Lead Trustworthy AI , Siemens
Sonja Zillner studied mathematics and psychology at the Albert-Ludwig-University Freiburg, Germany and accomplished her PHD in computer science specializing on the topic of Semantics at Technical University in Vienna. Since 2020 she is leading the Trustworthy AI Core Technology Module at Siemens Technology. From 2016 to 2019 she was invited to consult the Siemens Advisory Board in strategic decisions regarding artificial intelligence. She is chief-editor of the Strategic Research Innovation and Deployment Agenda of the new Partnership in AI, Data and Robotics, leading editor of the Strategic Research and Innovation Agenda of the Big Data Value Association (BDVA). She is author of more than 80 publications and more than 25 patents in the area of semantics, artificial intelligence and data-driven innovation.
Sonja is speaking at
The Data-driven Innovation (DDI) Workshop is based on the (DDI) Framework addressing the challenges of identifying and exploring data-driven innovation in an efficient manner. It guides entrepreneurs in scoping promising data-driven business opportunities by reflecting the dynamics of supply and demand by investigating the co-evolution and interactions between the scope of the offering (supply) and the context of the market (demand) in systematic manner.
In this workshop, business champions, entrepreneurs and interested techies will gain practical experiences of how to use the DDI Framework and Canvas for the continuous analysis of all influencing factors of data-driven business opportunities. The participants of the workshops will get to know a set of methods and tools that will guide them in redefining their own data-driven business opportunity.
We will take the opportunity of this EBDVF workshop to officially launch the DDI canvas site. We encourage you to contact us to assist you in using DDI, to share with us your return of experience to help us to improve the methodology or provide domain specific know how.
The DDI framework was developed and tested in the context of the Horizon 2020 BDVe project and is backed by empirical data and scientific research encompassing a quantitative and representative study of more than 90 data-driven business opportunities. The results of the research study guided the fine-tuning and updating the DDI framework as well as helped to identify success patterns of successful data-driven innovation. Currrently the DDI framework is used to run workshops with PPP projects, data-driven start-ups, SMEs and with corporates. It consists of a
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