Design and development practitioners such as those in game development often have difficulty comprehending and adhering to the European General Data Protection Regulation (GDPR), especially when designing in a private sensitive way. Inadequate understanding of how to apply the GDPR in the game development process can lead to one of two consequences: 1. inadvertently violating the GDPR with sizeable fines as potential penalties; or 2. avoiding the use of user data entirely. In this paper, we present our work on designing and evaluating the “GDPR Pitstop tool”, a gamified questionnaire developed to empower game developers and designers to increase legal awareness of GDPR laws in a relatable and accessible manner. The GDPR Pitstop tool was developed with a user-centered approach and in close contact with stakeholders, including practitioners from game development, legal experts and communication and design experts. Three design choices worked for this target group: 1. Careful crafting of the language of the questions; 2. a flexible structure; and 3. a playful design. By combining these three elements into the GDPR Pitstop tool, GDPR awareness within the gaming industry can be improved upon and game developers and designers can be empowered to use user data in a GDPR compliant manner. Additionally, this approach can be scaled to confront other tricky issues faced by design professionals such as privacy by design.
LINK
Game development businesses often choose Lua for separating scripted game logic from reusable engine code. Lua can easily be embedded, has simple interfaces, and offers a powerful and extensible scripting language. Using Lua, developers can create prototypes and scripts at early development stages. However, when larger quantities of engine code and script are available, developers encounter maintainability and quality problems. First, the available automated solutions for interoperability do not take domain-specific optimizations into account. Maintaining a coupling by hand between the Lua interpreter and the engine code, usually in C++, is labour intensive and error-prone. Second, assessing the quality of Lua scripts is hard due to a lack of tools that support static analysis. Lua scripts for dynamic analysis only report warnings and errors at run-time and are limited to code coverage. A common solution to the first problem is developing an Interface Definition Language (IDL) from which ”glue code”, interoperability code between interfaces, is generated automatically. We address quality problems by proposing a method to complement techniques for Lua analysis. We introduce Lua AiR (Lua Analysis in Rascal), a framework for static analysis of Lua script in its embedded context, using IDL models and Rascal.
DOCUMENT
Physical rehabilitation programs revolve around the repetitive execution of exercises since it has been proven to lead to better rehabilitation results. Although beginning the motor (re)learning process early is paramount to obtain good recovery outcomes, patients do not normally see/experience any short-term improvement, which has a toll on their motivation. Therefore, patients find it difficult to stay engaged in seemingly mundane exercises, not only in terms of adhering to the rehabilitation program, but also in terms of proper execution of the movements. One way in which this motivation problem has been tackled is to employ games in the rehabilitation process. These games are designed to reward patients for performing the exercises correctly or regularly. The rewards can take many forms, for instance providing an experience that is engaging (fun), one that is aesthetically pleasing (appealing visual and aural feedback), or one that employs gamification elements such as points, badges, or achievements. However, even though some of these serious game systems are designed together with physiotherapists and with the patients’ needs in mind, many of them end up not being used consistently during physical rehabilitation past the first few sessions (i.e. novelty effect). Thus, in this project, we aim to 1) Identify, by means of literature reviews, focus groups, and interviews with the involved stakeholders, why this is happening, 2) Develop a set of guidelines for the successful deployment of serious games for rehabilitation, and 3) Develop an initial implementation process and ideas for potential serious games. In a follow-up application, we intend to build on this knowledge and apply it in the design of a (set of) serious game for rehabilitation to be deployed at one of the partners centers and conduct a longitudinal evaluation to measure the success of the application of the deployment guidelines.
First Virtual Reality Museum for Migrant Women: creating engagement and innovative participatory design approaches through Virtual Reality Spaces.“Imagine a place filled with important stories that are hard to tell. A place that embodies the collective experience of immigrant women during their temporary stay”. In this project the first museum around immigrant women in Virtual Reality is created and tested. Working with the only migration centre for women in Monterrey, Lamentos Escuchados, project members (professional developers, lecturers, and interior design, animation, media and humanity students) collaborate with immigrant women and the centre officials to understand the migrant women stories, their notion of space/home and the way they inhabit the centre. This VR museum helps to connect immigrant women with the community while exploring more flexible ways to educate architects and interior designers about alternative ways of doing architecture through participatory design approaches.Partners:University of Monterey (UDEM)Lamentos Escuchados
Journalisten die veel interactie met hun publiek hebben (zoals consumentenprogramma’s) ontvangen via diverse, vaak besloten, kanalen (Facebook Messenger, WhatsApp, e-mail, fora) een grote stroom tips en/of berichten. Radio Dabanga, bijvoorbeeld, een op Soedan gericht radiostation in Amsterdam en ook een redactie met veel publieksinteractie, krijgt alleen al via WhatsApp 500-3000 berichten per dag. Met een redactie van twee mensen kan niet alles gelezen worden. Maar zelfs als dat kon, dan kan nog niet alles geverifieerd. Het gevolg is dat berichten gemist worden, dat Dabanga-journalisten vooral zoeken naar hun al bekende afzenders, en dat zij permanent het gevoel hebben belangrijke informatie te missen, waardoor zij hun contacten tekort te doen. Dit consortium onderzoekt of data science technieken hierbij kunnen helpen. Natural language processing technieken kunnen helpen de berichtenstroom beter te structureren waardoor tips over laag-frequente onderwerpen niet over het hoofd gezien worden. Recommender systemen kunnen ingezet worden om een betrouwbaarheidsindex te ontwerpen voor tot nog toe onbekende afzenders. Het resultaat is dan minder ondergesneeuwde tips en minder ondergesneeuwde afzenders. De uitkomsten worden getest met journalistenpanels. Bij goede resultaten uit bovenstaande onderzoeken, bouwt het consortium een prototype van de Berichtentemmer: een tool die helpt berichten uit diverse kanalen per onderwerp te structureren. Daardoor kunnen journalisten hun netwerken beter en efficiënter benutten. Bij het bouwen van deze tool hoort ook dat de gebruikte algoritmen transparant moeten zijn voor de journalist en de presentatie van de resultaten niet sturend mag zijn. Het consortium bestaat daarom uit een ‘Data science’-projectgroep voor het ontwerpen en testen van de algoritmen, en uit een ‘Ethiek & design’-projectgroep voor het ontwerpen van richtlijnen over transparantie van de algoritmen en de datavisualisatie. Tenslotte is er een ontwikkelgroep bestaande uit een combinatie van studenten en professional developers. Zij bouwen het prototype.
