Seminar: Digital Norway built on international standards Lillehammer, Norway, November 9 th, 2016

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1 How can international standards contribute to the Big Data V's with simpler management of data Volumes, data Velocity, data Variety and data Veracity to support data Value? Seminar: Digital Norway built on international standards Lillehammer, Norway, November 9 th, 2016 Arne J. Berre, SINTEF IKT Avdeling for Nettbaserte systemer og tjenester Gruppe for Smarte systemer og data Leder av GEMINI senter for Big Data, SINTEF, NTNU, UiO Leder av Big Data Value Association, BDVA.eu, Technical Priorities arne.j.berre@sintef.no 1

2 Dr. Arne J. Berre, Chief scientist SINTEF Forskningsveien 1, Blindern 0314 OSLO, NORWAY Phone: E.mail: Dr. Arne-Jørgen Berre is chief research scientist at SINTEF. He is responsible for the Big Data area at SINTEF, and leader of the Norwegian GEMINI Center for Big Data with SINTEF, NTNU and UiO and leader of the European Big Data Value Association ( task force on Technical Priorities. He is representing SINTEF in the collaboration with the new Telenor AI Lab at NTNU. He has been working in the standardisation communities since 1989 with the Object Management Group (OMG) and since 1994 with CEN/TC287, ISO/TC2111 and OGG. He has been the editor for ISO/TC211/OGC ISO Conceptual Schema Language and ISO Geographic services and CEN/TC287 TR , Service centric view on SDI Spatial Data Infrastructures. He is Norwegian representative to ISO Service ontology and ISO JTC1 WG9 Big Data. He is currently involved in projects on Big Data, Linked data and Interoperability for Geospatial data and Earth Observation, Smart Cities, Telecom, Environmental monitoring, BioEconomies (Fishery, Forestry, Agriculture), Transport and Energy Smart Grids. He is a member of the Belmont forum on e- Infrastructure and Data Management for Environmental data.

3 Big Data PPP Horizon 2020 Funding, 500 Meuro,

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5 GEMINI Center for Big Data (SINTEF Oslo/Trondheim, NTNU Trondheim/Gjøvik, UiO Oslo) Cooperation on Big Data between SINTEF, NTNU og UiO 12 full professors, 4 associate professors, 10 researcher, 8 PhD candidates, 10+ Master students Synergy related to a common tool box, methods/techniques, courses and projects related to Big Data Connection to related areas on Applied AI, Data Science and High Performance Computing Technical topics for Big Data: Big Data Architectures Big Data Management Big Data Analytics Big Data Privacy, Protection and Security Big Data Visualisation Big Data Standardisation Appliction areas/sectors for Big Data: Industry sectors: Smart Cities, Oil&Gas, Energy&Utilities, Telecom, Manufacturing, Media, Finance/Insurance, BioEconomies (Fishery/Aquaculture, Forestry, Agriculture), EU Social challenges: Health, Food&Agriculture, Energy, Transport, Climate, Inclusive Societies, Secure Societies,

6 The Big Data V's Volume Velocity Variety Veracity Value Data at Rest Terabytes to exabytes of existing data to process Data in Motion Streaming data, requiring mseconds to respond Data in Many Forms Structured, unstructured, text, multimedia, Data in Doubt Uncertainty due to data inconsistency & incompleteness, ambiguities, latency, deception Data into Money Business models can be associated to the data Adapted by a post of Michael Walker on 28 November 2012

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8 Data Collection & storage Preparation Curation Data processing Analysis Value Sector 1 Sector 2 '' Sector 3 Data Processing Architectures BIO Batch, Data Interactive, Streaming/Realtime (Volume, Velocity) Sector n Data Visualisation and User Interaction 1D, 2D, 3D, 4D, VR/AR (Value, Visualisation) Data Analytics Descriptive, Diagnostic, Predictive, Prescriptive (Value, Veracity) Data Management Collection, preparation, curation, linking, access Structured, semi-structured, non-structured (Variability, Variety, Volume - Storage) Basic types Infrastructure Time series, Sensor Storage IoT Image, Video, Audio Text, Language Resources, Cloud Web Social Media Geo spatial.. Meta data Communication HPC Privacy Protection, Anonymisation, Security Standards Sectors, Application areas BDVA Reference Architecture Data types, across sectors ETP4HPC, Cloud/Services 5G ++

9 ISO JTC1/WG9 NIST Big Data Reference Architecture with BDVA Technical priorities Standards Analytics Data Management Visualisation Data Management Processing Architecture HPC, Cloud computing Basic types Time series, Sensor Data Management Processing Architecture Image, Video, Audio Text, Language Web Social Media Geo spatial.. Meta data Data protection Privacy Security Standards

10 European Interoperabiliy Framework 14/11/2016

11 DataBio project, ICT15 Big Data PPP, Large Scale Pilot ( ) (48 partners, 16 Meuro) SINTEF Fiskeri og Havbruk, SINTEF IKT med Sildefiskelaget, Fiskefartøy, o.a.

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