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EDI's view on Digital Innovation Hubs Working Group Meeting on Big Data and Artificial Intelligence

  1. v Digital Innovation Hubs Working Group Meeting on Big Data and Artificial Intelligence Brussels, 7th November 2018 Dr. Diego López-de-Ipiña González-de-Artaza Project Coordinator – University of Deusto/DeustoTech @edincubator
  2. 2 EDI: European Data Incubator
  3. 3 EDI Incubation Approach (I)
  4. 4 EDI Incubation Approach (II)
  5. 5
  6. 6 What’s in for startups?
  7. 7 Open Call for Data Providers
  8. 8 Benefits for Corporates ▪ Access to top-level startups sorting out your business challenge at no cost*. ▪ Participation in the selection of the startups. ▪ Link with state-of-the-art data-based solutions for your business. ▪ Potential opportunities for investment or technology purchase. ▪ Be part of one of the biggest incubation and acceleration programmes in Europe. *No hidden fees. The EC finances EDI for this scouting and preparation for investment activites under H2020 programme budget.
  9. 9 Open Call for Data Startups (2nd round)
  10. 10 EDI’s ultimate goal ▪ Foster Big Data Innovation connecting corporations with top EU-startups. ▪ Leverage corporations’ unused assets (data) for new business opportunities. ▪ Link with corporate venture capital to facilitate investments. ▪ Build the future of the Data Market, boosting Data Economy
  11. 11 EDI as a Digital Innovation Hub (I) • How has EDI helped companies to create new data-driven products and services? – So far 16 startups from 9 countries are addressing 10 challenges from 9 Data Providers in Europe, helping them into their Digital Transformation: • Energy sector: – Thermal power plant management – Detection of anomalies in smart meters – HVAC usage management and control optimization • Industry sector: – Predictive maintenance of robots • Retail: – Prevent fraud in cashiers • Transport/Smart Cities: – Pricing bundles for drivers in Porto – Improving road safety in Barcelona – Optimizing traffic flow in Berlin • Weather: – Quality control of weather forecast • Media: – Sentiment analysis in consumer journey
  12. 12 EDI as a Digital Innovation Hub (II) • What are the services most demanded by the companies? – Hard to say, only progressed into 2nd stage of incubation (EXPERIMENT) but … • For startups: – Access to good quality datasets from big corporations which are well documented/explained from Data Providers – Opportunity to showcase the potential of their solutions • For Data Providers: – Assurance dataset is not used beyond incubation programme – Opportunity to outsource creation of novel solutions to their problems • What are the main requirements and bottlenecks in helping companies to use data as the base for their new or improved business models/products/services? – Many companies have the data and knowledge domain but not the data analysis skills – Others have Data Science skills and open mind but lack access to datasets and knowledge on domain – Data providers afraid that they may lose control of data – Need to establish agreements between both sides – Lack of Data and AI culture in companies
  13. 13 EDI as Digital Innovation Hub (III) • How an EU-level network of big data innovation hubs could leverage the work done by the local DIHs in breaking the “data silos” and in fostering cross-border data sharing and re-use and trading of data assets? – Need not only for Datasets Marketplaces but also for Data Solutions – Huge opportunities from linking data from different sectors • EDI will address this by giving more importance to cross-domain/open challenges where datasets coming from outside can be used • Are there any concrete examples showing the added value of a collaboration between the current big data / AI initiatives and the Digital Innovation Hubs? – Our only experience is that FIWARE community startups have also applied for EDI and some have actually qualified for next phase • Are there any ideas on how to make such collaborations easier? What are the incentives for collaboration? – Self-benefit, data needs solutions, solutions need data
  14. v Thanks a lot! This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 779790