SINTEF s. Open (Linked) Data projects portfolio (EC FP7 and H2020) Dumitru Roman. SINTEF, Norway.

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1 SINTEF s Open (Linked) Data projects portfolio (EC FP7 and H2020) Dumitru Roman SINTEF, Norway dumitru.roman@sintef.no

2 Source: McKinsey nd_performance_with_liquid_information Source: Garner _JUN+2014_v2.pdf What is Open Data? A movement to make data available (primarily government data) Businesses and citizens can develop new ideas, services and applications Can support (government) transparency and accountability Gartner: By 2016, the use of "open data" will continue to increase but slowly, and predominantly limited to Type A enterprises. By 2017, over 60% of government open data programs that do not effectively use open data internally, will be scaled back or discontinued. By 2020, enterprises and governments will fail to protect 75% of sensitive data and will declassify and grant broad/public access to it.

3 Lots of open datasets on the Web A large number of datasets have been published as open data in the recent years Many kinds of data: cultural, science, finance, statistics, transport, environment, Popular formats: tabular (e.g. CSV, XLS), HTML, XML, JSON,

4 What is Linked Data? A method for publishing structured data on the Web An open technology stack developed by W3C Core standards: RDF, SPARQL Applications for representing and integrating data from disparate sources on the Web

5 5 ongoing projects in SINTEF DaPaaS prodatamarket SmartOpenData Infrarisk Proasense totaling ~ 3.4M Euro for SINTEF over

6 How can we simplify Open Data publication and consumption?

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8 Open Data as Tabular Data and its problems Tabular datasets publicdata.eu data.gov.uk Records organized in silos of collections Very few links within and/or across collections The nature of the relationships among records/collections is hidden Difficult to integrate/query Data is trapped!

9 Linked Data is great for Open Data but has been ignored by the mainstream Difficult to make it accessible to people Publishers Developers Data workers DaPaaS is packaging Linked Data to make it more approachable to the open data community

10 DaPaaS one package 3 audiences Helping publishing open data DaPaaS Project Reaching through data and applications Data Publisher Giving better, easier tools End-Users Data Consumer Application Developer Data Value Chain

11 DaPaaS means to making Open (Linked) Data easier to use A platform/hosting: to make it easy for publishers to put data on the web, and developers to publish their applications A portal: to help advertising data and applications availability - and enticing new users Tool-supported data transformation methodology: to make it easy for people with Excel knowledge to publish large amounts of high quality data API's with high-quality documentation: for processing large amounts of data reliably in order to create interactives, visualisations and transformations Make Linked Data more accessible to everyone!

12 DaPaaS Enablers Grafter Grafterizer (Graphical Tool & DSL) DaPaaS platform RDF database-as-a-service RDF DDP PLUQI Open Data Visualization-as-a-service (Rainbow)

13 How can we innovate (and make money) with (property-related) Open Data?

14 Administration & Operations Data Value Chains Customer segments Banks Marketing Departments. Public Administration Farmers and Land Owners.. Business products and services Consortium products and services (CCST, CCS, CAPAS, SoE, RVAS, SIM, NNAS) 3 rd party data-driven services Free datasets Consortium datasets 3 rd party datasets prodatamarket Platform Marketplace Data Contextualization Data Workflows Data Access Data Hosting Marketplace portal Data Discovery and Search Data Linking Monetization Data Providers/Owners Publicly available free data Consortium proprietary data 3 rd party proprietary data

15 Business case example Cadastral report service (CERVED) Property Price Historical Data (proprietary data) CERVED's Cadastral Data (proprietary data) Other 3 rd party data (open or non-open) ISTAT's Statistical Data (open data) prodatamarket New datasets CERVED Cadastral Report Service (CCRS) Banks SMEs and Large Companies (e.g. financial) OSM Contextual Geo Data (open data) 3 rd party services Data Providers/Owners Business products and services Customer segments Data Value Chain

16 Business case example Norwegian State of Estate (Statsbygg) Statsbygg s Companies Data (proprietary data) Norwegian Mapping Authority Cadastral Data (open data) SSB s Statistical Data (open data) Public Sector Property Leasing and Ownership data (open data) Universal Design of Public Buildings (open data) RA s Cultural Heritage Data (open data) prodatamarket New datasets STATSBYGG State of the Estate Service (SoE) 3 rd party services Leasing companies in private and public sectors Ministry of Local Government and Modernisation Data Providers/Owners Business products and services Customer segments Data Value Chain

17 Business case example Norwegian Subterranean Infrastructure (Evry) Norwegian Mapping Authority Cadastral Data (open data) Natural geographical data (open data) Municipality Subterranean Infrastructure data (open data) prodatamarket New datasets Subterranean Infrastructure Map App and Service 3 rd party services Municipality administration Entrepreneur projecting and planning Mobile workforce, e.g. excavation operators Data Providers/Owners Business products and services Customer segments Data Value Chain

18 How can we bridge the gap between GeoSpatial and Linked Data?

19 SmartOpenData: Linked Open Data for environment protection in Smart Regions Open Data publishing platform/tools for public & voluntary GeoSpatial data resources on rural areas - such as national parks Aims to help bridge the gap between GeoSpatial Data - from the SDI/INSPIRE world Linked Open Data (LOD) - from the Semantic Web world Pilots in environmental conservation, water monitoring, forest sustainability, environmental data reuse, agroforestry management

20 Novel indicators for identifying critical infrastructure at risk from natural hazards

21 Infrarisk A stress test framework to tackle the impacts of natural hazards on interdependent infrastructure networks Focus on rare low-frequency natural hazard events Access to and sharing of data, information and risk scenarios Integrated approach to hazard assessment

22 The Proactive Sensing Enterprise: From Sensing into Proactive enterprises

23 Proasense Support a transition from Sensing enterprises into Proactive sensing enterprises to go from reactive to proactive computing in order to prevent problems or capitalize on opportunities before they even occur Adoption of the Observe-Orient-Decide-Act (OODA) loop of situational awareness and development of corresponding technologies: a scalable, distributed architecture for the management and processing of IoT big-data that will enable continuous monitoring, detection of the need for service adaptation and propose corresponding changes in a (semi-) automatic way

24 Summary Open (Linked) Data a promising opportunity, together with technology for data integration from disparate sources for Big Data but difficult to use by the mainstream SINTEF has a portfolio of projects tackling this area and is looking for cooperation with Norwegian organizations interested in Open and Linked Data in the context of Big Data