sc6 workshop 1: big data europe platform requirements and draft architecture: the results of the...

BIG DATA EUROPE BIG DATA EUROPE PLATFORM REQUIREMENTS & DRAFT ARCHITECTURE: THE RESULTS OF THE ONLINE SURVEY BIG DATA EUROPE WORKSHOP: THE CHALLENGES OF BIG DATA FOR SOCIETIES IN A CHANGING WORLD MARTIN KALTENBÖCK (SEMANTIC WEB COMPANY), 18.11.2015 HTTP://WWW.BIG-‐DATA-‐EUROPE.EU/

Integrating Big Data, Software & Communities for Addressing Europe’s Societal Challenges

Semantic Web Company (SWC)

SWC was founded 2001, head-quartered in Vienna

30 experts in linked data technologies & textmining

Product: PoolParty Semantic Suite (launched 2009)

Serving customers from all over the world

EU- & US-based consulting services

SWC: Customers & Partners

Some of our Customers ●  Credit Suisse ●  Boehringer Ingelheim ●  Roche ●  Wolters Kluwer ●  BMJ Publishing Group ●  Red Bull Media House ●  Canadian Broadcasting Corporation (CBC) ●  Pearson ●  Council of the EU ●  DG Environment, EC ●  Healthdirect Australia ●  Ministry of Finance (Austria) ●  World Bank Group ●  Inter-American Development Bank (IADB) ●  International Atomic Energy Agency (IAEA) ●  Buildings Performance Institute Europe (BPIE) ●  Renewable Energy & Energy Efficiency P (REEEP) ●  Global Buildings Performance Network (GBPN) ●  American Physical Society ●  Education Services Australia (ESA) ●  Norwegian Directorate of Immigration ●  Australian National Data Service

Finance / Automotive / Publisher / Health Care / Public Administration / Energy / Education

Selected Partners ●  EBCONT ●  EPAM Systems ●  iQuest ●  PwC ●  Tenforce ●  OpenLink Software ●  Ontotext ●  MarkLogic ●  Gravity Zero ●  Altotech ●  Wolters Kluwer ●  Taxonomy Strategies ●  Digirati ●  Fraunhofer (IAIS) ●  University of Leipzig (INFAI) ●  The Open Data Instizute (ODI)

We all have one goal in mind: Make machines smart enough so that they can help us to find those needles in the haystack, which are really relevant to us.

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: IBM

Big Data Dimensions

Rationale

COORDINATION Stakeholder Engagement (Requirements Elicitation)

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

BIG DATA EUROPE STAKERHOLDER ENGAGEMENT & REQUIREMENTS ENGINEERING APPROACH


BDE Stakeholder Engagement Approach & Activities

Work Packages & Implementation 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

Orthogonal Dimensions of Big Data Ecosystems

Generic Big Data Enabling Technologies

Data Value Chain

Data Generation & Acquisition

Data Analysis & Processing

Data Storage & Curation

Data Visualization &

Usage

Data-‐driven Services

Societal Challeng

es

Dom

ain Specific D

ata Assets & Techn

olog

y Healthcare

Food Security

Energy

Intelligent Transport

Climate & Environment

Inclusive & Reflective Societies

Secure Societies

Methodology of Requirements Engineering

BDE Approach & Methodology •  BDE Core Question Matrix as a basic Tool •  Online Survey (20.5. – 26.6.2015, 394 Participants) •  7 x 15 Face to Face Interviews (3 x 5 per SC) •  7 Workshops in 2015 (7 in 2016, 7 in 2017) •  7 BDE Pilot (Use Case) ideas / specifications

Requirements

Use case pilots

Online survey Interviews

BDE Core Question Matrix

Elements of the RE model

Questions to people within the specific Societal Challenge (grouped by type of interviewee)

Business Strategic Technical Domain Experts

Stories Question Question Question Question

In this element, stories which describe the current status and future development are asked Question Question Question Question

Personas Question Question Question Question In this element, typical personas which play a role are described Question Question Question Question

Data Question Question Question Question This element is to describe the data in amount, quality, type, usage, etc. Question Question Question Question

Technologies Question Question Question Question In this element, the technical requirements to our specific solution are described Question Question Question Question

Other Question Question Question Question

BDE Stakeholder Survey

The empirical methodology of online surveys generally coincides with problems of representativity. Samples generated through online surveys are regarded as biased, especially in terms of age, sex and education. Additionally lower response rates compared to other methods, self-selection and the lack of verifiability of demographic information provided by the respondents do not allow to draw conclus ions beyond the sample ascertained by the survey itself.

BDE Stakeholder Survey - Participants

Participants: sector and organisation size


Self-definition of role in the sector


Participation in EU funded projects


Years of IT Experience

BDE Stakeholder Survey - Results

Importance of Volume

Importance of Velocity


Importance of Variety

Efficiency of Data Infrastructures


Big Data

Volume

Velocity

Variety

Veracity

•  Not an issue •  Would be nice to have

•  Very important •  “mostly economic and Social Science data”

•  Not so much data •  “Increasingly important”

•  Very important “Data inconsistencies and ambiguities are solved before processing”


Investments in Big Data Technologies

Investments per Orgaisation Size

BDE Stakeholder Survey – Results: Growth of Data Volumes

BDE Stakeholder Survey – Results: Long Term Preservation

BDE Stakeholder Survey – Results: Long Term Preservation

¥  Long term preservation of data o  SC6 has the infrastructure in place for longterm

preservation of data o  “Current practice is a core service where data is held in a

central place within a national infrastructure, and secure remote access is provided to each social research team.”

¥  Data processing o  “We use small samples or just the “main information”’ of

data needed.”

BDE Stakeholder Survey – Results

Need of Processing Large Volumes of Data per Organisation Size

BIG DATA EUROPE TECHNICAL REQUIREMENTS & ARCHITECTURE / COMPONENTS


Blueprint of the Data Aggregator Platform

Batch Layer

Speed Layer

Data Storage

Real-time data & Transactions …

Batch View

Real-time View

mes

sage

pas

sing

message passing

Applications & Showcases

Real-time dashboards

Domain-specific BDE apps

Big Data Analytics In-stream Mining

BDE Platform

& Intelligence

Input data Stream Spatial Social Statistical Temporal Transactional Imagery

+ Semantic Layer

Lambda Architecture

Work distributor & monitor Work executorsWork in itiator

Spark master

dispatcher

Spark worker

Spark worker

Target situation

Spark master dispatcher

Spark worker

Spark worker

Worker1

Worker2

Worker3

Deployed situation

Big Data solutions – technical challenges

BDE platform – generic robust resource management

Announcements….

•  HangOut, 23.11.2015, 11.00am -12.00pm CET (SC2) INRA’s Big Data Perspectives and Implementation Challenges

•  HangOut, 25.11.2015, 14.00pm -15.00pm CET (SC1) Challenge of Health, Demographic Change and Wellbeing

•  HangOut, 08.12.2015, 11.00pm -12.00pm CET (SC3) Big Data in the energy domain

•  Big Data Europe MeetUp Vienna, 15.12.2015, 16:00-19:30pm CET, LINK •  2016 Conference on Big Data from Space, March 15, 2016, LINK

SEMANTiCS2016, early September 2016 in Leipzig, Germany, http://www.semantics.cc

EDF2016, 29-30 June 2016 Eindhoven, Netherlands, http://2016.data-forum.eu

BDE Channels for Societal Challenge 6

•  Overall Website: http://www.big-data-europe.eu •  SC 6 Website: http://www.big-data-europe.eu/social-sciences/ •  W3C Community Group: https://www.w3.org/community/bde-societies/ •  Subscribe BDE Newsletter: http://bit.ly/1PyhXRS

Contact the BDE Societal Challenge 6 network Domain: Ivana Ilijasic Versic (CESSDA): [email protected] Technical: Martin Kaltenböck (Semantic Web Company): [email protected]

Workshop 18.11. – Interactive Sessions

Session 1: Data in place in the Social Sciences and Humanities •  What are the most important data sources in social

sciences available / you are using (open / closed)? •  How are the characteristics along the 4 Vs of Big Data

regarding such sources (Volume - Variety - Velocity - Veracity)?

Session 2: Risks and Challenges of successful data management •  What are the most important challenges in data

management in social sciences? •  What are the most dangerous risks you can think of

regarding data management in social sciences? •  SWOT - Analysis

Session 3: Technological demands of data •  What technologies are in place in your organisations? •  What technologies are on your roadmap - or are you

evaluating at the moment? •  What are the most critical technological issues?

Session 4: Legal and policy demands of data •  Open Versus Closed data in social sciences? •  What are the most important legal issues in place? •  What needs to change regarding Policies to enable

more efficient data management in social sciences?

Martin Kaltenböck, [email protected] Semantic Web Company GmbH Mariahilfer Strasse 70/8, A-1070 Vienna +43-1-4021235 http://www.semantic-web.at http://www.poolparty-software.com http://slideshare.net/semwebcompany http://youtube.com/semwebcompany

Your Questions please….

www.big-data-europe.eu 27-Nov-15

#BigDataEurope

sc6 workshop 1: big data europe platform requirements and draft architecture: the results of the...

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