European Institute for Participatory Media

ABSTRACT Gamification is increasingly being used by organizations to foster work-related competencies and employee motivation. In the current body of gamification literature, there is a dearth of design knowledge about systems that foster the development of employee competencies through effective gamification approaches. The aim of this paper is to set the cornerstone of an information systems design theory (ISDT) of user-centered score mechanics that can assist both researchers and practitioners in building gamified environments.

Computer and social sciences offer a wide range of tools to help face the world’s challenges arising in smart city scenarios and involving environment, energy, food, water, transportation, infrastructures, society, healthcare, education, governance, and economy. Indeed, purely technical solutions might be of little effect without proper consideration of the social dimension of the Smart City. A user’s behavior depends on a variety of social and individual motivations, which require addressing both the technical and social sides of the problem to promote active engagement of individuals in increasing the social good. More specifically, social computing tools can be targeted on a wide range of Smart Cities applications, including urban transport and fleet logistics management (possibly leveraging electric vehicles or other intelligent transportation systems), traffic, public safety and air pollution monitoring via smart traffic lights, smart signals and lamp posts, automation of smart buildings and homes with the aim of improving energy efficiency, livability and age-friendliness, smart health, smart industries, electricity grids, water systems and solid waste management, and frameworks for educational, cultural, and entertainment initiatives.

This paper presents a visualization approach to accessing and exploring the knowledge obtained from patient cases created by general practitioners in their medical practice during postgraduate practical training. Our application MediMatrix visualizes this knowledge base by displaying the patient cases in a matrix-based grid. It addresses domain specific challenges (broad spectrum of medical topics, isolation from peers during training, time pressure) and use cases (solving patient cases, learning for the exam) of the target group. In addressing these requirements MediMatrix focuses on supporting specific kinds of information tasks such as gaining a quick overview of a heterogeneous case collection, comparing a specific case with other cases and discovering topical cross-connections between cases. Through the provided visual modalities for explorative access of a learner-generated medical case collection physicians can easily discover patient cases relevant for their practice and share knowledge by discussing, working on and learning from the patient cases.

The extraction of semantic information from multimedia content represents a challenging problem. Despite the continuous refinement of automatic tools, the quality and completeness of the results is not always satisfactory. To overcome this limitation, the vision of the CUbRIK project is to provide a multimedia search and exploration platform that seamlessly integrate human tasks and algorithms. In this paper, as a concrete example, we illustrate the design of amultimedia content processing pipeline that aims at extracting evidence of social relationships from the analysis of a photo collection covering the main events and people that shaped the history of Europe after World War II. We discuss the issues faced by general-purpose crowdsourcing and automatic face detection/recognition algorithms in determining the identities of people portrayed in the photo collection. Hence, we illustrate the design of a system that tackles the uncertainty of the results produced by face detection/recognition with expert-based crowdsourcing.