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BigDataEurope: Project Introduction @ Year #1 Workshops
The document outlines a series of workshops aimed at empowering communities through big data technologies, emphasizing the significance of managing the vast amounts of data generated daily. It discusses the dimensions of big data, the challenges it presents, and the objectives of the Big Data Europe project, which include fostering societal value and lowering barriers to technology use. Additionally, it highlights ongoing activities, stakeholder engagement, and the creation of various interest groups focused on specific societal sectors.
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BigDataEurope: Project Introduction @ Year #1 Workshops
- 1. Empowering Communities with DataTechnologies Year #1 Series of Workshops General Overview BIG DATA EUROPE
- 2. The Motivation –Big Data Every day, we create 2.5 quintillion bytes of data — so much that 90% of the data in the world today has been created in the last two years alone. This data comes from everywhere: sensors used to gather climate information, posts to social media sites, digital pictures and videos, purchase transaction records, and cell phone GPS signals to name a few. This data is big data. Source:
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- 4. Big Data: Dimensions www.big-data-europe.eu Volume Velocity Variety 100010101010101010101010 010100101010101010010100 101010010100101010010100 101001010100101010100101 010001010101010010101010 101010101001010101010101 001010101110001010101010 101010101001010010101010 101001010010101001010010 101001010010100101010010 101010010101000101010101 00101010101 1000101010 1010101010 1010010100 1010101010 1001010010 ……. …………. …… ………..……. . …………… 10 1000101010 1010101010 1010010100 1010101010 100101oo11 Veracity!
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- 6. Health Climate Energy Transport Food Societies Security Big Data inEurope: Challenges, Opportunities www.big-data-europe.eu Loremi psumd olors KSDJ OPSC KKSD KAB LKASJL LAWWD S wpweppe pwpisio we 101010 011010 100101 010 Regional Data Repositories #1: Compile, Harmonise, Publish 101010 011010 100101 010 101010 011010 100101 010 #2: Interlink, Centralise Access, Explore 101010100101010101001 011010001010101010010 101010100001011010001 010101010010101010100 100101010100101010101 001011010001010 Data Eleme nt #3: Analyse, Discover, Visualise #4: Mashup, Cross-domain Exploitation Journalists Authorities
- 7. Big Data inEurope: Obstacles 21-mai-15www.big-data-europe.eu #1 Big Data “Variety“ problem Multiple Data Sources Required: Integration, Harmonisation #2 Opening-up Data concerns Loss of control, lack of tracking Reservations about large corporations #3 Limited Skills, Training, Technology Lack of Data Scientists Lack of Generic Architectures, components
- 8. Data Value ChainEvolution 21-mai-15www.big-data-europe.eu Extraction, Curation Quality, Linking, Integration Publication, Visualization, Analysis Extraction, Curation, Quality, Linking, Integration, Publication, Visualization, Analysis Health Transport Security Extraction Curation Quality Linking Integration Publication Visualization Analysis Data Repositories Linked Open Data Cloud Stage 1 Stage 2 Stage 3 Food SocietiesClimate Energy
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- 10. Rationale Show societalvalue of Big Data Lower barrrier for using big data technologies o Required effort and resources o Limited data science skills Help establishing cross- lingual/organizational/domain Data Value Chains 21-mai-15
- 11. BigDataEurope: Objectives 21-mai-15www.big-data-europe.eu COORDINATION Stakeholder Engagement (RequirementsElicitation) SUPPORT Design, Realise, Evaluate Big Data Aggregator Platform Create and Manage Societal Big Data Interest Groups Cloud-deployment ready Big Data Aggregator Platform CSA Measures Results
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- 13. Big Data Ecosystems:Orthogonal Dimensions 21-mai-15www.big-data-europe.eu Generic Big Data Enabling Technologies Data Value Chain Data Generation & Acquisition Data Analysis & Processing Data Storage & Curation Data Visualization & Usage Data-driven Services SocietalChallenges DomainSpecificDataAssets&Technology Healthcare Food Security Energy Intelligent Transport Climate & Environment Inclusive & Reflective Societies Secure Societies
- 14. Work Packages &Phases Community Building M1-M12 M13-M24 M25-M36 Enabling Technologies Component Integration Uptake Integrator Deployment Community Assessment WP3 – Big Data Generic Enabling Technologies & Architecture WP5 – Big Data Integrator Instances WP7 – Dissemination & Communication WP2 – Community Building & Requirements WP4 – Big Data Integrator Platform WP6 – Real-life Deployment & User Evaluation
- 15. Societal Domains, FocusAreas, Data assetts Societal Domain Preliminary Big Data Focus area Selected Key Data assets Life Sciences & Health Heterogeneous data Linking & integration Biomedical Semantic Indexing & QA ACD Labs / ChemSpider, ChEBI, ChEMBL, Con-ceptWiki, DrugBank, EN- ZYME, Gene Ontology, GO Annotation, Swis-sProt, UniProt, Wik- iPathways, PubMed, MeSH, Disease Ontology (DO), Joint Chemical Dic- tionary (Jochem), Bio-ASQ datasets Food & Agriculture Large-scale distributed data integration INFOODS, AQUASTAT Green Learning Network (GLN), Agricultural Bibliography Network (ABN), AGRIS, AquaMaps, Fishbase Energy Real-time monitoring, stream processing, data analytics, and decision support European Energy Exchange Data, smart meter measurement data, gas/fuels/energy market/price data, consumption statistics, equipment condition monitoring data) Transport Streaming sensor network & geo-spatial data integration GTFS data, OSM/ LinkedGeoData, MobilityMaps, Transport sensor data, ROSATTE Road safety attributes, European Road Data Infrastructure - EuroRoadS Climate Real-time monitoring, stream processing, and data analytics. European Grid Infrastructure (EGI), Databases hosting atmospheric data. Several software frameworks for simulation, calibration and reconstruction. Social Sciences Statistical and research data linking & integration Federated social sciences data catalogs, statistical data from public data portals and statistical offices (e.g. EuroStats, UNESCO, WorldBank) Security Real-time monitoring, stream processing, and data analytics. Earth Observation data (e.g. Very High Resolution Satellite Imagery acquired from commercial providers and governmental systems) and collateral data for supporting CFSP/CSDP missions and operations,
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- 17. Data Aggregator Platform: Blueprint BatchLayer Speed Layer Data Storage Real-time data & Transactions … Batch View Real-time View messagepassing message passing Applications & Showcases Real-time dashboards Domain-specific BDE apps Big Data Analytics In-stream Mining BDEPlatform& Intelligence Input data Stream Spatial Social Statistical Temporal Transaction al Imagery + Semantic Layer (Retaining Semantics using LD Lambda Architecture
- 18. Current Activities –Year#1 2015 BDE Societal Workshops (7) Planned o Schedule on Website 7 W3C Interest Groups set up: Please Join! o SC1: HEALTH https://www.w3.org/community/bde-health/join o SC2: FOOD & AGRICULTURE https://www.w3.org/community/bde-food/ o SC3: ENERGY https://www.w3.org/community/bde-energy/ o SC4: TRANSPORT https://www.w3.org/community/bde-transport/ o SC5: CLIMATE & ENVIRONMENT https://www.w3.org/community/bde-climate/ o SC6: SOCIETIES https://www.w3.org/community/bde-societies/ o SC7: SECURITY https://www.w3.org/community/bde-secure-societies/ www.big-data-europe.eu
Editor's Notes
- #12 Two clearly defined coordination and support measures: Coordination: Engaging with a diverse range of stakeholder groups from SCs Collecting requirements for the ICT infrastructure needed by data-intensive science practitioners covering all aspects of publishing and consuming semantically interoperable, large-scale data and knowledge assets Support: meets requirements minimises disruption to current workflows, maximises the opportunities to take advantage of the latest European RTD developments BigDataEurope will implement and apply two main instruments to successfully realize these measures: Build Societal Big Data Interest/Community Groups in the W3C interest group scheme & involving a large number of stakeholders from the Horizon 2020 societal challenges as well as technical Big Data experts; Design, integrate and deploy a cloud-deployment-ready Big Data aggregator platform comprising key open-source Big Data technologies for real-time and batch processing, such as Hadoop, Cassandra and Storm.