1. Keynote Speech:
“From Information Science to
Data Science to Smart Nation”
Prof. Toh Chai Keong
Assistant Chief Executive (Engineering & Technology)
Infocomm Development Authority
of Singapore
Pg 1
2. Welcome to Singapore!!
From Info Science
To Data Science
Challenges facing us
Smart Nation
Conclusion
OUTLINE
3. The science of creating, handling, and processing
information???
Some say it is “application” focus rather than development
Others say it is more tied to business, IT architectures and
operations
INFORMATION SCIENCE
5. Digital and New Media Marketing
Mobile & Ubiquitous Commerce
E-Commerce
E-Business
Enterprise Social Systems
Technology Strategy & Management
IT and Customer Relationship Management
Mobile Apps Development
Strategic IS Planning
IT in Financial Services
SOME NUS INFO SCIENCE MODULES
7. Business Process Modeling & Solution Blueprinting
Enterprise Integration & Service-Oriented Architectures
Information Security & Trust
Architectural Analysis
Enterprise Web Solutions (web portals)
Interaction Design & Prototyping
ADVANCED INFO SCIENCE TOPICS
8. NUS IS Research Areas SMU IS Research Areas
IS Healthcare ■ Cybersecurity
E-Commerce ■ Data Mgmt & Analytics
Social Computing ■ IS Mgmt
Service Integration ■ Intelligent Systems
Info Mgmt ■ Cyber-Physical Systems
Economics of IS
INFO SCIENCE RESEARCH AREAS
9. The science of computation?
If so, you would think of Alan Turner’s Turing Machine
Or you may think of all the hardware and software
technologies behind the computer!!
COMPUTER SCIENCE
IBM 5100 1975
Ed Roberts’s Altair 1975
APPLE 1 1976
10. WORLD WIDE WEB
CLOUD
BIG DATA
IN-MEMORY COMPUTING
DATABASES
VIRTUALIZATION
CLUSTERED COMPUTING
INTERNET OF EVERYTHING
GRID COMPUTING
etc
WORLD TECH TRENDS
11. More Devices Than Humans
SCARY TREND #1
Anyone
Everyone
Anything
Can
Generate
Data
12. Data is the new nugget (not your money)
SCARY TREND #2
18. Birth = Computer (Computing) + Internet (Connectivity)
Anyone can publish information (server and client)
Data accessible anywhere everywhere
WWW: WORLD WIDE WEB
19. Search yields “convergence” but not necessarily “intelligence”
Based on what is out there……..
It does not quite “reason” or even “verify”!
WEB NEEDS SEARCH ENGINES
20. WHAT ABOUT DATABASES, SERVERS,
NETWORKS, VIRTUALIZATION?
MORE
STORAGE
MORE
SERVERS
GREEN
SERVERSDIVERSE
NETWORKS
VMs
22. Data Storage
Data Organization
Data Access
Data handling
Data processing
Data Filtering
Modeling
Reasoning
Knowledge Creation
Big Picture
Insights
DATA SCIENCE IS BORN !!!!!
WHAT TO DO WITH ALL THESE DATA?
Computing Internet
Web
Data
Analytics
23. BIRTH OF DATA SCIENCE:
Good it brings in multiple fields in computer and info sciences
24. Computers
Devices
Internet
IoE
Web
Data Explosion
Data Understanding
Data Reasoning
Data Science..
WHAT FUELS THE BIRTH OF DATA
SCIENCE?
25. WHEN – DATA MINING
Make Sense?
Data + Junk
YOUR INNOVATION
HERE….
27. Data Mining:
Task of discovering interesting patterns from big data..
Data Warehousing:
Data storage and memory
Data Mining Tools:
Microsoft SQL
DBMiner
Oracle Data Mining
DATA MINING & DATA WAREHOUSING
28. WHEN – KNOWLEDGE DISCOVERY
Knowledge = Understanding + Intelligence!!!
29. See big picture
Insights?
Answer to why?
WHY ANALYTICS?
34. Narrative
Can describe things down to each component
Too little data – back to square 1
Too much data – takes time to make sense
Too too too much data – blurred…
Giga bytes – 2^30 = 1000MBytes
Tera bytes – 2^40 bytes
Peta bytes – 2^50 bytes
Exa bytes – 2^60 bytes
Zetta Bytes – 2^70 Bytes
Yotta Bytes – 1000ZB – Too Big to Imagine
THE IRONY OF BIG DATA
35. When DATA is too big…
When DATA is too small…
When there is a lot of junk…
When MODEL is not good enough…
When Memory hits the limit….
When Computation hits the limit….
CHALLENGES:
SIZE VS COMPUTATION
36. I need a picture here
CHALLENGES: SPEED VS CONVERGENCE
VS SCALE VS ACCURACY
Technical
Challenges
Of
Big Data
Analytics
37. I need a picture here
CHALLENGES: WASTING CPU CYCLES
ANALYZING JUNK?
Data
Without
Meaning
Is junk…
38. Data privacy- anonymous (source and/or user unknown)
Data protection – accessibility
Data anomaly – odd, outlier, fake, alteration, etc….
CHALLENGES: DATA ANOMALY & DATA
PRIVACY
47. Big data
Cloud
Cybersecurity
Green ICT
Future Comms
Social Media
New Digital Economy
User Interface
Internet of Things
Data Science
Leads to ………………………………………………SMART NATION
IDA INFOCOMM TECH ROADMAP
48. SN: Improving Quality Of Life of Singaporeans
Enjoyable user experience Making meaningful choices
49. SMART NATION EVOLUTION…. SPATIAL
DIMENSION
Quality of life/Biz Productivity
Meeting citizens’ needs
Unlimited Possibilities
Smart Nation
(Singapore)
Use of technology to create
innovative solutions for Future Smart
Home, Office & City
Smart City/Town
Anticipatory govt that is citizen
centric & co-ordinated govt service
delivery
Smart Home/Office/Buildings
- Unified smart home experiences
- Smart work solutions for greater
business opportunities
56. Living Transformation
SMART NATION
Smart homes
- Energy mgmt
- Lighting ctl
- Temp ctl
- Noise ctl
- Mental State
Use of Sensors
Ambient Intelligence
Life style
58. Information Science should include Data Science
Data Science can enhance the lives of Singaporeans
Through Transformation in
Transport,
Living,
Healthcare
And others.
Together, we will
make this happen.
SMART NATION: CONCLUSION