Companies develop process models to explicitly describe their business operations. In the same time, business operations, business processes, must adhere to various types of compliance requirements. Regulations, e.g., Sarbanes Oxley Act of 2002, internal policies, best practices are just a few sources of compliance requirements. In some cases, non-adherence to compliance requirements makes the organization subject to legal punishment. In other cases, non-adherence to compliance leads to loss of competitive advantage and thus loss of market share. Unlike the classical domain-independent behavioral correctness of business processes, compliance requirements are domain-specific. Moreover, compliance requirements change over time. New requirements might appear due to change in laws and adoption of new policies. Compliance requirements are offered or enforced by different entities that have different objectives behind these requirements. Finally, compliance requirements might affect different aspects of business processes, e.g., control flow and data flow. As a result, it is infeasible to hard-code compliance checks in tools. Rather, a repeatable process of modeling compliance rules and checking them against business processes automatically is needed. This thesis provides a formal approach to support process design-time compliance checking. Using visual patterns, it is possible to model compliance requirements concerning control flow, data flow and conditional flow rules. Each pattern is mapped into a temporal logic formula. The thesis addresses the problem of consistency checking among various compliance requirements, as they might stem from divergent sources. Also, the thesis contributes to automatically check compliance requirements against process models using model checking. We show that extra domain knowledge, other than expressed in compliance rules, is needed to reach correct decisions. In case of violations, we are able to provide a useful feedback to the user. The feedback is in the form of parts of the process model whose execution causes the violation. In some cases, our approach is capable of providing automated remedy of the violation. / Firmen entwickeln Prozessmodelle um ihre Geschäftstätigkeit explizit zu beschreiben. Geschäftsprozesse müssen verschiedene Arten von Compliance-Anforderungen einhalten. Solche Compliance-Anforderungen entstammen einer Vielzahl von Quellen, z.B. Verordnung wie dem Sarbanes Oxley Act von 2002, interne Richtlinien und Best Practices. Die Nichteinhaltung von Compliance-Anforderungen kann zu gesetzlichen Strafen oder dem Verlust von Wettbewerbsvorteilen und somit dem Verlust von Marktanteilen führen. Im Gegensatz zum klassischen, domänen-unabhängigen Begriff der Korrektheit von Geschäftsprozessen, sind Compliance-Anforderungen domain-spezifisch und ändern sich im Laufe der Zeit. Neue Anforderungen resultieren aus neuen Gesetzen und der Einführung neuer Unternehmensrichtlinien. Aufgrund der Vielzahl der Quellen für Compliance-Anforderungen, können sie unterschiedliche Ziele verfolgen und somit widersprüchliche Aussagen treffen. Schließlich betreffen Compliance-Anforderungen verschiedene Aspekte von Geschäftsprozessen, wie Kontrollfluss- und Datenabhängigkeiten. Auf Grund dessen können Compliance-Prüfungen nicht direkt Hard-coded werden. Vielmehr ist ein Prozess der wiederholten Modellierung von Compliance-Regeln und ihrer anschließenden automatischen Prüfung gegen die Geschäftsprozesse nötig. Diese Dissertation stellt einen formalen Ansatz zur Überprüfung der Einhaltung von Compliance-Regeln während der Spezifikation von Geschäftsprozessen vor. Mit visuellen Mustern ist es möglich, Compliance-Regeln hinsichtlich Kontrollfluss- und Datenabhängigkeiten sowie bedingte Regeln zu spezifizieren. Jedes Muster wird in eine Formel der temporalen Logik abgebildet. Die Dissertation behandelt das Problem der Konsistenzprüfung zwischen verschiedenen Compliance-Anforderungen, wie sie sich aus unterschiedlichen Quellen ergeben können. Ebenfalls zeigt diese Dissertation, wie Compliance-Regeln gegen die Geschäftsprozesse automatisch mittels Model Checking geprüft werden. Es wird aufgezeigt, dass zusätzliche Domänen-Kenntnisse notwendig sind, um richtige Entscheidungen zu treffen. Der vorgestelle Ansatz ermöglicht nützliches Feedback für Modellierer im Fall eines Compliance-Verstoßes. Das Feedback wird in Form von Teilen des Prozessmodells gegeben, deren Ausführung die Verletzung verursacht. In einigen Fällen ist der vorgestellte Ansatz in der Lage, den Compliance-Verstoß automatisch zu beheben.

With development and impact of ICT, the method of work in many organizations has been becoming more collaborative and communicative, under which a number of organizations start to take corresponding strategies to achieve business goals and create more values. Managing Business Process is an effective and efficient way to improve productivity and performance of business activities from an organizational level. Business Process model, as a representation of Business Process, provides a big picture of Business Process, allowing organizations to acquire understanding on logical relationships among different business activities and to improve Business Process by various approaches. This study discusses the application of Business Process models on weakness identification which is related to the problem of excess inventory in supply chain with a qualitative method. It adopts three Business Process Modelling techniques to build Business Process models for a planning team involved with demand and supply planning, where four experts from the team participate in interview. The models are analyzed according to selected weakness patterns in order to identify the process weaknesses and link them with the causes of excess inventory. The result of this study gives a positive answer, which means the Business Process Models are capable to identify causes for the concrete problem of excess inventory by identifying process weaknesses.

De plus en plus les organisations adoptent les systèmes d'informations sensibles aux processus basés sur Cloud en tant qu'un environnement pour gérer et exécuter des processus dans le Cloud dans l'objectif de partager et de déployer leurs applications de manière optimale. Cela est particulièrement vrai pour les grandes organisations ayant des succursales opérant dans des différentes régions avec des processus considérablement similaires. Telles organisations doivent soutenir de nombreuses variantes du même processus en raison de la culture locale de leurs succursales, de leurs règlements, etc. Cependant, le développement d'une nouvelle variante de processus à partir de zéro est sujet à l'erreur et peut prendre beaucoup du temps. Motivés par le paradigme "la conception par la réutilisation", les succursales peuvent collaborer pour développer de nouvelles variantes de processus en apprenant de leurs processus similaires. Ces processus sont souvent hétérogènes, ce qui empêche une interopérabilité facile et dynamique entre les différentes succursales. Une variante de processus est un ajustement d'un modèle de processus afin de s'adapter d'une façon flexible aux besoins spécifiques. De nombreuses recherches dans les universités et les industries visent à faciliter la conception des variantes de processus. Plusieurs approches ont été développées pour aider les concepteurs de processus en recherchant des modèles de processus métier similaires ou en utilisant des modèles de référence. Cependant, ces approches sont lourdes, longues et sujettes à des erreurs. De même, telles approches recommandent des modèles de processus pas pratiques pour les concepteurs de processus qui ont besoin d'ajuster une partie spécifique d'un modèle de processus. En fait, les concepteurs de processus peuvent mieux développer des variantes de processus ayant une approche qui recommande un ensemble bien défini d'activités à partir d'un modèle de processus défini comme un fragment de processus. Les grandes organisations multi-sites exécutent les variantes de processus BP dans l'environnement Cloud pour optimiser le déploiement et partager les ressources communes. Cependant, ces ressources Cloud peuvent être décrites en utilisant des différents standards de description des ressources Cloud ce qui empêche l'interopérabilité entre les différentes succursales. Dans cette thèse, nous abordons les limites citées ci-dessus en proposant une approche basée sur les ontologies pour peupler sémantiquement une base de connaissance commune de processus et de ressources Cloud, ce qui permet une interopérabilité entre les succursales de l'organisation. Nous construisons notre base de connaissance en étendant les ontologies existantes. Ensuite, nous proposons une approche pour exploiter cette base de connaissances afin de supporter le développement des variantes BP. De plus, nous adoptons un algorithme génétique pour allouer d'une manière optimale les ressources Cloud aux BPs. Pour valider notre approche, nous développons deux preuves de concepts et effectuons des expériences sur des ensembles de données réels. Les résultats expérimentaux montrent que notre approche est réalisable et précise dans des cas d'utilisation réels / More and more organizations are adopting cloud-based Process-Aware Information Systems (PAIS) to manage and execute processes in the cloud as an environment to optimally share and deploy their applications. This is especially true for large organizations having branches operating in different regions with a considerable amount of similar processes. Such organizations need to support many variants of the same process due to their branches' local culture, regulations, etc. However, developing new process variant from scratch is error-prone and time consuming. Motivated by the "Design by Reuse" paradigm, branches may collaborate to develop new process variants by learning from their similar processes. These processes are often heterogeneous which prevents an easy and dynamic interoperability between different branches. A process variant is an adjustment of a process model in order to flexibly adapt to specific needs. Many researches in both academics and industry are aiming to facilitate the design of process variants. Several approaches have been developed to assist process designers by searching for similar business process models or using reference models. However, these approaches are cumbersome, time-consuming and error-prone. Likewise, such approaches recommend entire process models which are not handy for process designers who need to adjust a specific part of a process model. In fact, process designers can better develop process variants having an approach that recommends a well-selected set of activities from a process model, referred to as process fragment. Large organizations with multiple branches execute BP variants in the cloud as environment to optimally deploy and share common resources. However, these cloud resources may be described using different cloud resources description standards which prevent the interoperability between different branches. In this thesis, we address the above shortcomings by proposing an ontology-based approach to semantically populate a common knowledge base of processes and cloud resources and thus enable interoperability between organization's branches. We construct our knowledge base built by extending existing ontologies. We thereafter propose an approach to mine such knowledge base to assist the development of BP variants. Furthermore, we adopt a genetic algorithm to optimally allocate cloud resources to BPs. To validate our approach, we develop two proof of concepts and perform experiments on real datasets. Experimental results show that our approach is feasible and accurate in real use-cases

This dissertation focuses on the re-use of business process reference models, available in a business process model warehouse, to enable the definition of more comprehensive business requirements. It proposes a business process model warehouse framework to promote the re-use of multiple business process reference models and the flexible visualisation of business process models. The critical success factor for such a framework is that it should contribute to minimise to some extent the causes of inadequate business requirements. The proposed framework is based on an analogy with a data warehouse framework, consisting of the following components: usage of multiple business process reference models as source models, the conceptual design of a process to extract, load and transform multiple business process reference models into a repository, a description of repository functionality for managing enterprise architecture artefacts, and motivation of flexible visualisation of business process models to ensure more comprehensive business requirements. / Computer Science (School of Computing) / M.Sc. (Information Systems)

Submitted by Lukas Riehl Figueiredo null (lukas_rf@hotmail.com) on 2018-06-05T16:44:30Z No. of bitstreams: 1 Dissertacao-Lukas-Riehl-Figueiredo.pdf: 2667513 bytes, checksum: ea70d94af0366189c71508909d5f3ba7 (MD5) / Rejected by Elza Mitiko Sato null (elzasato@ibilce.unesp.br), reason: Solicitamos que realize correções na submissão seguindo as orientações abaixo: Problema 01) Na folha de aprovação deve constar a data(dia, mês e ano) da defesa, no seu arquivo está somente o ano. Lembramos que o arquivo depositado no repositório deve ser igual ao impresso, o rigor com o padrão da Universidade se deve ao fato de que o seu trabalho passará a ser visível mundialmente. Agradecemos a compreensão. on 2018-06-06T15:51:03Z (GMT) / Submitted by Lukas Riehl Figueiredo null (lukas_rf@hotmail.com) on 2018-06-06T21:57:37Z No. of bitstreams: 1 Dissertacao-Lukas-VF.pdf: 2667598 bytes, checksum: 032e5b83677ed9c2b780bd1c8401aa2e (MD5) / Approved for entry into archive by Elza Mitiko Sato null (elzasato@ibilce.unesp.br) on 2018-06-08T13:33:19Z (GMT) No. of bitstreams: 1 figueiredo_lr_me_sjrp.pdf: 2667598 bytes, checksum: 032e5b83677ed9c2b780bd1c8401aa2e (MD5) / Made available in DSpace on 2018-06-08T13:33:19Z (GMT). No. of bitstreams: 1 figueiredo_lr_me_sjrp.pdf: 2667598 bytes, checksum: 032e5b83677ed9c2b780bd1c8401aa2e (MD5) Previous issue date: 2018-02-01 / Modelos de processos de negócio têm sido utilizados em ambientes organizacionais para o entendimento da cadeia de processos, visando melhorias técnicas, gerenciais e estratégicas. Esses modelos abrangem variadas informações sobre os recursos utilizados e interações entre diferentes setores e pessoas, evidenciando interdependências entre os processos. Contudo, esses modelos podem apresentar problemas de legibilidade e dificuldades de navegação à medida em que se tornam extensos. A representação do conhecimento implícito é complexa e não está padronizada; as interdependências nem sempre são fáceis de serem compreendidas. O uso de ontologias tem aberto uma perspectiva complementar para mitigar esses problemas e prover processos com semânticas acessíveis por máquina. As ontologias contribuem para a conceituação e organização da informação embutida e desestruturada que se encontra presente nos processos de negócio e que deve ser explorada. As ontologias são utilizadas para estruturar o conhecimento implícito que está presente nos processos de negócio, possibilitando a compreensão desse conhecimento por máquina. As ontologias também contribuem para o alinhamento das visões das equipes de negócio e de Tecnologia da Informação da organização. Nesse contexto, este trabalho apresenta um processo sistemático para gerar uma ontologia a partir de um modelo de processos de negócio em BPMN v2.0, permitindo consultar informações sobre o modelo. Uma ferramenta denominada PM2ONTO foi então desenvolvida, visando gerar a ontologia em OWL automaticamente e disponibilizar uma interface para consultas predefinidas, elaboradas na linguagem SPARQL. Os modelos de processos de negócio devem ser exportados para arquivos em XPDL v2.2, os quais serão as entradas do sistema PM2ONTO. As ontologias resultantes ficam disponíveis em um banco de dados para consultas e também podem ser manipuladas por outras diferentes ferramentas. A avaliação do processo sistemático apresentado neste trabalho foi feita com base em estudos de caso, usando modelos de processos de negócio de diferentes áreas e diferentes níveis de complexidade. / Aiming technical, managerial and strategic improvements, business process models have been used in organizational environments to understand the process chain. Although these models may present readability problems and navigation difficulties as they become extensive, they can cover many information about resources and interactions between different sectors and people, showing interdependencies among the processes. Interdependencies are not always easy to understand because of its complex and not standardized knowledge. The use of ontologies has opened a complementary perspective to mitigate these problems and to provide processes with machine-accessible semantics. Also, they contribute in the conceptualization and organization of the embedded and unstructured information that is present in the business processes and that must be explored. In order to ease machine knowledge, ontologies are used to structure the implicit knowledge in business processes. They also contribute to the alignment of the organization's business and IT teams. In this context, this work presents a systematic process to generate an ontology from a business process model in BPMN v2.0, allowing to query information about the model. In this way, PM2ONTO tool was developed aiming to generate the ontology in OWL automatically and to provide an interface for predefined queries elaborated in the SPARQL language. Business process models should be exported to files in XPDL v2.2, which will be the inputs of the PM2ONTO system. The resulting ontologies stay available in a database for queries and can also be manipulated by other different tools. The systematic process evaluation presented in this work was made based on case studies, using business process models of different areas and different levels of complexity.

This dissertation focuses on the re-use of business process reference models, available in a business process model warehouse, to enable the definition of more comprehensive business requirements. It proposes a business process model warehouse framework to promote the re-use of multiple business process reference models and the flexible visualisation of business process models. The critical success factor for such a framework is that it should contribute to minimise to some extent the causes of inadequate business requirements. The proposed framework is based on an analogy with a data warehouse framework, consisting of the following components: usage of multiple business process reference models as source models, the conceptual design of a process to extract, load and transform multiple business process reference models into a repository, a description of repository functionality for managing enterprise architecture artefacts, and motivation of flexible visualisation of business process models to ensure more comprehensive business requirements. / Computer Science (School of Computing) / M.Sc. (Information Systems)