Standards may be argued to be important enablers for achieving interoperability as they aim to provide unambiguous specifications for error-free exchange of documents and information. By implication, therefore, it is important to model and represent the concept of a standard in a clear, precise and unambiguous way. Although standards development organisations usually provide guidelines for the process of developing and approving standards, they are usually more concerned with administrative aspect of the process. As a consequence, the state-of-the-art lacks practical support for developing the structure and content of a standard specification. In short, there is no systematic development method currently available: (a) For developing the conceptual model underpinning a standard; and/or (b) to guide a group of stakeholders to develop a standard specification. Semantic interoperability is considered to be an essential factor for effective interoperation – the ability to achieve semantic interoperability effectively and efficiently being strongly equated with quality by some. Semantics require that the meaning of terms, their relationships and also the restrictions and rules in the standards should be clearly defined in the early stages of standard development and act as a basis for the latter stages. This research proposes that ontology can help standards developers and stakeholders to address the issues of improving conceptual models and providing a robust and shared understanding of the domain. This thesis presents OntoStanD, a comprehensive ontology-based standards development methodology, which utilises the best practices of the existing ontology creation methods. The potential value of OntoStanD is in providing a comprehensive, clear and unambiguous method for developing robust information standards, which are more test friendly and of higher quality. OntoStanD also facilitates standards conformance testing and change management, impacts interoperability and also assists in improved communication among the standards development team. Last, OntoStanD provides an approach that is repeatable, teachable and potentially general enough for creating any kinds of information standard.

Providing an interoperability infrastructure for Electronic Healthcare Records (EHRs) is on the agenda of many national and regional eHealth initiatives. Two important integration profiles have been specified for this purpose: the &quot / IHE Cross-enterprise Document Sharing (XDS)&quot / and the &quot / IHE Cross Community Access (XCA)&quot / . XDS describes how to share EHRs in a community of healthcare enterprises and XCA describes how EHRs are shared across communities. However, currently no solution addresses some of the important challenges of cross community exchange environments. The first challenge is scalability. If every community joining the network needs to connect to every other community, this solution will not scale. Furthermore, each community may use a different coding vocabulary for the same metadata attribute in which case the target community cannot interpret the query involving such an attribute. Another important challenge is that each community has a different patient identifier domain. Querying for the patient identifiers in another community using patient demographic data may create patient privacy concerns. Yet another challenge in cross community EHR access is the EHR interoperability since the communities may be using different EHR content standards.

Today, the application of information and communication technologies to healthcare is on the agenda of many countries. The main aim is to make Electronic Healthcare Records (EHR) of a patient accessible anywhere at any time to all authorized users. This is even valid in the cross-border case / the European Commission has published eHealth interoperability recommendations to the EU Member States, in which the RIDE Project contributed, for the purpose of an interoperable European Health Network. Interoperable cross-border clinical data exchange is an ambitious goal with some challenges, the most obvious one being the variety of standards. This issue gets more complicated with the locally developed standards and coding systems. Each country has its own set of standards and it is not reasonable to make all possible combinations of mappings among them during multi-party EHR exchange. Instead, what needs to be done is keeping the legacy infrastructures of the participants and agreeing on a set of common EHR standards and coding systems. Then, each country shall develop &quot / Adapters&quot / transforming local EHR instances to the commonly agreed formats which will most probably be based on widely accepted standards such as HL7 CDA. This approach enables the structure level interoperability. As the second step, in order to achieve semantic interoperability, coded terms from locally defined coding systems shall be translated to international counterparts. In this thesis, our methodology is confirmed on Turkey&#039 / s National Health Information System. &quot / Transmission Schemas&quot / are automatically transformed to HL7 v3 CDA R2 and CEN EN 13606 standard formats. The local coded terms are translated by developing a mapping platform based on Unified Medical Language System (UMLS).

The interoperability of the electronic documents exchanged in eBusiness applications is an important problem in industry. Currently, this problem is handled by the mapping experts who understand the meaning of every element in the involved document schemas and define the mappings among them which is a very costly and tedious process. In order to improve electronic document interoperability, the UN/CEFACT produced the Core Components Technical Specification (CCTS) which defines a common structure and semantic properties for document artifacts. However, at present, this document content information is available only through text-based search mechanisms and tools. In this thesis, the semantics of CCTS based business document standards is explicated through a formal, machine processable language as an ontology. In this way, it becomes possible to compute a harmonized ontology, which gives the similarities among document schema ontology classes of different document standards through both the semantic properties they share and the semantic equivalences established through reasoning. However, as expected, the harmonized ontology only helps discovering the similarities of structurally and semantically equivalent elements. In order to handle the structurally different but semantically similar document artifacts, heuristic rules are developed describing the possible ways of organizing simple document artifacts into compound artifacts as defined in the CCTS methodology. Finally, the equivalences discovered among document schema ontologies are used for the semi-automated generation of XSLT definitions for the translation of real-life document instances.

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.

The management process of chronic diseases is longitudinal in nature. Patient records in electronic format provide information at the point of care and support decision-making processes. In our research, we analyzed the clinical pragmatics of Chronic Disease Management (CDM) and formulated a knowledge model to develop Ontology-based EMR. Our research involved knowledge abstraction, knowledge modeling, and ontology engineering. We applied the Knowledge Management approach to knowledge sources including medical literature, the Chronic Care Model (CCM), CPR Ontology and HL-7 RIM. We studied CDM in detail to abstract conceptual knowledge involved in the process of CDM. The abstracted knowledge was modeled into a formal model called CD-EMR Model. We adapted Methontology and developed an OWL-based ontology from the CD-EMR Model. We evaluated the ontology by instantiating longitudinal clinical cases of chronic diseases. CD-EMR ontology allows (a) computerization of longitudinal patient records, (b) semantic interoperability, and (c) reasoning for clinical decision support.

Les travaux de recherche de cette thèse portent sur la modélisation sémantique des informations industrielles, dans une approche og cycle de vie fg , de gestion des informations. Dans ce type d'approche, lever le verrou lié à l'interopérabilité des modèles d'information est une condition sine qua non à un échange d'information sans perte de flux sémantique. Jusqu'alors, des méthodes d'unification étaient envisagées, reposant sur l'utilisation mutuelle de modèles standards, tels que la norme STEP par exemple. Cependant, l'unification fait face à des limites en termes d'expressivité des modèles, de rigidité, et de perte de sémantique. Afin de lever ces limites, les paradigmes de modélisation évoluent et se tournent vers les ontologies d'inférence, outils du web sémantique.Dans cette thèse, nous proposons un cadre de modélisation sémantique général et une méthodologie de mise en place de ce cadre, qui reposent sur l'utilisation d'ontologies d'inférence. L'application du cadre de modélisation à un cas d'étude industriel, issu de l'ingénierie nucléaire (plus particulièrement l'expression et l'exécution des règles métier), permet alors d'évaluer les apports et limites des ontologies en tant que paradigme de modélisation. Les limites les plus importantes que nous identifions sur l'Open World Assumption, le manque de langage de règles performant et le manque d'outils d'implémentation robustes pour des applications à large échelle. Le développement d'un démonstrateur pour le cas d'étude industriel permet finalement de tendre vers une solution mixte, où les ontologies sont utilisées localement, afin d'en exploiter les divers avantages de manière optimale. / The present research study deals with industrial information modelling in a lifecycle management approach. In this context, achieving semantic interoperability is an important issue to guaranty the quality of information storage, exchange and reuse. Current solutions are based on unification approaches and use standard models as shared information representation. However, unification approches suffer from a lack of expressivity and flexibility. To overcome this issue, ontologies are proposed as a new modelling paradigm in order to perform federativ interoperability.This research focuses on inference ontologies and investigates the use of those semantic web-based technologies for a large scale industrial application. An ontology-based framework and a modelling methodology are therefore proposed and evaluated on a industrial use case in the nuclear industry. The application raises modelling issues like the Open World Assumption, the lack of a real integrated rule approach, and the robustness of implementation tools. The industrial use case is implemented within a demonstrator, that finally allows to propose an hybrid solution, where ontologies are locally used.end{abstract}

In the context of military field, more and more international coalitions among allied forces have takenplace. Information from heterogeneous systems needs to be exchanged without misinterpretation so theinvolved participating actors can share a common situational awareness regarding certain data and/ormessages. This, in turn, requires the preservation of the intended meaning not only on the syntax,language, and representation level, but on a semantic level as well.The application domain of the Business Object Reference Ontology Program (BORO) method focuseson the development of ontological or semantic models for large complex operational applications,especially in the military context. It is chosen by FOI, the Swedish Defense Research Agency in thefield of Information Systems, to apply to their Semantic Interoperability (SI) project.The goal of this thesis is to investigate how BORO method can be implemented for aligning the dataand/or messages between the Swedish Armed Forces and other military organizations on a semanticlevel for the FOI SI project. To achieve this goal the design science research methodology is conductedthrough a series of steps. The analysis regarding the usability of BORO method for FOI to obtainsemantic interoperability in its project will be demonstrated as the result of this thesis, which can alsobe utilized as a reference for other military organizations when conducting activities of informationexchange.

A presente tese de Doutorado trata de investigar a aplicação da mineração de texto, para a construção de uma terminologia que atenda aos preceitos estipulados pela normalização, nacional e internacional, referente à constituição de um Registro Eletrônico em Saúde (RES). As normas internacionais estudadas pelo presente trabalho foram as seguintes: ISO 13606-1 e ISO TS 17117. O padrão internacional ISO 13606-1 especifica os modelos de referência para a construção de arquétipos que são a estrutura-base do RES. A especificação técnica ISO 17117 estipula a formatação de terminologias controladas para o âmbito da informática em saúde. Localmente, o trabalho analisou o relatório técnico ABNT/ISO TR 20514 que dá a definição, o escopo e o contexto para o RES e o relatório técnico ABNT/ISO TR 12309 que visa a garantir o desenvolvimento de terminologias padronizadas para a área da saúde. Vários trabalhos científicos demonstram que, para a construção do RES baseado em arquétipos, pesquisadores utilizam terminologias de mercado como o SNOMED CT e SNOMED RT. No caso do Brasil, não existe uma terminologia oficialmente desenvolvida regionalmente ou traduzida para o português do Brasil que suporte a criação de modelos de referência. Essa situação dificulta a implantação das normas nacional e internacional de padronização, citadas anteriormente. Nesse ambiente, a tese aqui apresentada construiu uma ontologia no domínio da especialidade de Radiologia e Diagnóstico por Imagem, tendo como base a aplicação de métodos de mineração de texto para compor uma terminologia eficiente e eficaz que atendesse às lacunas demonstradas. A aplicação de método de mineração de texto foi realizada em uma amostra de 2.566.358 de sujeitos-laudos, consistindo em sujeitos-laudos dos exames de Ressonância Magnética, Raios-X, Tomografia Computadorizada e Ultrassonografia de regiões anatômicas humanas. Com base nessa extração, foi construída uma ontologia contendo 5.859 termos-indivíduos, 20.994 axiomas e 15.084 axiomas lógicos. Essa ontologia foi desenvolvida utilizando o software Prótége em linguagem OWL. A partir da formalização da ontologia (terminologia), foram construídos Archetype Definition Language (ADL), para o componente INSTRUCTION para exame de imagem, e ADL para o componente COMPOSITION de Tomografia Computadorizada de Coluna Cervical, Ressonância Magnética de Cervical e Torácica e Ressonância Magnética de Carótida. O trabalho mostrou a aplicabilidade da mineração de texto para a geração de uma terminologia que desse suporte à criação de ADL, conforme preconizado na normativa da área de informática em saúde. / This Doctoral Thesis aim to investigate the application of text mining for the construction of a terminology that meets the procedures laid down for standardization, national and international, regarding the establishment of an Electronic Health Record (RES). International standards studied in this work were ISO 13606-1 and ISO TS 17117. The ISO 13606-1 international standard specifies the reference models for the construction of archetypes, which is the basis of the RES structure. The technical specification ISO 17117 provides the formatting of controlled terminology for the scope of health informatics. Locally, the paper analyzed the technical ABNT / ISO TR 20514 report, which gives the definition, scope and context for the RES and technical ABNT / ISO TR 12309 report aimed at ensuring the development of standardized terminology for the health sector. Several scientific studies have shown that for the construction of RES based on archetypes, researchers use market terminology such as SNOMED CT and SNOMED RT. In Brazil, there is no terminology officially developed regionally or translated into Portuguese-Brazilian who support the creation of reference models. This situation impedes the deployment of national and international standards of standardization mentioned above. In this environment, the thesis presented here built an ontology in the field of specialty of Radiology and Diagnostic Imaging based on the application of text mining methods to make efficient and effective terminology that meets the demonstrated shortcomings. The application of text mining method was performed on a sample of 2,566,358 of subject-report, consisting of subject-reports of examinations MRI, X-ray, CT and ultrasound of human anatomical regions. Based on this extraction was built an ontology containing 5,859 individuals terms, axioms 20,994 and 15,084 logical axioms. This ontology was developed using Protégé OWL language software. From the formalization of the ontology (terminology) were built Archetype Definition Language (ADL) for INSTRUCTION component for imaging examination, and ADL for COMPOSITION component of CT cervical spine, MRI Cervical and Thoracic and MRI Carotid. The study showed the applicability of text mining to generate terminology that supported the creation of ADL as recommended by rules in the IT sector in health.

Semantic interoperability within the health care sector requires that patient data be fully available and shared without ambiguity across participating health facilities. The need for the current research was based on federal stipulations that required health facilities provide complete and optimal care to patients by allowing full access to their health records. The ongoing discussions to achieve interoperability within the health care industry continue to emphasize the need for healthcare facilities to successfully adopt and implement Electronic Health Record (EHR) systems. Reluctance by the healthcare industry to implement these EHRs for the purpose of achieving interoperability has led to the current research problem where it was determined that there is no existing single data standardization structure that can effectively share and interpret patient data within heterogeneous systems. The current research used the design science research methodology (DSRM) to design and develop a master data standardization and translation (MDST) model that allowed seamless exchange of healthcare data among multiple facilities. To achieve interoperability through a common data standardization structure, where multiple independent data models can coexist, the translation mechanism incorporated the use of the Resource Description Framework (RDF). Using RDF, a universal exchange language, allowed for multiple data models and vocabularies to be easily combined and interrelated within a single environment thereby reducing data definition ambiguity. Based on the results from the research, key functional capabilities to effectively map and translate health data were documented. The research solution addressed two primary issues that impact semantic interoperability – the need for a centralized standards repository and a framework that effectively maps and translates data between various EHRs and vocabularies. Thus, health professionals have a single interpretation of health data across multiple facilities which ensures the integrity and validity of patient care. The research contributed to the field of design science development through the advancements of the underlying theories, phases, and frameworks used in the design and development of data translation models. While the current research focused on the development of a single, common information model, further research opportunities and recommendations could include investigations into the implementation of these types of artifacts within a single environment at a multi-facility hospital entity.