UCL DataLab Launch - BigData to BigWisdom

Post on 10-May-2015

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A keynote about BigData in Securoty. Presetned at the launch of the UCL DataLab in 2013. [this has animation, so probably best to download the file]

Transcript of UCL DataLab Launch - BigData to BigWisdom

BigData to BigWisdom

Daniel Hulme - d.hulme@cs.ucl.ac.uk

• Masters (Msci) in Computer Science with Machine Learning @ UCL• Doctorate (EngD) in Computational Complexity @ UCL• Research Scientist in Optimisation & Innovation @ UCL• Co-lecturer of New Venture Analytics @ UCL• Founder & CEO of Satalia (NPComplete Ltd) @ UCL• Recipient of a Kauffman Global Scholarship• Visiting Fellow in BigData @ The Big Innovation Centre

BIG WISDOM

BIG UNDERSTANDING

BIG KNOWLEDGE

BIG INFORMATION

BIG DATA

DIKUW Pyramid

• Optimisation Algorithms• Decision Making• Decision Science

• Machine Learning• Analytics &

Visualisation• Data Science

• Aggregation & Visibility• Access & Storage• Security & Resilience

ACTION

INSIGHT

DATA

Understanding BigData

What is BigData?

Giving Meaning to Data

Structured

Databases

Siloed

Migrating from

Storage

Corruption

Security

Mining

Unstructured

Internet

Trawling

Mining

Language

Privacy

Cleaning

Authenticity

Semi-structured

Semantic Web

Tagging

Querying

Provenance

Mining

Storage

Migrating to

Why?

Machine Learning

Mature subject

Complex Correlations

Open-source Tools

Mining

Prediction

Hard

Semantic Inference

Reasoning

New research area

Semantic Web

Emerging Tools

Pretty Pictures & Data Scientists

The Use of Knowledge

Wisdom - Buy John a dog bowl for his birthday and he'll be very happy

Understanding - John's birthday is on April 27th. If John Smith likes Dogs then he probably has one

Knowledge - 1979-04-27 is John Smith's date of birth, and John Smith likes Dogs

Information - 1979-04-27 is a Date, John Smith is a Person, Dog is an Animal (data in context)

Data - "19790427", "John Smith", "Dog" (raw groups of symbols)

BigQuestions

What problem are you trying to solve?

Objectives, Variables and Constraints

POINTS ROUTES MEGA OPS /S

10 3,628,800 4 seconds

11 39,916,800 1 minute

13 6,227,020,800 2 hours

14 87,178,291,200 1 day

16 20,922,789,888,000 1 year

20 2,432,902,008,176,640,000 77,000 years

22 1,124,000,727,777,610,000,000 36 millennia

24 620,448,401,733,239,000,000,000 20 billion years

Odd or Even: O(1)Ordered Search: O(log n)Sorting Items: O(n2)Travelling Salesman: O(n!)

Knowledge, Power, Responsibility

Change the World

• Challenges– How anonymous is anonymised data?– What data should be open and how can it be used/abused?– What should be BigData standards, protocols and ontologies?

• Opportunities– What new innovations can emerge from BigData?– What about Personalised Medicine, Health, Education?

• Pioneers– JDI DataLab at UCL is uniquely positioned to address these

challenges and explore emerging opportunities– Facilitate exciting interdisciplinary collaborations across JDI, CS,

CASA, BEAMS, Bartlett, Enterprise, and beyond

Questions & Discussions

BIG WISDOM

BIG UNDERSTANDING

BIG KNOWLEDGE

BIG INFORMATION

BIG DATA