q13/random_k2/random_1.md

Proposal for the Theme on Big Data
Analytics

Qiang Yang, HKUST

Jiannong Cao, PolyU

Qi-man Shao, CUHK

May 2015

Motivation

•

The world's technological per-capita capacity to

store information doubled every 40 months

–

As of 2012, 2.5 exabytes (2.5×1018) of data/day
Relational database management systems and
•
desktop statistics and visualization packages often
have difficulty handling big data.

–

Big Data: new driver for digital economy&society







Gartner: hundreds of billions  of GDP by 2020.
Intangible factor after labor and capital
Data Science: The fourth paradigm

2

The Power of Big Data

•

•

•

•

Big Data can bring “big values” to our life in
almost every aspects.
Technologically, Big Data is bringing about changes in our lives because it
allows diverse and heterogeneous data to be fully integrated and
analyzed to help us make decisions.
Today, with the Big Data technology, thousands of data from seemingly
unrelated areas can help support important decisions.  This is the
power of Big Data.
Areas of Applications

–

–

–

–

–

Health and Well being

Policy making and public opinions

Smart cities and more efficient society

New online educational models: MOOC and Student-Teacher modeling

Robotics and human-robot interaction

•

Much of this power hinges on Research on Analytics

3

Hong Kong needs Big Data
Research

1.

2.

to develop state-of-the-art Big
Data platform in research,
education and industrial
applications, and open it to the
Hong Kong society and the world
at large, and

to make a difference in Smart
Cities, Health and Well-being
(including supporting aging
populations), and modernizing
Finance, Education and Logistics
in Hong Kong.

4

Big Data Analytics Objectives

5

Relation to Smart Cities and IoT

•

•

•

World economic forum
ranking HK’s
infrastructure: #1
–

Maintain the lead in IT

Infrastructure

East Kowloon Project:
Energizing Hong Kong
via Smart Cities
Big Data:
–

IoT provides the

infrastructure for

collecting the data

Smart Cities as

important application

goal

–

6

Research Objectives

•

•

•

•

Big Data Analytics: data mining and machine learning
–

Large-scale machine learning, data mining and data visualization

Big Data Computing: data center support for Analytics
–

Big data collection and transformation, integration and distributed
data management and computing

Big data sampling and statistical theory, Big data security and privacy

Big Data Theory, Privacy&Security issues on Analytics
–
Big Data Science: 4th Paradigm – Analytics for Science and
Engineering
–

Big Data and Multi-disciplines (Bio, Chemistry, Engineering, Social)

7

Why Hong Kong is Ready for the Theme

•

We have the best researchers in machine learning, data mining, data
management, sensor networks, statistics, and multidisciplinary
research such as bioinformatics

–

–

–

China National 973 Projects on Big Data

IEEE Transactions on Big Data: EiC

ACM KDD Conferences: PC and Conference Chairs

Winner of Big Data related international competitions

–
New industries based on lots of data

–

Financial industry, logistics industry, education sector, government
services, etc.

We have many potential collaborators and partners
–

Huawei, Tencent, Baidu, Alibaba, Google, Microsoft, etc.

•

•

8

Big Data Analytics Workflow

 9

Data
Extraction

Data
Integration

•  HKUST
CUHK
•
Baptist
•
HSBC
•
Astri
•

•  HKUST
HKU
•
City U
•
Alibaba
•
Astri
•

Applications

•  Biology and Genetics
•
•
•
•
•
•
•
•

Chemistry
Physics
Government Policies
Social Sciences
General Health
Logistics
Finance
Business

Data Mining &
Visualization

•  HKUST
CUHK
•
City U
•
Huawei
•
Tencent
•

Big Data
Computing &Data
Management

•  CUHK
•
•
•
•
•

HKUST
HKU
PolyU
City U
Baptist U

Multi-disciplinary Big-data Analytics

•

Objectives:
•

Interdisciplinary,
research
technological big data analytics

heterogeneous

multi-university,

on

multi-team
and

scientific

10

Why Big Data needs Team Work?

•

Big data analytics is necessarily a joint effort by
researchers from academic institutions,
government and society and industry.
–

The government and industry are sources of Big
Data, and providers of problems and challenges,
The academic researchers are solution

providers.

When it comes to package the solutions from
university labs to transfer to the real world,
universities and industry must work together to
build scalable and robust solutions.

–

–

11

Expected Outcomes

•

•

•

•

New methodologies and solutions for Big Data
research
New applications that impact the society and
industry in Hong Kong and beyond, and
New digital economies created based on big
data
New educational programs for students;
cultivating leaders for the Big Data society and
industry.

12

Breakthroughs Expected

•

•

•

•

New algorithms, methodologies, systems and
applications in Big Data
New knowledge from Big data applications in
Science, Engineering, and Societal Problems
New insights into Big data practices in real
world
New ways to protect security and privacy of big

data relevant to individuals and organizations

13

Call for Proposals in Big Data Analytics

•

•

Foundations in Big Data Analytics Research:
–

developing and studying fundamental theories,
algorithms, techniques, methodologies,
technologies to address the effectiveness and
efficiency issues to enable the applicability of Big
Data problems;

Innovative Applications in Big Data Analytics:
developing techniques, methodologies and
–
technologies of key importance to a Big Data
problem that requires the seamless cooperation
of domain scientists with big data researchers.

14

Benefit for the Hong Kong Society

•

•

•

•

•

Can  Hong  Kong  transform  into  a  more  data-
driven  society  and  maintain
leadership
globally?

its

How  can  companies  in  Hong  Kong  become
more competitive with Big Data technology?

Can Data Science in Hong Kong’s research
fields benefit from strong foundations on big data?

Can the government become more efficient with
big data driven methodologies in decision
making?

Can education, finance, logistics and health
benefit from the ever increasing data?

15