BIG DATA EUROPEBIG DATA EUROPE:CONCEPT AND PLATFORMNCSR Demokritos20 December 2016

Big Data Europe (CSA: 2015-17) Show societal value of Big Data

o Across all societal challenges addressed by Horizon 2020

Lower barrier for using big data technologieso Effort and resources to convert tools and workflows

o Skills and expertise

H l bli h d l h i Help establish data value chainso Across languages, organizations and domains

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Consortium

NCSRDEMOKRITOS

Stakeholder Engagement

Stakeholder engagement workshops:g g p Present the action and its

showcase deployments Raise awareness about BDE results

and what they mean for stakeholders

Collect requirements to drive further development

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Societal Soc e aChallenges

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Architecture

Big Data Integrator (BDI):o The prototype developed by BDE

Main points of the architecture Main points of the architectureo Dockerization

Support layer including integrated UIo Support layer, including integrated UIo Semantification layer

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Docker containers

Docker offers lightweight virtualizationo Docker containers can be shared to be provisioned on different

Linux variations and versions

Identical base sys not required

All BDI components: Docker containers

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Docker containers

BDI components Processing and storage components

o Re-used existing docker containers where availableo Dockerized by BDE where noto Ensured all can be provisioned through Docker Swarm

Components by BDE:o Support Layero Semantic Layer

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BDE Docker Containers

D t i HDFS C d 4 t Data serving: HDFS, Cassandra, 4store, PostGIS, Strabon, Elastic Search, Hive, SemagrowSemagrow

Processing: Spark, Flink, Sansa Stream ingestion middleware: Flume,

Kafka

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Semantic layer tools

BDE tooling for Semantic Data Lake:go Swagger: Semantics of RESTful APIso Semantic Analytics Stack (SANSA): y ( )

Distributed data processing for large-scale RDF data

o Semagrow: SPARQL perspective over Big Data stores

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Questions? BigDataEurope Web site:

https://www.big-data-europe.eu

Thank you for your attention!

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