1. Geneva, Switzerland, 20-21 March 2012 Innovation in big data analytics: from lab to market to standards Filippo Dal Fiore, PhD M.I.T. Senseable City Lab & Currentcity dalfiore@mit.edu ITU Workshop on ICT Innovations (Geneva, Switzerland, 20-21 March 2012)

2. Geneva, Switzerland, 20-21 March 2012 2 What the Senseable City Lab does Data analyses and visualizations Smart objects

3. Geneva, Switzerland, 20-21 March 2012 3 What the Currentcity spin-off does Data analytics applications

4. Our specialty within big data analytics: collective sensing Aggregated and anonymized data from telecom and web 2.0 networks is used as a proxy for human presence and activities, on an historical basis and in real- time.

5. How we pursue innovation in the Lab Industrial collaborations in which we “tweak” with proprietary data/sensors Reliance on open-source SW solutions Scalability and standardization issues not of immediate relevance Creative, “keep options open” approach Geneva, Switzerland, 20-21 March 2012 5

6. 6 How we pursue innovation in the spin-off Emphasis on user acceptance, revenue generation, future scalability Explorative, “keep options open” approach Difficulty to spot markets make the standardization question premature Benefiting from previous standards (i.e. GSM/UMTS), but only up to a certain point

7. Big data analytics: a Babel of data and operations on them Multi-level value chain: data generation  data storage  data query & extraction  data analysis  data fruition The possibility for multiple combinations are “infinite”: standardization to be applied at multiple levels Geneva, Switzerland, 20-21 March 2012 7

8. Big issues in big data analytics Data ownership Data security Data privacy Data formats & legacy data system Patchwork of laws and regulations Geneva, Switzerland, 20-21 March 2012 8

9. The need for standardization in big data Data reside within different companies and is silo-related (i.e. finance/health-care/energy) Need for (individual/urban) data portfolios “Data banks” as gateways for new data markets (data transactions as monetary transactions) Geneva, Switzerland, 20-21 March 2012 9

10. In absence of standards, big data is managed in big pooled datasets, but this lead to: Increased vulnerabilily (i.e. hacker attacks) Proliferation of consent and data use agreements; Inflexible, stale and inaccurate datasets; (source: Helmore, 2012) Geneva, Switzerland, 20-21 March 2012 10

11. Conclusions and Recommendations ??? Geneva, Switzerland, 20-21 March 2012 11