D3.3 Serious Gaming Approach to support Usability of IOT oriented User CoCreation

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The GOALS approach: business and software modeling traceability by means of human-computer interaction: enterprise modeling language and method

The management of an enterprise relies on the continuous organization and development of its business and software systems. A process that requires merging the ideas of the enterprise’ systems managers, targeting the specification of business requirements and the conception and implementation of a supporting information system. This process finds obstacles in the identification and communication of requirements, and also in their transformation in software artefacts, leading to difficulties or loss of traceability between business and software models. Existing methods, languages and techniques are still not sufficiently standardized to ensure that when a business improvement is introduced, the supportive software solution will be implemented within budget and time. Methods are still too closed to the concepts of their original scientific domains, conceiving solutions which are not representative of the business and software conceptual relation and of the complexity concealed in an improvement effort, namely concerning usability and user experience. Moreover, the lack of a common modeling language and method for the conception of holistic and traceable software solutions, also refrains the performance of the enterprise development process. The GOALS Approach presents a solution to surpass these barriers by means of the specification of an enterprise modeling language that relates the business and software conceptual structures using a shared set of concepts, a notation, process, method and techniques, that allow the design of the software as a result of the business organization, ensuring traceability by means of the permanent representation of the business structure in the software structure

Multi-Method Framework for Development of Systemic, Technology-Driven Capability Concepts

Emerging technologies shape the operations of many commercial and military organisations, including the Australian Defence Force. Current capability development processes, grounded in the principles of systems engineering, focus on capability gaps rather than opportunities, often locking in incremental improvements but not transformative changes enabling new capabilities and processes. Furthermore, traditional systems engineering is framed in a way that equates capability with product, leading to single-technology stove-piped processes. By contrast, the study presented in this thesis seeks to design a methodological framework for development of systemic, technology-driven capability concepts that recognise capability as an emergent property of complex systems. The study draws on the body of knowledge in systems thinking and multi-method operations research to design the methodological framework and apply, evaluate and refine it across five concept development workshops within a multi-case study. The study findings support reducing the focus on current processes, use of boundary-mitigating steps to improve generation of ideas, and evolution of technology use cases during concept development. Higher-level, operational concepts are found to be more complex than lower-level tactical concepts; cyclical processes that include resupply produce concepts with higher dynamic complexity. Elicitation of impacts is shaped by the available time and discussion prompts. Importantly, concepts are best framed in terms of capability rather than technology, as capabilities are enabled by multiple interacting technological elements. This is reflected in the novel formalism of technological ecosystem maps, which reframes the discussion of capability options towards capability effects generated by technology groupings. For operations researchers seeking to design real-life interventions, the study demonstrates a traceable process of methodological evolution, with a novel application of boundary critique as the analytical lens for improvement. For capability developers, the study provides a fit-for-purpose methodology for exploring the opportunities presented by emerging technologies, intended to complement the existing capability development processes. The formalism of technological ecosystems lays the groundwork for reframing of capability development towards a more holistic framework, emphasising integration, sustainment, and long-term management of capability elements

Approaches for the anticipation of skill needs in the Transitional Labour Market perspecitve: The Austrian experience

A synthesis of studies regarding anticipation practices in Austria is provided. The theoretical approach combines concepts from transitional labour market theory, the foresight paradigm, institutional approaches to the coordination of education and employment, and the concept of an anticipation system as a social system of knowledge generation and management. The Analysis focuses on four main aspects: (1) the communication structure, (2) the current state of forecasting, (3) anticipation practices at the regional and sector level, and (4) the measurement and matching instruments. The Austrian system is an informal system which emphasises a professionalpolitical approach. It relies mainly on practitioner task forces which work at an informal level. The system also reflects the segmented structure of the education and training system. New developments at the regional level are related to the establishment of the Fachhochschule sector a decade ago. Another strand of development has been regional innovation policy. The regional level serves as a catalyst in setting up more elaborate systems for anticipating skill needs. The criteria for anticipation in a TLM perspective are not fulfilled. In sum, the foresight and transitional labour market approaches could provide several pathways for development. -- Das Paper enthält eine Synthese von Studien über das österreichische Antizipationssystem. Der theoretische Ansatz kombiniert Konzepte der Übergangsarbeitsmärkte, des Vorauschau-Paradigmas, der Koppelung von Bildung und Beschäftigung, und sozialer Wissensproduktion. Vier Aspekte stehen in Vordergrund: (1) die Kommunikationsstruktur, (2) formale Prognosen, (3) Praktiken auf regionaler und sektoraler Ebene, und (4) Mess- und Matching-Instrumente. Das österreichische Antizipationssystem ist ein informelles System auf Basis eines professionell-politischen Ansatzes. Es baut wesentlich auf informellen PraktikerInnen- Arbeitsgruppen auf und reflektiert die segmentierte Struktur des Bildungswesens. Wesentliche Entwicklungsimpulse gehen von der regionalen Ebene aus. Die Kriterien des Ansatzes der Übergangsarbeitsmärkte sind nicht erfüllt und können wichtige Impulse für die Weiterentwicklung geben.

Designing a method for discovering expertise in cyber security communities: an ontological approach

Cyber security aims to protect our connected society from threats affecting services that rely on cyberspace. The pervasive nature of those threats requires a collaborative engagement in which a heterogeneous set of stakeholders request or provide security services. One of the major challenges in current cyber security initiatives is to place skilled people wherever needed whilst reducing the overall knowledge gap. Thus, in order to orchestrate roles in such a complex and dynamic environment, a novel approach to discover talent within the cyber security community is required. This PhD research addresses this challenge by devising a conceptual model and an ontological methodology, which aids a robust discovery of the fittest expertise driven by the specific needs of cyber security projects, as well as benchmarking expertise shortages. Talent management, knowledge management and organisational modelling theories provide the theoretical foundations upon which the cyber security community is articulated. Mixed methods were performed within a cyber security community to triangulate findings in the literature, test the method and appraise the solution. The method for discovering expertise in cyber security communities (DECYSE) is capable of delivering a seamless solution for processes involving expertise discovery. This method enables learning from previous projects; supports selection, ranking and assessment of experts according to specified requirements in a project profile; and provides indicators to measure knowledge gaps and shortages in the cyber security community. The DECYSE method is robust and underpinned by analytical techniques, considering complex interactions and perspectives from the actors involved. In order to promote ongoing improvement on the method itself, this thesis also details the conceptual model which articulates the requirements for developing DECYSE. A round of experiments was successfully conducted, where a team of three experts, out of sixty-six participant profiles, met the criteria in a cyber security project. The method was also positively appraised by a board of experts working with strategic CS projects. DECYSE enables ongoing improvement and contributes to both theory and the cyber security community

Advanced predictive-analysis-based decision support for collaborative logistics networks

Purpose – The purpose of this paper is to examine challenges and potential of big data in heterogeneous business networks and relate these to an implemented logistics solution. Design/methodology/approach – The paper establishes an overview of challenges and opportunities of current significance in the area of big data, specifically in the context of transparency and processes in heterogeneous enterprise networks. Within this context, the paper presents how existing components and purpose-driven research were combined for a solution implemented in a nationwide network for less-than-truckload consignments. Findings – Aside from providing an extended overview of today’s big data situation, the findings have shown that technical means and methods available today can comprise a feasible process transparency solution in a large heterogeneous network where legacy practices, reporting lags and incomplete data exist, yet processes are sensitive to inadequate policy changes. Practical implications – The means introduced in the paper were found to be of utility value in improving process efficiency, transparency and planning in logistics networks. The particular system design choices in the presented solution allow an incremental introduction or evolution of resource handling practices, incorporating existing fragmentary, unstructured or tacit knowledge of experienced personnel into the theoretically founded overall concept. Originality/value – The paper extends previous high-level view on the potential of big data, and presents new applied research and development results in a logistics application