SDIL bridges the gap between cutting-edge research and industrial big data applications.
The Smart Data Innovation Lab (SDIL) offers big data researchers unique access to a large variety of big data and in-memory technologies. Industry and science collaborate closely to find hidden value in big data and generate smart data. Projects focus on the strategic research areas of Industry 4.0, Energy, Smart Cities and Personalized Medicine.
The main goal of the SDIL is to accelerate innovation cycles using smart data approaches.
In order to close today’s gap between academic research and industry problems using a data-driven innovation cycle, the SDIL provides extensive support to all collaborative research projects free of charge.
The hardware and software provided by the SDIL platform enable researchers to perform their analytics on unique state-of-the-art hardware and software without acquiring, for example, separate licensing or dealing with complicated cost structures. It gives a chance to industrial data providers to analyze their data together with an academic partner in a fully secured on-premise environment at KIT.
SDIL provides access to experts and domain-specific skills within Data Innovation Communitiesfostering the exchange of project results. They further provide the possibility for open innovation and bilateral matchmaking between industrial partners and academic institutions.
Legal and Security
Template agreements and processes ensure fast project initiation at maximum legal security fit to the common technological platform. A standardized process allows anyone to set up a new collaborative project on SDIL within 2 weeks.
The SDIL guarantees a sustainable investment to all partners by curating industrial data sources, best practices, and code artifacts, that are contributed on a fair share basis. Furthermore, it actively includes open data and encourages open source developments to augment the unique industrial grade solutions provided within the platform.
The SDIL offers various anonymization tools to its projects which are applicable to data from research and industrial sources.