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Big Data PPP Industrial Data Platforms - Towards cross-sectorial optimization and traceability
To start identifying synergies and to learn how different projects will address key data collection, sharing, integration, and exploitation challenges, a series of webinars have been organized under the umbrella of this Big Data Value PPP. These webinars are also organized by BDVA, BDVe project, and other projects which are part of this PPP.

Big Data PPP Industrial Data Platforms - Towards cross-sectorial optimization and traceability
To start identifying synergies and to learn how different projects will address key data collection, sharing, integration, and exploitation challenges, a series of webinars have been organized under the umbrella of this Big Data Value PPP. These webinars are also organized by BDVA, BDVe project, and other projects which are part of this PPP.

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  1. 1. KRAKEN (GoToWebinars, 8th May 2020) Big Data PPP Personal Data Platforms - "Empowering Citizens Leveraging their Data Power" Juan Carlos Pérez Baún, Atos This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871473 Brokerage and market platform for personal data www.krakenh2020.eu
  2. 2. 2www.krakenh2020.eu 1. Project Overview 2. Objectives 3. Key Innovations 4. Use cases and (key characteristics) of data sets involved 5. Expected business impact 6. Initial results 7. Challenges faced regarding data
  3. 3. 3www.krakenh2020.eu 1- KRAKEN Overview 1/2 Funded from the EU Horizon 2020 R & I programme under grant agreement No 871473 5M € 10 Partners 6 Countries Spain Italy Austria Slovenia Belgium Finland
  4. 4. 4www.krakenh2020.eu 1- KRAKEN Partners role 2/2 INDUSTRY PARTNERS • Coordinator • SSI • Technical Coordinator • Business Coordinator • SSI SMEs PARTNERS • Cryptography • Exploitation • Marketplace • Cryptography • Standardization • Health pilot RESEARCH ORGANIZATIONS • Cryptography • Standardization • Education pilot • Cryptography • Legal expert • UI
  5. 5. 5www.krakenh2020.eu 2- Objectives: Main objective 1/2
  6. 6. 6www.krakenh2020.eu 2- Objectives 2/2 • Implements a highly trusted and secure yet scalable and efficient personal data sharing and analysis platform • SSI management & user-centric • Regulatory compliant • Demonstrate in two high-impact pilots (Health & Education) • Create economic value and innovative business models supporting SMEs • Apply Agile methodology
  7. 7. 7www.krakenh2020.eu 3- Key Innovations & Timeline 1/1
  8. 8. 8www.krakenh2020.eu • A biomedical and wellbeing data marketplace connecting data providers • Individual citizens • Healthcare organizations • Sharing medical and wellness data streams with data consumers (academic research centers, health-tech companies, insurers, public authorities, wellbeing services providers) in exchange for economic value, in full compliance with the GDPR. • The platform will leverage existing blockchain data infrastructures: • MyHealthMyData (MHMD) • Streamr: decentralized P2P pub-sub system for transfer of data streams • 4 Use Cases (sell, buy, monetize and Data Analytics aaS) 4- Use cases: Health pilot 1/4
  9. 9. 9www.krakenh2020.eu • Health records: medical histories lab results procedures etc • Health and wellbeing, real-word data by mobile apps and wearable devices: heart rate dietary physical activity etc DATA PRODUCERS Individuals, hospitals, data unions, app providers, patient associations, etc. • Data-driven biomedical research: disease biomarkers, innovative drugs and therapeutic approaches, disease characterization • Clinical trials: patient stratification, virtual cohort generation • Clinical decision marking: early diagnosis, patient management and stratification, therapy assignment • Medical device development: design, testing and validation • Artificial Intelligence: algorithm training and validation, real-time AI stream processing and analytics • Human resources management systems, Recruitment companies, professional social networks. • Insurance companies • Disease risk profile determination • Data analytics services DATA DATA BUYERS Research centers, AI developers, insurance companies, device manufacturers, etc. 4- Use cases: Health pilot types of data 2/4 UTILITY
  10. 10. 10www.krakenh2020.eu • Data marketplace connecting data providers • Students • Sharing grades, certifications, courses with data consumers (recruitment agencies) in exchange for economic value, in full compliance with the GDPR. • Use of a dedicated Linkedin page as recruitment company • 3 UCs where produce academic data, purchase/access data, processing academic data 4- Use cases: Education pilot 3/4
  11. 11. 11www.krakenh2020.eu Certification Enrolment status Student career path Student qualifications DATA OWNERS Students to trade their academic records in a privacy-preserving way • Human resources management systems, Recruitment companies, professional social networks. • Training, education, life-long learning institutions • Market consultants, Research and advisory companies • Government, education ministries, European networks (Eurydice, ENQA) DATA BUYERS Recruitment agencies to acquire this data and process it, keeping the student's privacy intact. DATA UTILITY 4- Use cases: Education pilot types of data 4/4
  12. 12. 12www.krakenh2020.eu KRAKEN develops a trusted and secure personal data platform with state-of-the-art privacy aware analytics methods, guaranteeing on metadata privacy, including query privacy Benefits for Data Subjects Increased trust thanks to high security and privacy by design . No information are stored into the public ledger Real control over their own data. Everything is stored in a wallet under user’s control Make profit from data Easy Access to data Added value data through data-driven services, analytics tools and new AI-based models New improved business services* thanks to added value data GDPR responsibility decreases thanks to the use of privacy-protection schema Benefits for Data Users * health prevention, education certification etc. A shift from trusting central authorities to trusting math Based on Blockchain technology and Distributed Ledger every information can be easily verifiable 5- Expected Business Impact 1/1
  13. 13. 13www.krakenh2020.eu 6- Initial results: Agile methodology 1/4
  14. 14. 14www.krakenh2020.eu • Taiga: Project management and issue tracking • Slack: Communication tool between partners • Mural: Work in a collaborative way between partners at the same time • GitLab CE: Source repositories and wiki • Jenkins: continuous integration and deployment CI/CD • Sonarqube: Quality assurance • Nexus: Binary artefacts repository 6- Initial results: Tools Availability 2/4
  15. 15. 15www.krakenh2020.eu WP2 Architecture specifications • Architecture initial version • Leverages ESSIF for eIDAS connection 6- Initial results: Technical 3/4 WP3 Decentralised Ledger Solutions • Specifications from WP2 WP4 Crypto technologies & Analytics • Data Analytics as a Service • Very draft 1st version of FE prototype
  16. 16. 16www.krakenh2020.eu WP6 Business, Exploitation & Communication • https://www.krakenh2020.eu/ • Social channels (Twitter, Linkedin, Zenodo) 6- Initial results: WPs 3/6 ESSIF Liaison • The European self-sovereign identity framework (eSSIF) • Part of European Blockchain Service Infrastructure (EBSI) • Use eSSIF infrastructure for eID authentication • Contribute to this initiative: Collaborative development
  17. 17. 17www.krakenh2020.eu Returns the control of personal data back into the hands of data subjects and data owners and its subsequent use Ensure the personal data platforms respect of prevailing legislation Apply the GDPR in the context of ICT in healthcare Secure data access and secure data sharing on cloud-based storage systems Create economic impact and increase value- creation from personal data. Contribute to the economic value of data The lack of trusted and secure platforms and privacy-aware analytics methods for secure sharing of personal data and proprietary data Implement data privacy protection methods 7- Challenges faced regarding data Preserves utility for data analysis and allow for the management of privacy/utility trade-offs, metadata privacy, including query privacy
  18. 18. Thank you for your attention ! << Juan Carlos Pérez Baún >> << juan.perezb@atos.net>> This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 871473 www.krakenh2020.eu @KrakenH2020 Kraken H2020

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