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.

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Presentation transcript:

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

Geneva, Switzerland, March What the Senseable City Lab does Data analyses and visualizations Smart objects

Geneva, Switzerland, March What the Currentcity spin-off does Data analytics applications

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.

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, March

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

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, March

Big issues in big data analytics Data ownership Data security Data privacy Data formats & legacy data system Patchwork of laws and regulations Geneva, Switzerland, March

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, March

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, March

Conclusions and Recommendations ??? Geneva, Switzerland, March