The i* framework for goal-oriented modeling

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-39417-6i* is a widespread framework in the software engineering field that supports goal-oriented modeling of socio-technical systems and organizations. At its heart lies a language offering concepts such as actor, dependency, goal and decomposition. i* models resemble a network of interconnected, autonomous, collaborative and dependable strategic actors. Around this language, several analysis techniques have emerged, e.g. goal satisfaction analysis and metrics computation. In this work, we present a consolidated version of the i* language based on the most adopted versions of the language. We define the main constructs of the language and we articulate them in the form of a metamodel. Then, we implement this version and a concrete technique, goal satisfaction analys is based on goal propagation, using ADOxx. Throughout the chapter, we used an example based on open source software adoption to illustrate the concepts and test the implementation.Peer ReviewedPostprint (author's final draft

Towards a classification framework for social machines

The state of the art in human interaction with computational systems blurs the line between computations performed by machine logic and algorithms, and those that result from input by humans, arising from their own psychological processes and life experience. Current socio-technical systems, known as ‘social machines’ exploit the large-scale interaction of humans with machines. Interactions that are motivated by numerous goals and purposes including financial gain, charitable aid, and simply for fun. In this paper we explore the landscape of social machines, both past and present, with the aim of defining an initial classificatory framework. Through a number of knowledge elicitation and refinement exercises we have identified the polyarchical relationship between infrastructure, social machines, and large-scale social initiatives. Our initial framework describes classification constructs in the areas of contributions, participants, and motivation. We present an initial characterization of some of the most popular social machines, as demonstration of the use of the identified constructs. We believe that it is important to undertake an analysis of the behaviour and phenomenology of social machines, and of their growth and evolution over time. Our future work will seek to elicit additional opinions, classifications and validation from a wider audience, to produce a comprehensive framework for the description, analysis and comparison of social machines

Rethinking affordance

n/a – Critical survey essay retheorising the concept of 'affordance' in digital media context. Lead article in a special issue on the topic, co-edited by the authors for the journal Media Theory

FLIAT, an object-relational GIS tool for flood impact assessment in Flanders, Belgium

Floods can cause damage to transportation and energy infrastructure, disrupt the delivery of services, and take a toll on public health, sometimes even causing significant loss of life. Although scientists widely stress the compelling need for resilience against extreme events under a changing climate, tools for dealing with expected hazards lag behind. Not only does the socio-economic, ecologic and cultural impact of floods need to be considered, but the potential disruption of a society with regard to priority adaptation guidelines, measures, and policy recommendations need to be considered as well. The main downfall of current impact assessment tools is the raster approach that cannot effectively handle multiple metadata of vital infrastructures, crucial buildings, and vulnerable land use (among other challenges). We have developed a powerful cross-platform flood impact assessment tool (FLIAT) that uses a vector approach linked to a relational database using open source program languages, which can perform parallel computation. As a result, FLIAT can manage multiple detailed datasets, whereby there is no loss of geometrical information. This paper describes the development of FLIAT and the performance of this tool

Management and Service-aware Networking Architectures (MANA) for Future Internet Position Paper: System Functions, Capabilities and Requirements

Future Internet (FI) research and development threads have recently been gaining momentum all over the world and as such the international race to create a new generation Internet is in full swing: GENI, Asia Future Internet, Future Internet Forum Korea, European Union Future Internet Assembly (FIA). This is a position paper identifying the research orientation with a time horizon of 10 years, together with the key challenges for the capabilities in the Management and Service-aware Networking Architectures (MANA) part of the Future Internet (FI) allowing for parallel and federated Internet(s)

How to Generate Security Cameras: Towards Defence Generation for Socio-Technical Systems

Recently security researchers have started to look into automated generation of attack trees from socio-technical system models. The obvious next step in this trend of automated risk analysis is automating the selection of security controls to treat the detected threats. However, the existing socio-technical models are too abstract to represent all security controls recommended by practitioners and standards. In this paper we propose an attack-defence model, consisting of a set of attack-defence bundles, to be generated and maintained with the socio-technical model. The attack-defence bundles can be used to synthesise attack-defence trees directly from the model to offer basic attack-defence analysis, but also they can be used to select and maintain the security controls that cannot be handled by the model itself.Comment: GraMSec 2015, 16 page

The Mundane Computer: Non-Technical Design Challenges Facing Ubiquitous Computing and Ambient Intelligence

Interdisciplinary collaboration, to include those who are not natural scientists, engineers and computer scientists, is inherent in the idea of ubiquitous computing, as formulated by Mark Weiser in the late 1980s and early 1990s. However, ubiquitous computing has remained largely a computer science and engineering concept, and its non-technical side remains relatively underdeveloped. The aim of the article is, first, to clarify the kind of interdisciplinary collaboration envisaged by Weiser. Second, the difficulties of understanding the everyday and weaving ubiquitous technologies into the fabric of everyday life until they are indistinguishable from it, as conceived by Weiser, are explored. The contributions of Anne Galloway, Paul Dourish and Philip Agre to creating an understanding of everyday life relevant to the development of ubiquitous computing are discussed, focusing on the notions of performative practice, embodied interaction and contextualisation. Third, it is argued that with the shift to the notion of ambient intelligence, the larger scale socio-economic and socio-political dimensions of context become more explicit, in contrast to the focus on the smaller scale anthropological study of social (mainly workplace) practices inherent in the concept of ubiquitous computing. This can be seen in the adoption of the concept of ambient intelligence within the European Union and in the focus on rebalancing (personal) privacy protection and (state) security in the wake of 11 September 2001. Fourth, the importance of adopting a futures-oriented approach to discussing the issues arising from the notions of ubiquitous computing and ambient intelligence is stressed, while the difficulty of trying to achieve societal foresight is acknowledged

An analytical framework to nowcast well-being using mobile phone data

An intriguing open question is whether measurements made on Big Data recording human activities can yield us high-fidelity proxies of socio-economic development and well-being. Can we monitor and predict the socio-economic development of a territory just by observing the behavior of its inhabitants through the lens of Big Data? In this paper, we design a data-driven analytical framework that uses mobility measures and social measures extracted from mobile phone data to estimate indicators for socio-economic development and well-being. We discover that the diversity of mobility, defined in terms of entropy of the individual users' trajectories, exhibits (i) significant correlation with two different socio-economic indicators and (ii) the highest importance in predictive models built to predict the socio-economic indicators. Our analytical framework opens an interesting perspective to study human behavior through the lens of Big Data by means of new statistical indicators that quantify and possibly "nowcast" the well-being and the socio-economic development of a territory