Enabling SmartWorkflows over heterogeneous ID-sensing technologies

Sensing technologies in mobile devices play a key role in reducing the gapbetween the physical and the digital world. The use of automatic identification capabilitiescan improve user participation in business processes where physical elements are involved(Smart Workflows). However, identifying all objects in the user surroundings does notautomatically translate into meaningful services to the user. This work introduces Parkour,an architecture that allows the development of services that match the goals of each ofthe participants in a smart workflow. Parkour is based on a pluggable architecture thatcan be extended to provide support for new tasks and technologies. In order to facilitatethe development of these plug-ins, tools that automate the development process are alsoprovided. Several Parkour-based systems have been developed in order to validate theapplicability of the proposal

Desarrollo de procesos de negocio móviles adaptados a la obtrusividad

Los procesos de negocio pueden beneficiarse de una mayor integración de los elementos físicos, mediante el uso de tecnologías de identificación automática. Un ejemplo de ella es el uso de la Identificación por Radio Frecuencia (RFID), con la cual se consigue interconectar objetos del mundo real, con servicios de información digital, en lo que se conoce como Internet de las Cosas (Internet of Things). En este trabajo se aborda la construcción de sistemas de soporte a procesos de negocio en el contexto de la Internet de las Cosas, partiendo de la descripción del proceso y de la obtrusividad requerida en el desarrollo de sus tareas, para obtener una solución informática basada software que dé el soporte adecuado al proceso. Esta tesis propone el uso de un marco conceptual para clasificar los tipos de interacción requeridos para completar las tareas del proceso de negocio, y así obtener el nivel de obtrusividad adecuado para el sistema. En particular, se aborda el desarrollo de estos sistemas aprovechando las capacidades avanzadas para la detección de objetos del mundo real que poseen los dispositivos móviles actuales. Finalmente, se definió un caso de estudio para probar la aplicabilidad de la propuesta y su implementación en entornos móviles.Martínez Arenas, RC. (2009). Desarrollo de procesos de negocio móviles adaptados a la obtrusividad. http://hdl.handle.net/10251/11942Archivo delegad

Enabling integration and aggregation of context information into WS-BPEL processes

Previously, techniques of Context-Aware Computing were limited only to small scale monolithic applications due to the lack of standardized technologies which could support interoperability of services owned by different organizations. The advancement in Service-Oriented Computing technology allowed autonomous and heterogeneous applications to be exposed as Web Services and interconnected into service compositions exploiting well-agreed interfaces, protocols and message formats. The Web Service Business Process Execution Language (WS-BPEL) is the de-facto standard for composing reusable Web services. To enable handling of context information in applications, context information has to be made available within service compositions; hence, integrated in WS-BPEL processes. Through this means, new innovative context-enriched services can be built and provided using the convergence of context-aware computing and workflow technology. In this diploma thesis, context information provided by the C-CAST Context Management Framework and Google Maps Web services, is integrated into WS-BPEL, and business modelers are supported with the creation of context-based compositions. After surveying some of the current best practice and relevant literature in this area, this thesis presents a solution to this problem based on the Integration Process Pattern work previously done at the Institute of Architecture of Application Systems at the University of Stuttgar

Semantic manipulation and business context in big data analytics

Business organisations receive a huge amount of data from many sources every day. These data are known as big data. Since they are mostly unstructured, big data creates a complex problem of how to capture, manage, analyse and then derive meaningful information from them. To deal with the challenges that big data has brought, this research proposes a new technique in big data analytics in the business area to integrate semantically meaningful information relevant to textual queries and business context. To achieve this aim, this study makes three major related contributions. Firstly, the relationship between business processes and strategies is established using the concept of a rule-based inference model via facts and annotations. This relationship is required to determine the importance of a big data query for a business organisation. Secondly, we introduce approaches to determine the significance level of a query, by incorporating the processstrategy relationship, process contributions and priority of business strategies. Thirdly, the proposed data analytic technique embeds business context into the bedrock of data collection and analysis process. The first two contributions were implemented using Python programming language including the Pyke package (Pyke is built in the Python environment and has an artificial intelligence tool for the development of expert systems) and their performances were analysed based on a business use case. The last contribution was implemented mainly in the Hadoop and Java programs. Results show that the first contribution successfully establishes the processstrategy relationship, the second calculates the significance level of a query in relation to a business organisation, while the third reveals the huge impact of query significance level and business context on big data collection and captures deep business insights.Doctor of Philosoph

Resource-driven processes : concept, use, and incorporation

Reaching organizational goals requires executing business processes. Modeling, using, and improving existing knowledge about business processes establishes organizational best practices. A common method for this is accomplished in an activity-oriented way by modeling, using, and improving business processes based on recurring activities and their order. Furthermore, modeled activities and their coordination can be automated with the help of IT infrastructures to increase automation and support for actors. Unfortunately, activities and their order in business processes are not always (i) foreseeable at modeling time or (ii) repeated in different executions. This variation of activities and their order among business processes decreases the usefulness of activity-oriented modeling approaches and raises the need for another approach to (i) support such business processes and (ii) reproduce desired outcomes. In addition, this need is intensified by increasing demands toward individualized products and solutions, as each product and solution can require custom-tailored activities in a different order. In this work, we introduce a resource-driven approach for modeling and executing business processes. Our approach relies on automatically allocated interrelated resources for supporting actors participating in business processes and reproducing their desired outcomes. To create definitions of business processes in a resource-driven way, we present a formal resource-driven process modeling language capable of specifying business processes in terms of their goals, capabilities, and interrelated resources. To evaluate and validate our approach, we conducted a survey with 416 participants. Results of the survey confirm our claims regarding (i) increased support for actors of business processes and (ii) the reproducibility of their desired outcomes using our resource-driven approach. For using resource-driven processes in organizations, we present a resource-driven process management life cycle involving four phases. The first phase of the life cycle describes steps needed for preparing an IT infrastructure enabling the steps conducted in other phases of the life cycle. In the second phase, business experts model resource-driven processes by starting with specifying goals and ending with selecting appropriate interrelated resources. The execution of resource-driven processes takes place in the third phase. Upon initializing modeled resource-driven processes, interrelated resources of resource-driven processes are automatically allocated, if applicable. The allocated resources collaboratively work toward the goals specified in definitions of resource-driven processes resulting in interactions between resources. In the fourth phase, these interactions are analyzed to generate resource-centric recommendations to guide business experts during modeling. We implemented a series of prototypes and conducted an expert survey to validate and evaluate the life cycle. Finally, we present the means of incorporating resource-driven processes into activity-oriented business process models. Therefore, we present a new type of activity construct called context-sensitive activity, adapting the execution based on the current situation. We validated the concept of context-sensitive activities by extending a tool for activity-oriented business processes to support context-sensitive activities

Systemunterstützung zur automatischen Anpassung von Workflows zur Laufzeit

In dieser Arbeit wird ein Ansatz zur automatischen Berechnung und Ausführung von strukturellen Anpassungsmöglichkeiten für Workflows auf Basis von Kontextinformationen entwickelt. Zur Sicherstellung der semantischen Korrektheit der Anpassungsmöglichkeiten werden zwei Arten von Einschränkungen berücksichtigt: Zustandsbezogene Einschränkungen (ZBE) und Aktivitätsabhängigkeiten (AA). ZBEs spezifizieren Einschränkungen zwischen Anpassungsoperationen und dem Ausführungszustand des Workflows. AAs beschreiben temporale Beziehungen zwischen Aktivitäten eines Workflows