Harnessing data flow and modelling potentials for sustainable development

Tackling some of the global challenges relating to health, poverty, business and the environment is known to be heavily dependent on the flow and utilisation of data. However, while enhancements in data generation, storage, modelling, dissemination and the related integration of global economies and societies are fast transforming the way we live and interact, the resulting dynamic, globalised and information society remains digitally divided. On the African continent, in particular, the division has resulted into a gap between knowledge generation and its transformation into tangible products and services which Kirsop and Chan (2005) attribute to a broken information flow. This paper proposes some fundamental approaches for a sustainable transformation of data into knowledge for the purpose of improving the peoples' quality of life. Its main strategy is based on a generic data sharing model providing access to data utilising and generating entities in a multi disciplinary environment. It highlights the great potentials in using unsupervised and supervised modelling in tackling the typically predictive-in-nature challenges we face. Using both simulated and real data, the paper demonstrates how some of the key parameters may be generated and embedded in models to enhance their predictive power and reliability. Its main outcomes include a proposed implementation framework setting the scene for the creation of decision support systems capable of addressing the key issues in society. It is expected that a sustainable data flow will forge synergies between the private sector, academic and research institutions within and between countries. It is also expected that the paper's findings will help in the design and development of knowledge extraction from data in the wake of cloud computing and, hence, contribute towards the improvement in the peoples' overall quality of life. To void running high implementation costs, selected open source tools are recommended for developing and sustaining the system. Key words: Cloud Computing, Data Mining, Digital Divide, Globalisation, Grid Computing, Information Society, KTP, Predictive Modelling and STI

Cross-disciplinary lessons for the future internet

There are many societal concerns that emerge as a consequence of Future Internet (FI) research and development. A survey identified six key social and economic issues deemed most relevant to European FI projects. During a SESERV-organized workshop, experts in Future Internet technology engaged with social scientists (including economists), policy experts and other stakeholders in analyzing the socio-economic barriers and challenges that affect the Future Internet, and conversely, how the Future Internet will affect society, government, and business. The workshop aimed to bridge the gap between those who study and those who build the Internet. This chapter describes the socio-economic barriers seen by the community itself related to the Future Internet and suggests their resolution, as well as investigating how relevant the EU Digital Agenda is to Future Internet technologists

Models of everywhere revisited: a technological perspective

The concept ‘models of everywhere’ was first introduced in the mid 2000s as a means of reasoning about the environmental science of a place, changing the nature of the underlying modelling process, from one in which general model structures are used to one in which modelling becomes a learning process about specific places, in particular capturing the idiosyncrasies of that place. At one level, this is a straightforward concept, but at another it is a rich multi-dimensional conceptual framework involving the following key dimensions: models of everywhere, models of everything and models at all times, being constantly re-evaluated against the most current evidence. This is a compelling approach with the potential to deal with epistemic uncertainties and nonlinearities. However, the approach has, as yet, not been fully utilised or explored. This paper examines the concept of models of everywhere in the light of recent advances in technology. The paper argues that, when first proposed, technology was a limiting factor but now, with advances in areas such as Internet of Things, cloud computing and data analytics, many of the barriers have been alleviated. Consequently, it is timely to look again at the concept of models of everywhere in practical conditions as part of a trans-disciplinary effort to tackle the remaining research questions. The paper concludes by identifying the key elements of a research agenda that should underpin such experimentation and deployment

Facing Digital Dystopias: A Discussion about Responsibility in the Design of Smart Products

The paper investigates some critical issues connected to the digitalization of products and systems for the domestic environments involving the collection of personal data. The research focuses on the most innovative solutions, such as those based on AI algorithms for speech recognition, IoTs, wearable devices, cloud computing, and the use of smart phones and devices. These solutions require and imply the collection of personal data and their local or remote processing. The paper provides a design-oriented discussion on the features of smart products with respect to the consequences of design choices on complex dimensions of experience such as sense of self, privacy, and personal identity. The paper aims to set out the terms of a discussion about the most critical factors of services and systems involving personal data, and to create references on the responsibilities of designers acting in multi-disciplinary project teams. The research is based on ethnography at home and on a critical discussion about case studies. The results highlight the importance of considering privacy and control issues in the design of smart solutions and provide some pointers to be used in the development of smart solutions for home

Untangling the Web of E-Research: Towards a Sociology of Online Knowledge

e-Research is a rapidly growing research area, both in terms of publications and in terms of funding. In this article we argue that it is necessary to reconceptualize the ways in which we seek to measure and understand e-Research by developing a sociology of knowledge based on our understanding of how science has been transformed historically and shifted into online forms. Next, we report data which allows the examination of e-Research through a variety of traces in order to begin to understand how the knowledge in the realm of e-Research has been and is being constructed. These data indicate that e-Research has had a variable impact in different fields of research. We argue that only an overall account of the scale and scope of e-Research within and between different fields makes it possible to identify the organizational coherence and diffuseness of e-Research in terms of its socio-technical networks, and thus to identify the contributions of e-Research to various research fronts in the online production of knowledge

Service Level Agreement-based GDPR Compliance and Security assurance in (multi)Cloud-based systems

Compliance with the new European General Data Protection Regulation (Regulation (EU) 2016/679) and security assurance are currently two major challenges of Cloud-based systems. GDPR compliance implies both privacy and security mechanisms definition, enforcement and control, including evidence collection. This paper presents a novel DevOps framework aimed at supporting Cloud consumers in designing, deploying and operating (multi)Cloud systems that include the necessary privacy and security controls for ensuring transparency to end-users, third parties in service provision (if any) and law enforcement authorities. The framework relies on the risk-driven specification at design time of privacy and security level objectives in the system Service Level Agreement (SLA) and in their continuous monitoring and enforcement at runtime.The research leading to these results has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 644429 and No 780351, MUSA project and ENACT project, respectively. We would also like to acknowledge all the members of the MUSA Consortium and ENACT Consortium for their valuable help

The Strategy of the Commons: Modelling the Annual Cost of Successful ICT Services for European Research

The provision of ICT services for research is increasingly using Cloud services to complement the traditional federation of computing centres. Due to the complex funding structure and differences in the basic business model, comparing the cost-effectiveness of these options requires a new approach to cost assessment. This paper presents a cost assessment method addressing the limitations of the standard methods and some of the initial results of the study. This acts as an illustration of the kind of cost assessment issues high-utilisation rate ICT services should consider when choosing between different infrastructure options. The research is co-funded by the European Commission Seventh Framework Programme through the e-FISCAL project (contract number RI-283449)