VALS WP7 – Dissemination. Status at Salamanca final meeting

[EN]This presentation was made in the Final VALS project meeting in Salamanca (Spain) at February 11th – 12th 2016. It is devoted to present the current state of the dissemination of VALS project

Understanding the barriers to virtual student placements in the Semester of Code

The Semester of Code initiative organised virtual placements for university students around Europe, working on authentic business problems using open source software. The project was welcomed by stakeholders, and many companies and open source foundations became involved. However, the response from students was disappointing. In this paper we examine the reasons for this, discussing the results of the evaluation work carried out. Finally, we consider the implications of our work for student placements and the Knowledge Alliance European Union programme.La iniciativa Semester of Code organiza prácticas virtuales para estudiantes universitarios de toda Europa, trabajando en problemas reales de empresas que emplean software de código abierto en sus procesos de negocio. El proyecto fue bienvenido por todos actores involucrados, entre los que se encuentran varias empresas y fundaciones relacionadas con el software libre. Sin embargo, la respuesta por parte de los estudiantes fue menor de lo esperado. En este artículo se examinan las razones de ello, se discuten los resultados de la evaluación que se ha llevado a cabo. Finalmente, se reflexiona sobre las implicaciones del trabajo realizado para las prácticas en empresas de los estudiantes y el Programa Knowledge Alliance de la Unión Europea

VALS: Virtual Alliances for Learning Society

[EN] VALS has the aims of establishing sustainable methods and processes to build knowledge partnerships between Higher Education and companies to collaborate on resolving authentic business problems through open innovation mediated by the use of Open Source Software. Open Source solutions provide the means whereby educational institutions, students, businesses and foundations can all collaborate to resolve authentic business problems. Not only Open Software provides the necessary shared infrastructure and collaborative practice, the foundations that manage the software are also hubs, which channel the operational challenges of their users through to the people who can solve them. This has great potential for enabling students and supervisors to collaborate in resolving the problems of businesses, but is constrained by the lack of support for managing and promoting collaboration across the two sectors. VALS should 1) provide the methods, practice, documentation and infrastructure to unlock this potential through virtual placements in businesses and other public and private bodies; and 2) pilot and promote these as the “Semester of Code”. To achieve its goals the project develops guidance for educational institutions, and for businesses and foundations, detailing the opportunities and the benefits to be gained from the Semester of Code, and the changes to organisation and practice required. A Virtual Placement System is going to be developed, adapting Apache Melange, and extending it where necessary. In piloting, the necessary adaptations to practice will be carried out, particularly in universities, and commitments will be established between problem owners and applicants for virtual placements

SensoMan: Social Management of Context Sensors and Actuators for IoT

Sensor networks that collect data from the environment can be utilized in the development of context-aware applications, bringing into sight the need for data collection, management, and distribution. Boards with microcontrollers, such as Arduino and Raspberry Pi, have gained wide acceptance and are used mainly for educational and research purposes. Utilizing the information available via sensors connected to these platforms requires extended technical knowledge. In this work, we present a sensor management framework, SensoMan, that manages a collection of sensors spread in the environment connected to microcontroller boards. We present the framework’s architecture, a method for sensor data management, and a prototype system. Sensor data can also trigger the execution of actions on actuators. Thus, we further propose a rule engine as well as social connectivity following a scheme where sensors and their data can be shared among users. Our work shows that the creation of such a system is feasible and can use simple equipment (e.g., sensors, controller plugs) that can be replicated in other environments. The use of SensoMan is demonstrated via two scenarios that show its potential in combining simple tools that do not require an extended learning curve. A small-scale user study was also performed

Improving the\ua0Representation Choices of\ua0Privacy Policies for\ua0End-Users

Privacy policies provide users the possibility to get informed about how their data are being used by specific services and vendors. Unfortunately their texts are usually long and users are not devoting the required time to read them and understand their content. Tools that bring the privacy policies closer to the users can assist towards enhancing users’ privacy awareness. In this work, we are presenting the updated version of Privacy Policy Beautifier, our approach and accompanying tool that offers various representations of the privacy policy text, as a way to assist the users in better understanding the policy, devoting less time to explore its main content. Text highlighting, text summarization, word cloud, GDPR terms presence/absence are the techniques employed for the representations. The updated version of Privacy Policy Beautifier has been evaluated for its enhanced features via the participation of 32 users with promising results

Enhancing user awareness on inferences obtained from fitness trackers data

In the IoT era, sensitive and non-sensitive data are recorded and transmitted to multiple service providers and IoT platforms, aiming to improve the quality of our lives through the provision of high-quality services. However, in some cases these data may become available to interested third parties, who can analyse them with the intention to derive further knowledge and generate new insights about the users, that they can ultimately use for their own benefit. This predicament raises a crucial issue regarding the privacy of the users and their awareness on how their personal data are shared and potentially used. The immense increase in fitness trackers use has further increased the amount of user data generated, processed and possibly shared or sold to third parties, enabling the extraction of further insights about the users. In this work, we investigate if the analysis and exploitation of the data collected by fitness trackers can lead to the extraction of inferences about the owners routines, health status or other sensitive information. Based on the results, we utilise the PrivacyEnhAction privacy tool, a web application we implemented in a previous work through which the users can analyse data collected from their IoT devices, to educate the users about the possible risks and to enable them to set their user privacy preferences on their fitness trackers accordingly, contributing to the personalisation of the provided services, in respect of their personal data

SensoMan: Social Management of Context Sensors and Actuators for IoT

Sensor networks that collect data from the environment can be utilized in the development of context-aware applications, bringing into sight the need for data collection, management, and distribution. Boards with microcontrollers, such as Arduino and Raspberry Pi, have gained wide acceptance and are used mainly for educational and research purposes. Utilizing the information available via sensors connected to these platforms requires extended technical knowledge. In this work, we present a sensor management framework, SensoMan, that manages a collection of sensors spread in the environment connected to microcontroller boards. We present the framework’s architecture, a method for sensor data management, and a prototype system. Sensor data can also trigger the execution of actions on actuators. Thus, we further propose a rule engine as well as social connectivity following a scheme where sensors and their data can be shared among users. Our work shows that the creation of such a system is feasible and can use simple equipment (e.g., sensors, controller plugs) that can be replicated in other environments. The use of SensoMan is demonstrated via two scenarios that show its potential in combining simple tools that do not require an extended learning curve. A small-scale user study was also performed

RAGE Reusable Game Software Components and Their Integration into Serious Game Engines

This paper presents and validates a methodology for integrating reusable software components in diverse game engines. While conforming to the RAGE com-ponent-based architecture described elsewhere, the paper explains how the interac-tions and data exchange processes between a reusable software component and a game engine should be implemented for procuring seamless integration. To this end, a RAGE-compliant C# software component providing a difficulty adaptation routine was integrated with an exemplary strategic tile-based game “TileZero”. Implementa-tions in MonoGame, Unity and Xamarin, respectively, have demonstrated successful portability of the adaptation component. Also, portability across various delivery platforms (Windows desktop, iOS, Android, Windows Phone) was established. Thereby this study has established the validity of the RAGE architecture and its un-derlying interaction processes for the cross-platform and cross-game engine reuse of software components. The RAGE architecture thereby accommodates the large scale development and application of reusable software components for serious gaming