Semantic Data Analytics Hub

Many DSI members have increasing access to combinations of high-density data from real-life activities, environments, brain structures as well as individual data on multiple psychological and biological functions, skills, impairments and contexts for large numbers of individuals. According to the European Strategy Forum on Research Infrastructures (ESFRI) and OECD recommendations for dealing with such “new types of data”, such data can only be integrated in future analyses on the basis of analytics providing a way to automatize their integration and interpretation through innovative interpretation, not only classification, analytics, i.e., semantic activity analytics.  In order to exploit the huge transdisciplinary potential of the DSI membership, the DSI Roadmap 2019+ has identified the establishment of structures to develop and apply theory-driven “explainable AI” to automatize the interpretation of the health-related meaning of such data combinations (XAI 4 Health) for various stakeholders as a strategic goal. This will continue to make the DSI and its membership a driving force in establishing a new emerging field of semantic activity analytics that necessarily draws on the wide range of disciplinary expertise within the DSI membership committed to responsible AI.

Currently, our goal is to develop a technology platform for semantic activity analytics in order to store, organize, manage, and integrate multiscale individually assignable health-related activity data. We commit ourselves to developing theoretical models and analytical tools to produce theory-based data analytics. The interdisciplinary research group dedicated to this project consist of experts from health science, computer science, medical science, legal science and ethics with a track record of collaboration on the semantic analytics of multi-scale health dynamics.

Project coordination

  • Prof. Mike Martin (UZH)