Big Data - Where from Where to

Copyright © 2013 Hanmin Jung
Hanmin Jung
Head of the Dept. of Computer Intelligence Research
KISTI
Big Data:
Where from? Where to?

Very Recent Activities on Big Data
(National Science and Technology Commission) Member of Big Data
Technical Impact Assessment Committee
(Korea Communications Commission) Sub-committee Chair of Big Data
Forum
(Ministry of Knowledge Economy) Technical Secretary of Big Data
Program Planning Committee
(Ministry of Educational Science and Technology) Member of Big Data
Information Strategic Program Expert Committee
(National IT Industry Promotion Agency) Lecturer of Big Data Expertise
Reinforcement Program
Let Me Introduce Myself :-)
2

Copyright © 2013 Hanmin Jung3
Questions
Where are Big Data from?
Who gathers and consumes the data?
Is the data used for?

Smart Work
http://files.thinkpool.com/files/bbs/2010/07/21/%EC%8A%A4%EB%A7%88%ED%8A%B8%EC%9B%8C%ED%81%AC1.jpg
4

Cloud Computing
Service Platform Accelerated by Mobile Devices
http://simpleroot.com/wp-content/uploads/2012/10/Remote-Cloud-Computing.jpg
5

Cloud Computing – 建建建建て前前前前 & 本音本音本音本音
Introducing iCloud

Cloud Computing
Google Data Center
http://www.youtube.com/watch?v=avP5d16wEp0

Data Sources
Web -> Social -> Thing
“The next Google or Facebook may well be
an Internet of Things company.”
by R. MacManus (ReadWriteWeb)

Social Data
http://bynoy.files.wordpress.com/2011/08/united-noy-weblife-60-seconds.jpg

Machine Data
T. Baer, “What is Big Data? The Reality for Analytics”, OVUM, 2011.
Call data recordsCall data records
Sensory dataSensory data
Web log filesWeb log files
Financial Instrument TradeFinancial Instrument Trade

Internet of Things
K. Escherich, “Internet of Things”, 2011.

Big Data in the World
http://www.ektron.com/billcavablog/Big-Data-Big-Content-Big-Challenges/

Infographics for Big Data
http://thumbnails.visually.netdna-cdn.com/big-data_50291c3b16257.jpg

Google.com Traffic
http://siteanalytics.compete.com/naver.com/

Naver.com Traffic
http://siteanalytics.compete.com/naver.com/

Foreseeable Future
Google Project Glass
16

Hype Cycle

Hype Cycle – 2010
Emerging Technologies Hype Cycle 2010

Hype Cycle – 2011

Hype Cycle – 2012

Google Insights
http://www.google.com/insights/search/

Bottleneck in Data Ecosystem
http://quizzicaleyebrow.files.wordpress.com/2011/03/pict0044.jpg

Big Data Ecosystem
http://imexresearch.com/Newsletter_HTML/bd2.png

Big Data Ecosystem
New Approaches Required for
Persistence
Indexing
Caching and query optimization
Processing
Structure
Query language
Compression
24
T. Baer, “What is Big Data? The Reality for Analytics”, OVUM, 2011.

Insights for Search
http://www.google.com/insights/search/

Mobile Phone
Worldwide Market Share
Worldwide mobile device sales to end users in 2008 ~ 2012
Gartner, IDC Worldwide Mobile Phone Tracker
4.0, 14.14.3, 17.19.9, 47.8Apple
7.5, 23.011.0, 31.68.1, 28.45.4, 21.1LG
3.3, 15.8Huawei
Company
4Q2012
(%, M. Units)
3Q2011
(%, M. Units)
3Q2010
(%, M. Units)
3Q2009
(%, M. Units)
3Q2008
(%, M. Units)
Nokia 17.9, 86.3 27.1, 106.6 31.6,110.4 37.8, 108.5 38.6, 117.9
Samsung 23.0, 111.2 22.3, 87.8 20.5, 71.4 21.0, 60.2 17.0, 52.0
ZTE 3.6, 17.6 4.9, 19.1 3.5, 12.1
Sony Ericsson 4.9, 14.1 8.4, 25.7
Motorola 4.7, 13.6 8.3, 25.4
Others 42.3, 203.8 36.1, 142 32.2, 112.5 20.6, 59.1 20.1, 61.5
Total 482.5 393.7 348.9 287.1 305.4
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CDC Influenza Summary
http://www.cdc.gov/flu/weekly/usmap.htm

Google Flu Trends
J. Ginsberg, “Detecting influenza epidemics using search engine query data”

Voice Search Evaluation
http://static.googleusercontent.com/external_content/untrusted_dlcp/research.google.com/en//pubs/archive/40491.pdf

Causes of Death
http://image.guardian.co.uk/sys-files/Guardian/documents/2011/10/28/Factfile_deaths_2_2011.pdf

IBM Watson
http://powet.tv/powetblog/wp-content/uploads/2011/02/watson_the_computer_beats_ken_jennings_and_brad_rutter_at_jeopardy_full.jpg

Search
Clustering
Extracting
Decision
Support
Forecasting
Scenario
Planning
Advising
Modified from D. Bousfield & P. Fooladi, “STM Information: 2009 Final Market Size and Share Report”, 2010.
Value Pyramid
InSciTe Advanced (2011)
InSciTe Adaptive (2012)
OntoFrame (2005~2009)

Big Data & Decision Making
http://lithosphere.lithium.com/t5/Lithium-s-View/Big-Data-Analytics-Reducing-Zettabytes-of-Data-Down-to-a-Few/ba-p/36378
Reducing Zettabytes of Data Down to a Few Bits
Data help us make better decisions.
The primary function of analytics is to support decision making.
The challenge of big data analytics is
to reduce a lot of data down to a few bits.

Strategic Foresight
R. Rohrbeck, H. Arnold, and J. Heuer, “Strategic Foresight in Multimedia Enterprises”, 2007.
34

Quantitative Analytics

TI Projects
FUSE
Funded by IARPA (early 2011 ~ early 2016)
Kick off meeting in summer, 2011
Foresight and Understanding from Scientific Exposition Program
Seeks to develop automated methods that aid in the systematic,
continuous, and comprehensive assessment of technical emergence using
information found in the published scientific, technical, and patent
literature
Partners
BAE Systems, Brandeis Univ., New York Univ., 1790 Analytics, …

TI Projects
FUSE

TI Projects
CUBIST
Funded by the European Commission (late 2010 ~ late 2013)
1st CUBIST workshop in July, 2011
Combining and Uniting Business Intelligence with Semantic Technologies
Program
Aims to develop new ways to interrogate not only the massive volume data
on the Internet, but also analyze the different formats it exist in – such as
blogs, wikis, and video
Partners
SAP, Ontotext, Sheffield Hallam Univ., …
38

TI Projects
CUBIST

TI Projects
Common Technologies
Semantic technologies
Ontology, reasoning, URI scheme
Analytics model
BYOM (e.g. technology opportunity discovery model, technology
evolution model, formal concept analysis model)
Information extraction (InSciTe, FUSE)
Named entities and events/relations in textual documents
40

Our Vision & Architecture
41

42

Data Fact Sheet
Articles: 22.6 millions (9.8 millions for papers, 7.6 millions for patents, 5.3
millions for Web data)
All technical areas (2001~2011)
Named entities: 1.9 millions
Authority dictionary: 1.5 millions entries
LOD data: 290 GB (are being connected)
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Supporting Decision Making
http://4.bp.blogspot.com/-Pf1hkccZZh4/TWDJahBpL2I/AAAAAAAAASU/JHLpXi8d9AQ/s640/meetings.jpg

Data Scientist
http://philanthropy.com/blogs/innovation/matching-data-scientists-and-nonprofits/778

Evidence-based Decision Making
Advantages
Ensures that policies are responding to the real needs of the community
Highlight the urgency of an issue or problem which requires immediate
attention
Enables information sharing amongst other members of the public sector
Reduces government expenditure which may otherwise be directed into
ineffective policies or programs
Produces an acceptable return on the financial investment that is allocated
toward public programs
Ensures that decisions are made in a way that is consistent with our
democratic and political processes which are characterized by
transparency and accountability
http://www.abs.gov.au/ausstats/abs@.nsf/lookup/1500.0chapter32010
47

InSciTe Project
http://semantics.kisti.re.kr

Thank you
jhm@kisti.re.kr
“A lot of times, people don’t know what they want until you show it to them.”
by Steve Jobs
“Many people won’t be convinced until they’ve seen it for themselves.”
by Jakob Nielsen

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