Towards the realisation of an integratated decision support environment for organisational decision making

Traditional decision support systems are based on the paradigm of a single decision maker working at a stand‐alone computer or terminal who has a specific decision to make with a specific goal in mind. Organizational decision support systems aim to support decision makers at all levels of an organization (from executive, middle management managers to operators), who have a variety of decisions to make, with different priorities, often in a distributed and dynamic environment. Such systems need to be designed and developed with extra functionality to meet the challenges such as collaborative working. This paper proposes an Integrated Decision Support Environment (IDSE) for organizational decision making. The IDSE distinguishes itself from traditional decision support systems in that it can flexibly configure and re‐configure its functions to support various decision applications. IDSE is an open software platform which allows its users to define their own decision processes and choose their own exiting decision tools to be integrated into the platform. The IDSE is designed and developed based on distributed client/server networking, with a multi‐tier integration framework for consistent information exchange and sharing, seamless process co‐ordination and synchronisation, and quick access to packaged and legacy systems. The prototype of the IDSE demonstrates good performance in agile response to fast changing decision situations

Improving Quality Assurance in Multidisciplinary Engineering Environments with Semantic Technologies

In multidisciplinary engineering (MDE) projects, for example, automation systems or manufacturing systems, stakeholders from various disciplines, for example, electrics, mechanics and software, have to collaborate. In industry practice, engineers apply individual and highly specialized tools with strong limitation regarding defect detection in early engineering phases. Experts typically execute reviews with limited tool support which make engineering projects defective and risky. Semantic Web Technologies (SWTs) can help to bridge the gap between heterogeneous sources as foundation for efficient and effective defect detection. Main questions focus on (a) how to bridge gaps between loosely coupled tools and incompatible data models and (b) how SWTs can help to support efficient and effective defect detection in context of engineering process improvement. This chapter describes success-critical requirements for defect detection in MDE and shows how SWTs can provide the foundation for early and efficient defect detection with an adapted review approach. The proposed defect detection framework (DDF) suggests different levels of SWT contributions as a roadmap for engineering process improvement. Two selected industry-related real-life cases show different levels of SWT involvement. Although SWTs have been successfully applied in real-life use cases, SWT applications can be risky if applied without good understanding of success factors and limitations

A pivotal-based approach for enterprise business process and IS integration

A company must be able to describe and react against any endogenous or exogenous event. Such flexibility can be achieved through business process management (BPM). Nevertheless a BPM approach highlights complex relations between business and IT domains. A non-alignment is exposed between heterogeneous models: this is the 18business-IT gap 19 as described in the literature. Through concepts from business engineering and information systems driven by models and IT, we define a generic approach ensuring multi-view consistency. Its role is to maintain and provide all information related to the structure and semantic of models. Allowing the full return of a transformed model in the sense of reverse engineering, our platform enables synchronisation between analysis model and implementation model

Spatial Data Quality in the IoT Era:Management and Exploitation

Within the rapidly expanding Internet of Things (IoT), growing amounts of spatially referenced data are being generated. Due to the dynamic, decentralized, and heterogeneous nature of the IoT, spatial IoT data (SID) quality has attracted considerable attention in academia and industry. How to invent and use technologies for managing spatial data quality and exploiting low-quality spatial data are key challenges in the IoT. In this tutorial, we highlight the SID consumption requirements in applications and offer an overview of spatial data quality in the IoT setting. In addition, we review pertinent technologies for quality management and low-quality data exploitation, and we identify trends and future directions for quality-aware SID management and utilization. The tutorial aims to not only help researchers and practitioners to better comprehend SID quality challenges and solutions, but also offer insights that may enable innovative research and applications

Integrating information and knowledge for enterprise innovation

It has widely been accepted that enterprise integration, can be a source of socio-technical and cultural problems within organisations wishing to provide a focussed end-to-end business service. This can cause possible “straitjacketing” of business process architectures, thus suppressing responsive business re-engineering and competitive advantage for some companies. Accordingly, the current typology and emergent forms of Enterprise Resource Planning (ERP) and Enterprise Application Integration (EAI) technologies are set in the context of understanding information and knowledge integration philosophies. As such, key influences and trends in emerging IS integration choices, for end-to-end, cost-effective and flexible knowledge integration, are examined. As touch points across and outside organisations proliferate, via work-flow and relationship management-driven value innovation, aspects of knowledge refinement and knowledge integration pose challenges to maximising the potential of innovation and sustainable success, within enterprises. This is in terms of the increasing propensity for data fragmentation and the lack of effective information management, in the light of information overload. Furthermore, the nature of IS mediation which is inherent within decision making and workflow-based business processes, provides the basis for evaluation of the effects of information and knowledge integration. Hence, the authors propose a conceptual, holistic evaluation framework which encompasses these ideas. It is thus argued that such trends, and their implications regarding enterprise IS integration to engender sustainable competitive advantage, require fundamental re-thinking

System Qualities Ontology, Tradespace and Affordability (SQOTA) Project Phase 5

Motivation and Context: One of the key elements of the SERC's research strategy is transforming the practice of systems engineering and associated management practices- "SE and Management Transformation (SEMT)." The Grand Challenge goal for SEMT is to transform the DoD community 's current systems engineering and management methods, processes, and tools (MPTs) and practices away from sequential, single stovepipe system, hardware-first ,document-driven, point- solution, acquisition-oriented approaches; and toward concurrent, portfolio and enterprise-oriented, hardware-software-human engineered, model-driven, set-based, full life cycle approaches.This material is based upon work supported, in whole or in part, by the U.S. Department of Defense through the Office of the Assistant Secretary of Defense for Research and Engineering (ASD(R&E)) under Contract H98230-08-D-0171 and HQ0034-13-D-0004 (TO 0060).This material is based upon work supported, in whole or in part, by the U.S. Department of Defense through the Office of the Assistant Secretary of Defense for Research and Engineering (ASD(R&E)) under Contract H98230-08-D-0171 and HQ0034-13-D-0004 (TO 0060)

Semantic Management of Location-Based Services in Wireless Environments

En los últimos años el interés por la computación móvil ha crecido debido al incesante uso de dispositivos móviles (por ejemplo, smartphones y tablets) y su ubicuidad. El bajo coste de dichos dispositivos unido al gran número de sensores y mecanismos de comunicación que equipan, hace posible el desarrollo de sistemas de información útiles para sus usuarios. Utilizando un cierto tipo especial de sensores, los mecanismos de posicionamiento, es posible desarrollar Servicios Basados en la Localización (Location-Based Services o LBS en inglés) que ofrecen un valor añadido al considerar la localización de los usuarios de dispositivos móviles para ofrecerles información personalizada. Por ejemplo, se han presentado numerosos LBS entre los que se encuentran servicios para encontrar taxis, detectar amigos en las cercanías, ayudar a la extinción de incendios, obtener fotos e información de los alrededores, etc. Sin embargo, los LBS actuales están diseñados para escenarios y objetivos específicos y, por lo tanto, están basados en esquemas predefinidos para el modelado de los elementos involucrados en estos escenarios. Además, el conocimiento del contexto que manejan es implícito; razón por la cual solamente funcionan para un objetivo específico. Por ejemplo, en la actualidad un usuario que llega a una ciudad tiene que conocer (y comprender) qué LBS podrían darle información acerca de medios de transporte específicos en dicha ciudad y estos servicios no son generalmente reutilizables en otras ciudades. Se han propuesto en la literatura algunas soluciones ad hoc para ofrecer LBS a usuarios pero no existe una solución general y flexible que pueda ser aplicada a muchos escenarios diferentes. Desarrollar tal sistema general simplemente uniendo LBS existentes no es sencillo ya que es un desafío diseñar un framework común que permita manejar conocimiento obtenido de datos enviados por objetos heterogéneos (incluyendo datos textuales, multimedia, sensoriales, etc.) y considerar situaciones en las que el sistema tiene que adaptarse a contextos donde el conocimiento cambia dinámicamente y en los que los dispositivos pueden usar diferentes tecnologías de comunicación (red fija, inalámbrica, etc.). Nuestra propuesta en la presente tesis es el sistema SHERLOCK (System for Heterogeneous mobilE Requests by Leveraging Ontological and Contextual Knowledge) que presenta una arquitectura general y flexible para ofrecer a los usuarios LBS que puedan serles interesantes. SHERLOCK se basa en tecnologías semánticas y de agentes: 1) utiliza ontologías para modelar la información de usuarios, dispositivos, servicios, y el entorno, y un razonador para manejar estas ontologías e inferir conocimiento que no ha sido explicitado; 2) utiliza una arquitectura basada en agentes (tanto estáticos como móviles) que permite a los distintos dispositivos SHERLOCK intercambiar conocimiento y así mantener sus ontologías locales actualizadas, y procesar peticiones de información de sus usuarios encontrando lo que necesitan, allá donde esté. El uso de estas dos tecnologías permite a SHERLOCK ser flexible en términos de los servicios que ofrece al usuario (que son aprendidos mediante la interacción entre los dispositivos), y de los mecanismos para encontrar la información que el usuario quiere (que se adaptan a la infraestructura de comunicación subyacente)