Title : On Amsterdam Data Science – who we are, what we do, and how you can connect

Presenter Eva Kenny
Abstract Amsterdam Data Science (ADS) is a collaboration of CWI, HvA, UvA (Amsterdam Business School and Informatics Institute) and VU (Computer Science). ADS accelerates data science research by connecting, sharing and showcasing world-class technology, expertise and talent from Amsterdam on a regional, national andinternational level. Our research enables business and society to better gather, store, analyse and present data in order to gain valuable insights and makeinformed decisions. I will present an update on current projects and future plans including a new initiative: Amsterdam School of Data Science. This virtual School will provide a summary of all data science related study options available at HvA, UvA, VU. The idea is to have one site to showcase the large portfolio of data science related study available in Amsterdam. Feedback throughout the presentation is most welcome on current projects and ideas for future plans.

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Presenter Darya Tarasowa
Abstract A major obstacle of increasing the efficiency, effectiveness and quality of education is the lack of widely available, accessible, multilingual, timely, engaging and high-quality educational material. The creation and maintenance of comprehensive OpenCourseWare is tedious, time-consuming and expensive, with the effect that often courseware employed by teachers, instructors and professors is incomplete or outdated. Universities create much of the world's intellectual capital and are eager to share this knowledge beyond the walls of the academy and to grant access to education for everyone. Unfortunately, academic institutions have found it difficult to scale the significant organizational, technical, and cost barriers to distribution of rich OpenCourseWare while supporting the content interoperability and keeping the quality of the shared content high. The aim of the thesis is to develop a concept for a collaborative authoring platform, supporting reusable and remixable educational content. Our systematic literature study revealed the lack of crucial conceptual and technological approaches supporting the large-scale collaboration on this type of content. Namely, the issues of content localization, remixing and repurposing, as well as user engagement and coordination techniques were not yet sufficiently researched. In the thesis we have researched, adapted and integrated collaborative authoring strategies in a comprehensive approach, which comprises the following pillars: - In order to engage and coordinate collaborators we have developed the CrowdLearn concept, that applies social networking techniques to the structured content development. - To facilitate the content reuse and repurpose we have developed the WikiApp data model, that presents the content as a sequence of content revisions, each of which can be operated and reused independently. - In order to enable a fully-featured collaboration on multilingual educational content we have developed the CoSMEC concept, which allows synchronization and co-evolution of the content between its versions in different languages. We have implemented and evaluated the developed concepts within the web-based SlideWiki framework. The application deals with two main types of structured content objects: slide sets and self-assessment items attached to the slides. Both content types can be authored and maintained collaboratively, with enhanced possibilities for cross-lingual reuse and repurpose. The SlideWiki platform involves both teachers and students into the content development process, thus increasing quality not only of the developed content, but of the learning process in general.