Abstract:Responsible research and innovation (RRI) is a nascent concept, promoted actively by the European Union and other policy makers around the world. Hitherto, this concept has been associated primarily with publicly funded activities but given the considerable proportion of research and innovation that is undertaken in the private sector, RRI will be rendered irrelevant unless it is adopted by industry. This paper introduces a private sector perspective of RRI, specifically that of the information and communication technology (ICT) industry, working in the field of healthy ageing. Drawing upon empirical data from 30 in-depth interviews with key industry representatives from across Europe, it explores: (a) the level of awareness of RRI; (b) the drivers and obstacles influencing its implementation; and (c) the factors deemed vital for facilitation of RRI in industry. The findings paint a varied picture, including significant concerns about adoption of RRI in an industry environment where the economic implications of all activities must be considered carefully. However, some companies have found their own ways to balance financial and altruistic goals, suggesting that there is both a willingness and a place for an RRI-type governance framework within the private sector.

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Abstract. Context management in pervasive computing environments must reflect the specific characteristics of these environments, e.g. distribution, mobility, resource-constrained devices, or heterogeneity of context sources. Although a number of context models have been presented in the literature, none of them supports all of these requirements to a sufficient extent at the same time. In this paper, we present a comprehensive and integrated approach for context modeling in pervasive computing environments. It combines the advantages of existing approaches and addresses the need for supporting effective software development. The proposed context model follows an ontology-based approach and has three layers of abstraction, i.e. conceptual layer, exchange layer, and functional layer. This layered approach facilitates a model-driven development of context-aware applications. Throughout the paper we compare our solution with the related work in order to clearly demonstrate why we needed to develop a new context management framework and where we have adopted existing ideas.

SUMMARY Although the idea of context‐awareness was introduced almost two decades ago, few mobile software applications are available today that can sense and adapt to their run‐time environment. The development of context‐aware and self‐adaptive applications is complex and few developers have experience in this area. On the basis of several demonstrators built by the joint European research project MUSIC, this paper describes typical context and adaptation features relevant for the development of context‐aware and self‐adaptive mobile applications. We explain how the demonstrators were realised using the open‐source platform MUSIC and present the feedback of the developers of these demonstrators. The main contribution of this paper is to show how the development complexity of context‐aware and self‐adaptive mobile applications can be mastered by using an adaptation framework such as MUSIC. Copyright © 2012 John Wiley & Sons, Ltd.

Driven by the emergence of mobile and pervasive computing there is a growing demand for context-aware software systems that can dynamically adapt to their run-time environment. We present the results of project MADAM which has delivered a comprehensive solution for the development and operation of context-aware, self-adaptive applications. The main contributions of MADAM are (a) a sophisticated middleware that supports the dynamic adaptation of component-based applications, and (b) an innovative model-driven development methodology which is based on abstract adaptation models and corresponding model-to-code transformations. MADAM has demonstrated the viability of a general, integrated approach to application-level adaptation. We discuss our experiences with two real-world case studies that were built using the MADAM approach.

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