representation, to be described in Sec. 4, will be denoted the SOMWeb representation. 1http://www.w3.org/2004/OWL 2http://www.w3.org/RDF 4 1.1 Overview We begin by describing features of the MedView representations in Sec. 2.1, followed by requirements for an ontology of oral medicine in Sec. 2.2. In Sec. 3, brief introductions to ontologies, RDF, and OWL are given, followed by a longer recount of others’ experiences in working with OWL. Section 4 gives details of the remodeling of the MedView knowledge model using OWL and RDF, for both the developed ontologies and the design decisions made. A description of how the ontologies are used in the datahandling of MedView applications is given in Sec. 5. In Sec. 6, the discussion, we compare the developed ontologies to the requirements of Sec. 2.2, as well as to standards for representing patient records and medical classifications. We also discuss our experiences in using OWL, the constraints and benefits of starting with an existing knowledge model and code base, and the trade-offs in maintaining user-control, while aspiring for standardization, reuse, and formal knowledge representation. Finally, in Sec. 7 we provide conclusions of this work and in Sec. 8 give suggestions for future work. 2 Knowledge
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