BigDataEurope @BDVA Summit2016 2: Societal Pilots
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Transcript of BigDataEurope @BDVA Summit2016 2: Societal Pilots
Talk outline
The BigDataEurope Project & Mission [2 slides] The Big Data Integrator (BDI) platform [3 slides] 7 Pilots for the 7 Societal Challenge Domains
o Overview o SC4 (Transport: Traffic Conditions Estimation)o SC7 (Security: Event Detection) [DEMO]
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Supporting the Societal Domains with Big Data Technology
BigDataEurope Project
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BigDataEurope Action EC Horizon 2020 Coord. & Support Action
o ~5mio €, 2015-2017
Lower barrier for using BD technologieso Setup & deploy use-case workflows, lack of expertise
Show societal value of Big Datao Across 7 H2020 societal challengeso Establish data value chains across domains & orgs.
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Data Value Chain Evolution
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Extraction, Curation Quality, Linking, Integration
Publication, Visualization, Analysis
Extraction, Curation, Quality, Linking, Integration, Publication,
Visualization, Analysis
HealthTransport
Security
Extraction Curation Quality Linking Integration Publication Visualization Analysis
Data Repositories
Linked Open Data
TIME
Food SocietiesClimate EnergyProprietary, ‘locked-in’solutions
OS Solutions,Big Data Stacks
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A flexible, generic platform for (Big) Data Value Chain Deployment
Big Data Integrator
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• Must be considered at: data acquisition, data processing and data display level
• A need to find a solution to accommodate all 3 levels
• It is an important concern to most SCs• Common feeling “better integration solution of wider variety of data
leads to better statistics”
• Most help in this direction is needed by SC1 and SC5, remains an important aspect for All SCs
• Decisions depend on results of statistics which are as good as the data quality which is used
SC1 SC2 SC3 SC4 SC5 SC6 SC7
Societal Perception of the 4 V’s
Platform Requirements
Big Data Integrator: Architecture Key points
o Stacks Open Source solutions (Free)
o Dockerization
o Facilitates integration and deployment
o Plug-and-play BD Platform
o Cloud-deployment ready
Key BDE additionso Support layer: integrated UI
o Semantification layer6-déc.-16www.big-data-europe.eu
Big Data Integrator: In-Use
Big Data Integrator:https://github.com/big-data-europe
WIKI : extensive documentation, information on supported components, instructions, etc.
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Demonstrating the Societal Value through 7 Pilot ‘Real-world’ use-cases
1. Overview
BigDataEurope Pilots
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Pilots: Overview
SC1: Health & Pharm.
SC2: Food & Agr.
SC3: Energy
SC4: Transport
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SC5: Climate
SC6: Social Sciences
SC7: Security
7 Pilots
◎ BDI Platform Instantiationso Allow end-users to easily deploy functionality in own system environment o Modularized Docker approach - easier to replace componentso Reduces effort to keep 3rd party software updated & integrated
◎ 7 Societal Challenge Pilots o Aligned with 7 European Commision H2020 Societal Challengeso Real-world use-cases (Data, Objectives, Solutions)o Some pilots have different data & objectives but a similar solution
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SC1: Pharmacology research
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Life Sciences & Health
• Query a large number of datasets, some large
• Existing elaborate ingestion and homogenization by OpenPHACTS
• Extensive toolset developed by OPF and others
Objective: Large-scale heterogeneous pharma-research data linking & integration
SC1: Architecture & Components
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• Replicate Open PHACTS functionality on the BDE infrastructure using OS solutions• Based on Virtuoso, proprietary
distributed database• Apply to other domains (e.g.
Agriculture)• Porting to BDI gives flexibility
and enables new functionalities• Logging & system health monitoring
SC2: Viticulture resources
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Food and Agriculture
Objective: Automate publication ingestion and thematic classification• AgInfra is a major
infrastructure for agriculture researchers, serving cross-linked bibliography, data, and processing services
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SC2: Architecture & Components
• BDI deployed as an external infrastructure for processing text (viticulture publications)
• Storing and processing text at a larger scale than AgInfracan currently manage
SC3: Predictive maintenance
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Energy
• Wind turbine monitoring applies computational models to sensor data streams
• Models are weekly re-parameterized using week’s data from multiple turbines
Objective: Real-time turbine monitoring stream processing and analytics
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• Existing in-house non-scalable solution for model parameterization• Reliable Fortran software for data analysis• Efficient, but not scalable to data volume
• Developing a BDI orchestrator• Re-uses existing software unmodified• Makes it easy to apply in parallel to many
datasets and manage the outputs
SC3: Architecture & Components
SC4: Traffic conditions estimation
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Transport
• Combines:• Traffic modelling from
historical data• Current measurements from a
taxi fleet of 1200 vehicles
Objective: Estimation of real-time traffic conditions in Thessaloniki
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• New Flink implementations of map matching and traffic prediction algorithms
• BDI provides access to varied data sources• PostGIS database with
city map• ElasticSearch database
of historical data• Kafka stream of real-
time data
SC4: Architecture & Components
SC5: Climate modelling
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Climate
• Preparing modelling experiments• Slicing, transforming, combining datasets• Submission and retrieval from modelling
infrastructure• Discovering and re-using previously
computed derivatives• Lineage annotation: computer derivatives
from datasets and model parameters• Finding appropriate past runs avoids
repeating weeks-long modelling runs
Objective: Supporting data-intensive climate research
• BDI offers:• Hive for managing data
in a way that can be retrieved and manipulated, rather than file blocks
• Cassandra stores structured and textual metadata for searching headers and lineage
• Existing infrastructure; stable, reliable software for parallel computation of models• BDI is deployed as an external infrastructure for preparing and managing datasets
SC5: Architecture & Components
SC6: Municipality budgets
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Social Sciences
• Ingestion of budget and budget execution data
• Multiple municipalities in varied formats and data models
Objective: Homogenized Budgetary data made available for analysis and comparison
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• BDI deployed as ingestion and storage infrastructure for external tools• Homogenizes variety of
data (JSON, CSV, XML, etc.)
• Exposes data as SPARQL endpoint serving homogenized data
• Existing analytics and visualization tools• Use SPARQL queries to retrieve only the relevant slices of the overall data
SC6: Architecture & Components
SC7: Change detection & verification
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Secure Societies
• Events are extracted from text published by news agencies and on social networking sites
• Events are geo-located and relevant changes are detected by comparing current and previous satellite images
Objective: Detect and Verify Events based on Satellite Imagery, News and Social Media
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Event Detection
Change Detection
• Re-implementation of change detection algorithms for Spark
• Parallel orchestrator for text analytics• Re-uses existing software• Scales to many input streams
• BDI provides:• Cassandra for text content and
metadata• Strabon GIS store for detected
change location• Homogeneous access to both for
analysis and visualization
SC7: Architecture & Components
Demonstrating the Societal Value through 7 Pilot ‘Real-world’ use-cases
2. In-depth look at the Transport Pilot
BigDataEurope Pilots
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Transport Pilot: Architecture & Objectives
“A scalable, fault-tolerant and flexible platform based on open source frameworks that can process unbounded data sets and graphs.”
Message Broker: Kafka Cluster
L. Selmi - BDE - Tech. Workshop
Apache Kafka is a high-throughput distributed durable messaging system
Apache Kafka
Stream and Batch Processor: Flink Cluster
L. Selmi - BDE - Tech. Workshop
Apache Flink is an open source platform for distributed stream and batch data processing.
Apache Flink
Storage and Indexing: Elasticsearch Cluster
L. Selmi - BDE - Tech. Workshop
Elasticsearch is a distributed open source document database built on top of Apache Lucene
Map-Matching & Prediction: Rserve
L. Selmi - BDE - Tech. Workshop
R is a free software environment for statistical computing. It is used in the pilot to run the map-matching and the prediction algorithms.
The R Project
Visualization
L. Selmi - BDE - Tech. Workshop
SC4 Pilot 1 can process real-time FCD data for map-matching and simple road segments classification (normal/congested)
Demonstrating the Societal Value through 7 Pilot ‘Real-world’ use-cases
3. Demonstration of the Security Pilot
BigDataEurope Pilots
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2nd round of Societal Workshops
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Transport 22 September 2016 Brussels Collocated with Big Data for Transport, Tisa workshop
Food&Agri 30 September 2016 Brussels Collocated with DG AGRI WP2018-20 stakeholder consultation
Energy 4 October 2016 Brussels Collocated with EC H2020 Info Day on “Smart Grids and Storage”
Climate 11 October 2016 Brussels Collocated with Melodies Project Event – Exploiting Open Data
Security 18 October 2016 Brussels Standalone WorkshopSocieties 5 December 2016 Cologne Collocated with EDDI16- 8th Annual
European DDI User Conference Health 9 December 2016 Brussels Standalone Workshop
Other Activities
Fresh set (7) of Societal Workshops in 2017
Various SC-focussed and general hangouts, follow!o Apache Flink & BDE (20 Oct) – available onlineo BDVA & BDE Webinar planned early next yearo Keep track on BDE Website (Events)
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WEB: www.big-data-europe.eu EMAIL: [email protected]
BIG DATA INTEGRATOR www.github.com/big-data-europe
PROJECT COORDINATION (Fraunhofer IAIS)Prof. Sören Auer, auer © cs.uni-bonn · de > Dr. Simon Scerri, scerri © cs.uni-bonn · deEIS Department/Group,Fraunhofer IAIS & CS Department Uni-Bonn, Bonn, Germany
Questions & Contacts
www.big-data-europe.eu6-déc.-16
#BigDataEurope
leads the FraunhoferBig Data Alliance