From Info Science to Data Science & Smart Nation
3 likes1,288 views
The keynote speech discusses the evolution from information science to data science and how this progression enables Singapore's vision of becoming a smart nation. It outlines how exponential growth in data and new technologies led to the birth of data science. Data science faces challenges regarding data size, computation limits, and ensuring privacy. The speech envisions how data analytics can help address Singapore's challenges like aging population and urban density through transformations in healthcare, transport, living and business enabled by a national smart nation platform.
From Info Science to Data Science & Smart Nation
- 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
- 4. Course Structure NUS INFO SCIENCE DEGREE
- 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
- 13. SCARY TREND #3
- 14. SCARY TREND #4
- 15. SCARY TREND #5
- 17. DATA EXPLOSION GRAPH From 2010 onwards
- 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
- 21. DATA CENTERS ARE BORN
- 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….
- 26. DATA MINING
- 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?
- 30. WHEN ANALYTICS? U SELL IN MASSES, U NEED ANALYTICS Customer Feedback Size & Wants
- 31. 101001000 BYTE PACKET MESSAGE INFO ELEMENT Text Audio Video Image Etc. ANALYTICS: DATA IS A REPRESENTATION
- 32. Text Audio Video Image Metadata TYPES OF DATA & THEIR CHALLENGES Social Data Sensor Data
- 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
- 39. DATA ANALTYTICS PLATFORM Spark: 40x faster than Hadoop; In-memory data storage Shark: Ported Hive in Spark..
- 41. Learn from data, make predictions on data MACHINE LEARNING
- 43. Plenty of room for research and development…. ADVANCED ANALYTICS
- 44. “CONWAY” DEFINITION OF WHAT IS A DATA SCIENTIST
- 45. DEMAND FOR DATA SCIENTIST SURGING
- 46. SHORTAGE OF TALENTS – IDA CULTIVATING THEM
- 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
- 50. SMART NATION: KEY BUILDING BLOCKS
- 51. SMART NATION: DATA ANALYTICS PLATFORM COMPUTE t s p c
- 52. Data Handling, Knowledge Building, Intelligence Creation SMART NATION:
- 53. AGEING POPULATION Elderly Living Health Care URBAN DENSITY Smart Transport Smart Living SMART NATION ADDRESSES THESE CHALLENGES..
- 54. Healthcare Transformation WHAT’S NEXT • Personalized Medicine • Preventive Illness • Predictive Illness • Implantables • Wearables • Smart Health
- 55. Transport Transformation WHAT’S NEXT • Autonomous Self Driving Vehicles • Multi-modal Transport
- 56. Living Transformation SMART NATION Smart homes - Energy mgmt - Lighting ctl - Temp ctl - Noise ctl - Mental State Use of Sensors Ambient Intelligence Life style
- 57. Business Transformation (BI) WHAT’S NEXT
- 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