We take a healthcare knowledge management approach to represent the Clinical Pathway (CP) as workflows. We have developed a semantic representation of CP in terms of a CP ontology that outlines the different clinical processes, their properties, constraints and relationships, and is able to computerize a range of CP. To model business workflows we use the graphical Business Process Modeling Notation (BPMN) modeling language that generates a BPMN ontology. To represent a CP as a BPMN workflow, we have developed a semantic interoperability (mapping ontology) framework between the CP ontology and the BPMN ontology. The mapping ontology allows the alignment of relations between two ontologies and ensures that a clinical process defined in the CP ontology is mapped to a standard BPMN workflow element. We execute our BPMN-based CP in the Lombardi workflow engine, whereby users can view the execution of the CP and make the necessary adjustments.

Semantic web based decision support systems represent domain knowledge using ontologies that capture the domain concepts, their relationships and instances. Typically, decision support systems use a single knowledge model—i.e. a single ontology—which at times restricts the knowledge coverage to only select aspects of the domain knowledge. The integration of multiple knowledge models—i.e. multiple ontologies—provides a holistic knowledge model that encompasses multiple perspectives, orientations and instances. The challenge is the execution-time merging of multiple ontologies whilst maintaining knowledge consistency and procedural validity. Knowledge morphing aims at the intelligent merging of multiple computerized knowledge artifacts—represented as distinct ontological models—in order to create a holistic and networked knowledge model. In our research, we have investigated and developed a knowledge morphing framework—termed as OntoMorph—that supports ontology merging through: (1) Ontology Reconciliation whereby we harmonize multiple ontologies in terms of their vocabularies, knowledge coverage, and description granularities; (2) Ontology Merging where multiple reconciled ontologies are merged into a single merged ontology. To achieve ontology merging, we have formalized a set of semantically-defined merging criteria that determine ontology merge points, and describe the associated process-specific and knowledge consistency constraints that need to be satisfied to ensure consistent ontology merging; and (3) Ontology Execution whereby we have developed logic-based execution engines for both execution-time ontology merging and the execution of the merged ontology to infer knowledge-based recommendations. We have utilized OWL reasoning services, for efficient and decidable reasoning, to execute an OWL ontology. We have applied the OntoMorph framework for clinical decision support, more specifically to achieve the dynamic merging of multiple clinical practice guidelines in order to handle comorbid situations where a patient may have multiple diseases and hence multiple clinical guidelines are to be simultaneously operationalized. We have demonstrated the execution time merging of ontologically-modelled clinical guidelines, such that the decision support recommendations are derived from multiple, yet merged, clinical guidelines such that the inferred recommendations are clinically consistent. The thesis contributes new methods for ontology reconciliation, merging and execution, and presents a solution for execution-time merging of multiple clinical guidelines.

Ever increasing complexity of software systems, and distributed and dynamic nature of today’s enterprise level computing have initiated the demand for more self aware, flexible and robust systems, where human beings could delegate much of their work to software agents. The Semantic Web presents new opportunities for enabling, modeling, sharing and reasoning with knowledge available on the web. These opportunities are made possible through the formal representation of knowledge domains with ontologies. Semantic Web is a vision of World Wide Web (WWW) level knowledge representation system where each piece of information is equipped with well defined meaning; enabling software agents to understand and process that information. This, in turn, enables people and software agents to work in a more smooth and collaborative way. In this thesis we have first presented a detailed overview of Semantic web vision by describing its fundamental building blocks which constitutes famous layered architecture of Semantic Web. We have discussed the mile stones Semantic Web vision has achieved so far in the areas of research, education and industry and on the other hand we have presented some of the social, business and technological barriers in the way of this vision to become reality. We have also evaluated that how Semantic vision is effecting some of the current technological and research areas like Web Services, Software Agents, Knowledge Engineering and Grid Computing. In the later part of thesis we have focused on problem of ontology mapping for agents on semantic web. We have precisely defined the problem and categorized it on the basis of syntactic and semantic aspects. Finally we have produced a survey of the current state of the art in ontology mapping research. In the survey we have presented some of the selected ontology mapping systems and described their functionality on the basis of the way they approach the problem, their efficiency, effectiveness and the part of problem space they cover. We consider that the survey of current state of the art in ontology mapping will provide a solid basis for further research in this field. / Ever increasing complexity of software systems, and distributed and dynamic nature of today’s enterprise level computing have initiated the demand for more self aware, flexible and robust systems, where human beings could delegate much of their work to software agents. The Semantic Web presents new opportunities for enabling, modeling, sharing and reasoning with knowledge available on the web. These opportunities are made possible through the formal representation of knowledge domains with ontologies. Semantic Web is a vision of World Wide Web (WWW) level knowledge representation system where each piece of information is equipped with well defined meaning; enabling software agents to understand and process that information. This, in turn, enables people and software agents to work in a more smooth and collaborative way. In this thesis we have first presented a detailed overview of Semantic web vision by describing its fundamental building blocks which constitutes famous layered architecture of Semantic Web. We have discussed the mile stones Semantic Web vision has achieved so far in the areas of research, education and industry and on the other hand we have presented some of the social, business and technological barriers in the way of this vision to become reality. We have also evaluated that how Semantic vision is effecting some of the current technological and research areas like Web Services, Software Agents, Knowledge Engineering and Grid Computing. In the later part of thesis we have focused on problem of ontology mapping for agents on semantic web. We have precisely defined the problem and categorized it on the basis of syntactic and semantic aspects. Finally we have produced a survey of the current state of the art in ontology mapping research. In the survey we have presented some of the selected ontology mapping systems and described their functionality on the basis of the way they approach the problem, their efficiency, effectiveness and the part of problem space they cover. We consider that the survey of current state of the art in ontology mapping will provide a solid basis for further research in this field. / Folkparksvagen 18:01,372 40 Ronneby. Sweden

Na área de emparelhamento de ontologias, são utilizadas algumas métricas para avaliar os alinhamentos produzidos. As métricas baseadas em alinhamento têm como princípio básico confrontar um alinhamento proposto com um alinhamento de referência. Algumas destas métricas, entretanto, não têm alcançado êxito suficiente porque (i) não conseguem discriminar sempre entre um alinhamento totalmente errado e um quase correto; e (ii) não conseguem estimar o esforço do usuário para refinar o alinhamento resultante. Este trabalho tem como objetivo apresentar uma nova abordagem para avaliar os alinhamentos de ontologias. A nossa abordagem apresenta uma métrica na qual utilizamos as próprias consultas normalmente já realizadas nas ontologias originais para julgar a qualidade do alinhamento proposto. Apresentamos também alguns resultados satisfatórios de nossa abordagem em relação às outras métricas já existentes e largamente utilizadas. / In the ontology matching field, different metrics are used to evaluate the resulting alignments. Metrics based on alignment adopt the basic principle of verifying a proposed alignment against a reference alignment. Some of these metrics do not achieve good results because (i) they cannot always distinguish between a totally wrong alignment and one which is almost correct; and (ii) they cannot estimate the effort for the user to refine the resulting alignment. This work aims to present a new approach to evaluate ontology alignments. Our approach presents a measure that uses the usual queries in the original ontologies to assess the quality of the proposed alignment. We also present some satisfactory results of our approach with regard to widely used metrics.

This thesis establishes a connection between GOMMA and STROMA – both are tools of ontology processing. Consequently, a new workflow of denoting a set of correspondences with five semantic relation types has been implemented. Such a rich denotation is scarcely discussed within the literature. The evaluation of the denotation shows that trivial correspondences are easy to recognize (tF > 90). The challenge is the denotation of non-trivial types ( 30 < ntF < 70). A prerequisite of the implemented workflow is the extraction of semantic relations between concepts. These relations represent additional background knowledge for the enrichment tool STROMA and are integrated to the repository SemRep which is accessed by this tool. Thus, STROMA is able to calculate a semantic type more precisely. UMLS was chosen as a biomedical knowledge source because it subsumes many different ontologies of this domain and thus, it represents a rich resource. Nevertheless, only a small set of relations met the requirements which are imposed to SemRep relations. Further studies may analyze whether there is an appropriate way to integrate the missing relations as well. The connection of GOMMA with STROMA allows the semantic enrichment of a biomedical mapping. As a consequence, this thesis enlightens two subjects of research. First, STROMA had been tested with general ontologies, which models common sense knowledge. Within this thesis, STROMA was applied to domain ontologies. Studies have shown that overall, STROMA was able to treat such ontologies as well. However, some strategies for the enrichment process are based on assumption which are misleading in the biomedical domain. Consequently, further strategies are suggested in this thesis which might improve the type denotation. These strategies may lead to an optimization of STROMA for biomedical data sets. A more thorough analysis will review their scope, also beyond the biomedical domain. Second, the established connection may lead to deeper investigations about advantages of semantic enrichment in the biomedical domain as an enriched mapping is returned. Despite heterogeneity of source and target ontology, such a mapping results in an improved interoperability at a finer level of granularity. The utilization of semantically rich correspondences in the biomedical domain is a worthwhile focus for future research.

M. Tech. (Information Technology, Department of Information and Communications Technology, Faculty of Applied an Computer Sciences), Vaal University of Technolog / One of the main research topics in Semantic Web is the semantic extraction of knowledge stored in relational databases through ontologies. This is because ontologies are core components of the Semantic Web. Therefore, several tools, algorithms and frameworks are being developed to enable the automatic conversion of relational databases into ontologies. Ontologies produced with these tools, algorithms and frameworks needs to be valid and competent for them to be useful in Semantic Web applications within the target knowledge domains. However, the main challenges are that many existing automatic ontology construction tools, algorithms, and frameworks fail to address the issue of ontology verification and ontology competency evaluation. This study investigates possible solutions to these challenges. The study began with a literature review in the semantic web field. The review let to the conceptualisation of a framework for semantic knowledge extraction to deal with the abovementioned challenges. The proposed framework had to be evaluated in a real life knowledge domain. Therefore, a knowledge domain was chosen as a case study. The data was collected and the business rules of the domain analysed to develop a relational data model. The data model was further implemented into a test relational database using Oracle RDBMS. Thereafter, Protégé plugins were applied to automatically construct ontologies from the relational database. The resulting ontologies are further validated to match their structures against existing conceptual database-to-ontology mapping principles. The matching results show the performance and accuracy of Protégé plugins in automatically converting relational databases into ontologies. Finally, the study evaluated the resulting ontologies against the requirements of the knowledge domain. The requirements of the domain are modelled with competency questions (CQs) and mapped to the ontology using SPARQL queries design, execution and analysis against users’ views of CQs answers. Experiments show that, although users have different views of the answers to CQs, the execution of the SPARQL translations of CQs against the ontology does produce outputs instances that satisfy users’ expectations. This indicates that Protégé plugins generated ontology from relational database embodies domain and semantic features to be useful in Semantic Web applications.

In advent of the Semantic Web and recent standardization efforts, Ontology has quickly become a popular and core semantic technology. Ontology is seen as a solution provider to knowledge based systems. It facilitates tasks such as knowledge sharing, reuse and intelligent processing by computer agents. A key problem addressed by Ontology is the semantic interoperability problem. Interoperability in general is a common problem in different domain applications and semantic interoperability is the hardest and an ongoing research problem. It is required for systems to exchange knowledge and having the meaning of the knowledge accurately and automatically interpreted by the receiving systems. The innovation is to allow knowledge to be consumed and used accurately in a way that is not foreseen by the original creator. While Ontology promotes semantic interoperability across systems by unifying their knowledge bases through consensual understanding, common engineering and processing practices, it does not solve the semantic interoperability problem at the global level. As individuals are increasingly empowered with tools, ontologies will eventually be created more easily and rapidly at a near individual scale. Global semantic interoperability between heterogeneous ontologies created by small groups of individuals will then be required. Ontology mapping is a mechanism for providing semantic bridges between ontologies. While ontology mapping promotes semantic interoperability across ontologies, it is seen as the solution provider to the global semantic interoperability problem. However, there is no single ontology mapping solution that caters for all problem scenarios. Different applications would require different mapping techniques. In this thesis, we analyze the relations between ontology, semantic interoperability and ontology mapping, and promote an ontology-based semantic interoperability solution. We propose a novel ontology mapping approach namely, OntoMogic. It is based on first order logic and model theory. OntoMogic supports approximate mapping and produces structures (approximate entity correspondence) that represent alignment results between concepts. OntoMogic has been implemented as a coherent system and is applied in different application scenarios. We present case studies in the network configuration, security intrusion detection and IT governance & compliance management domain. The full process of ontology engineering to mapping has been demonstrated to promote ontology-based semantic interoperability.

<p>Nowadays, more and more companies use Enterprise Models to integrate and coordinate their business processes with the aim of remaining competitive on the market. Consequently, Enterprise Models play a critical role in this integration enabling to improve the objectives of the enterprise, and ways to reach them in a given period of time. Through Enterprise Models, companies are able to improve the management of their operations, actors, processes and also to improve communication within the organisation.</p><p>This thesis describes another use of Enterprise Models. In this work, we intend to apply Enterprise Models as interface for information searching. The underlying needsfor this project lay in the fact that we would like to show that Enterprise Models canbe more than just models but it can be used in a more dynamic way which is through a software program for information searching. The software program aimed at, first,extracting the information contained in the Enterprise Models (which are stored into aXML file on the system). Once the information is extracted, it is used to express a query which will be sent into a search engine to retrieve some relevant document to the query and return them to the user.</p><p>The thesis was carried out over an entire academic semester. The results of this workare a report which summarizes all the knowledge gained into the field of the study. A software has been built to serve as a proof of testing the theories.</p>

This work focuses on the axiomatized relationships between different ontologies of varying levels of expressivity. Motivated by experiences in the decomposition of first-order logic ontologies, we partially decompose the Descriptive Ontology for Linguistic and Cognitive Engineering (DOLCE) into modules. By leveraging automated reasoning tools to semi-automatically verify the modules, we provide an account of the meta-theoretic relationships found between DOLCE and other existing ontologies. As well, we examine the composition process required to determine relationships between DOLCE modules and the Process Specification Language (PSL) ontology. Then, we propose an ontology based on the semantically-weak Computer Integrated Manufacturing Open System Architecture (CIMOSA) framework by augmenting its constructs with terminology found in PSL. Finally, we attempt to map two semantically-weak product ontologies together to analyze the applications of ontology mappings in e-commerce.

This work focuses on the axiomatized relationships between different ontologies of varying levels of expressivity. Motivated by experiences in the decomposition of first-order logic ontologies, we partially decompose the Descriptive Ontology for Linguistic and Cognitive Engineering (DOLCE) into modules. By leveraging automated reasoning tools to semi-automatically verify the modules, we provide an account of the meta-theoretic relationships found between DOLCE and other existing ontologies. As well, we examine the composition process required to determine relationships between DOLCE modules and the Process Specification Language (PSL) ontology. Then, we propose an ontology based on the semantically-weak Computer Integrated Manufacturing Open System Architecture (CIMOSA) framework by augmenting its constructs with terminology found in PSL. Finally, we attempt to map two semantically-weak product ontologies together to analyze the applications of ontology mappings in e-commerce.