Purpose -The purpose of this study is to develop a novel approach to e-participation, which is based on "passive crowdsourcing" by government agencies, exploiting the extensive political content continuously created in numerous Web 2.0 social media (e.g. political blogs and microblogs, news sharing sites and online forums) by citizens without government stimulation, to understand better their needs, issues, opinions, proposals and arguments concerning a particular domain of government activity or public policy. Design/methodology/approach -This approach is developed and elaborated through cooperation with potential users experienced in the design of public policies from three countries (Austria, Greece and the UK), using a combination of quantitative and qualitative techniques: co-operative development of application scenarios, questionnaire surveys, focus groups and workshops and, finally, in-depth interviews.Findings -A process model for the application of the proposed passive crowdsourcing approach has been developed, which is quite different from the one of the usual active crowdsourcing. Based on it, the functional architecture of the required supporting information and communication technologies (ICT) infrastructure has been formulated, and then its technological architecture has been designed, addressing the conflicting requirements: low response time and, at the same time, provision of sufficiently "fresh" content for policymakers. Practical implications -Taking into account that traditionally government agencies monitor what the press writes about them, our research provides a basis for extending efficiently these activities in the new electronic media world (e.g. newspapers websites, blogs and microblogs, online forums, etc.) to understand better the needs, issues, opinions, arguments and proposals raised by the society with respect to important domains of government activity and public policies. Social implications -The proposed approach provides a new channel for the "voice" of the society to be directly communicated to the government so that the latter can design its policies and activities based on the social needs and realities and not on oversimplified models and stereotypes. Originality/value -Our paper proposes a novel approach to e-participation, which exploits the Web 2.0 social media -but in a quite different way from previous approaches -for conducting "passive crowdsourcing", and elaborates it: it develops an application process model for it and also an ICT infrastructure for supporting it, which are quite different from the ones of the existing "active crowdsourcing" approaches.

Abstract. The emergence of web 2.0 social media enables the gradual emergence of a second generation of e-participation characterized by more citizens' control, in which government agencies post content (e.g. short or longer text, images, video) to various social media and then analyze citizens' interactions with it (e.g. views, likes/dislikes, comments, etc.). In this paper we propose an even more citizens controlled third generation of e-participation exploiting web 2.0 social media as well, but in a different manner. It is based on the search by government agencies for content on a public policy under formulation, which has been created in a large set of web 2.0 sources (e.g. blogs and microblogs, news sharing sites, online forums) by citizens freely, without any initiation, stimulation or moderation through government postings. This content undergoes advanced processing in order to extract from it arguments, opinions, issues and proposals on the particular policy, identify their sentiments (positive or negative), and finally summarize and visualize them. This approach allows the exploitation of the vast amount of user-generated content created in numerous web 2.0 social media for supporting governments to understand better the needs, wishes and beliefs of citizens, and create better and more socially rooted policies.

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Abstract-Intelligent Environments most commonly take a physical form such as homes, offices, hotels, restaurants, shops, that are equipped with advanced networked computer based systems, which enable better or new lifestyles for people. However, Intelligent Environments can also take the form of virtual online spaces such as SecondLife, which can both mimic the real world and provide functionalities which could not be provided in reality, such as advanced simulations and movement. There is the growing trend for people to spend more time in such virtual environments and, to these ends, this work in progress paper reports on a new project, +Spaces which is developing a range of virtual world tools for e-government applications, and presents some of the concepts and technical challenges involved in creating these intelligent virtual spaces for e-government.

Tailoring personalized treatments demands the analysis of a patient’s characteristics, which may be scattered over a wide variety of sources. These features include family history, life habits, comorbidities, and potential treatment side effects. Moreover, the analysis of the services visited the most by a patient before a new diagnosis, as well as the type of requested tests, may uncover patterns that contribute to earlier disease detection and treatment effectiveness. Built on knowledge-driven ecosystems, we devise DE4LungCancer, a health data ecosystem of data sources for lung cancer. In this data ecosystem, knowledge extracted from heterogeneous sources, e.g., clinical records, scientific publications, and pharmacological data, is integrated into knowledge graphs. Ontologies describe the meaning of the combined data, and mapping rules enable the declarative definition of the transformation and integration processes. DE4LungCancer is assessed regarding the methods followed for data quality assessment and curation. Lastly, the role of controlled vocabularies and ontologies in health data management is discussed, as well as their impact on transparent knowledge extraction and analytics. This paper presents the lessons learned in the DE4LungCancer development. It demonstrates the transparency level supported by the proposed knowledge-driven ecosystem, in the context of the lung cancer pilots of the EU H2020-funded project BigMedilytic, the ERA PerMed funded project P4-LUCAT, and the EU H2020 projects CLARIFY and iASiS.