BIG DATA …

AND CULTURAL LANDSCAPE UAE CONTEXT

PRESENTED IN THE MCYCD WORKSHOP – UAE INNOVATION WEEK22 – 28 NOVEMBER 2015 – # UAE INNOVATES-----------------------------------------------------------------------------------------------------

Sufyan Al BarghouthiDirector of Org. Development – FCSA - UAE

Member of Global Working Group on BIG DATA for Official Statistics – UN

26 NOVEMBER 2015

My Route Map

• What's BIG DATA

• BIG DATA and Culture sector

• BIG DATA and Cultural Landscape

• Some Cases .. Food 4 Thought ..!

• Some Main Conclusions

• Open Discussions

Information every where…

We are living in an ‘online information society’ Internet of Things

“Remember … MORE numbers doesn’t mean more INORMATION!!!!.”

Growth of Global Internet usage by 2015

What does that mean?Big Change … Big Shift ..!!

• Big data

New Production

Factor

• Claude ComputingNew Public

Services

• Internet

New Infrastructure

network

Around 6 Millions Tweets

per day in the

Arab countries

11% fro UAE

90000

2011

410000

2014

???

2021

What's Big data definition..?

Many definitions, but most of them are summarized as follow:

Big Data is a term applied to data sets whose size is beyond the ability of commonly used software tools to capture, manage, and process the data within a tolerable elapsed time. Big Data sizes are a constantly moving target currently ranging from a few dozen terabytes to many petabytes of data in a single data set.

What they say about Big data ..?

New Oil / wealth which increase by use!!

Main Sources for Big data

• Smart meters and sensors:

Traffic cameras, GPS devices, price scanners, power

monitors, smart watches, smart phones, etc.

• Social Interactions:

Talks and publications on social networks like Twitter,

Facebook, FourSquare, etc.

• Business Transactions:

Movements of credit cards, electronic cash registers, cell

phone records, etc.

• Electronic files:

Documents which are available in electronic formats such as

PDF files, websites, videos, audio, digital media broadcasting

• Broadcast media

Digital video and audio produced on real time

It comes as Structured and Unstructured forms

BD characterized by Vs term:

we can add Value added

Data Confidentiality / Security in Cultural

Landscape

• Personal information is individual & precious to

each one of us – it’s vital that we treat it

properly.

• There is a long-standing and healthy debate

about the balance between the right to privacy

and the necessity to hold and share data.

Challenges of B D in Culture Sector

(International Exp.)

• There is concerns about the accessibility, quality, and

comparability of cultural data, different infrastructure;

• Pre judgments and inherited norms: many cultural

practitioners assume that data—and especially

quantitative data—are of limited value when it comes

to making programmatic and artistic decisions;

• Different culture sector stories: lack of coordination

and standardization in existing cultural data collection

efforts.

• In addition to organization level challenges .. Learning

institutions are most likely better in using BD.

B D Driving Future Cultural

Landscape

Data-driven organizations

perform better on measures

of financial and operational

results than those who do

not

Data facilitate efficient

processes, saving time and

money

Data lead to innovation

Data will ultimately lead to

funding.

Data-driven decision making

require organizational cultural

change

Strong Leadership is necessary

to set clear goals and to ask the

right questions

Skillful and talented Data/IT

Specialists must be on staff.

Lack of statistical and technical

skills in the labor force

BD and Culture sector in the UAE Context

Interactive Cycle of Engagement and Empowerment

Public Policies;

YES

Government

Society

Environment

Individuals

Sustainability

Engage

ment

Empow

erment

Accountability

Macro View: BD Impacts Domain

Utilizing BD

opportunities

Economic growth of

information industry

Social and economic benefits to

people

Improving public service delivery

Citizen awareness

and developme

nts

BD for Development in Culture Sector

Big Data for Development

is about turning imperfect, complex, often

unstructured data

into actionable information

By the time hard evidence finds its way to the

front pages of newspapers and the desks of

decision makers, it is often too late or

extremely expensive to respond…!!!

Can we link B D to the Development Agenda Post 2015?

Lets have a look on the SDGs

Remember

Monitoring means:

Measuring and tracking

B D & Sustainable Development Agenda Post 2015

B D & Sustainable Development Agenda Post 2015

B D & Sustainable Development Agenda Post 2015

B D & Sustainable Development Agenda Post 2015

Practical view: Where we are standing?

Wisdom

intelligence

Understanding

Knowledge

Information

Data / statistics

Noise / Numbers

Where we are standing? Information Journey …

Seeing what you asked for

Versus

asking yourself what you see;

1st defines the info you want; the 2nd the info defines the model you need.

Org. Dev.!?

Development

Modernization

Standard-

izations

Strategy Dev.

Operation / KPIs

Corporate performance

& Excellence

Innovative Solutions

Foresights / Shaping the Future

So …

Who is influential ?

People influence the culture or culture influence the people?

How Big Data can help?

What sort of project we can think about with BD?

Role of Culture..

• What is the role of ‘the arts’ in people's lives relative to their other activities and interests

Audience Habits

• How do UAE nationals / Non-nationals satisfy their needs for both creative expression and artistic enjoyment

Culture and

UAE Mix

• What is the culture mix fits demographic, social, cultural, technological shifts and the UAE mix?

Cultural Shift Drivers

• What macro trends in consumer behaviors and public tastes are driving demand for new arts and future culture

What sort of project we can think about with BD?

Cultural turning Points

• What line of change on culture audience behavior and consumption is taking place? Is there turning points

Culture values

• What links between arts on the ground and people values? Who drive? Where we are going from now?

Demand for Culture

• Why people join activities they may previously disliked or wasn’t aware

Designing Demand

• What role can our institution play in building demand for the arts and culture?

What sort of project we can think about with BD?

Time Use and Youth needs

• What motivates youth in our society to invest their time and their physical presence in the arts as participants rather than merely audiences , how they make their choices?

Impacts

• What is the rewards / impacts of culture season?

How can we work with Big Data?

How we can work with Big Data?

Step 1. Source Data: Speed, Type and Amount.

What kind and how much data are we working with?

• Assessing how hard it is to access

• Determining how it needs to be transformed

• Identifying the technologies to facilitate the process

Step 2. Data Preparation: Cleansing and Verification.

What do the data need for operational requirements?

• Define methods required for data prep such as:

• Standardization, verification, filtering, etc…

Step 3. Data Transformation.

What is required to leverage the data?

• Unstructured data may be broken down and presented in a structured

format

• Data sources can be aggregated to determine not-so-obvious

relationships between data types

How we work with Big Data?

Step 4. Business Intelligence/Decision Support.

Tools, methods, techniques to leverage data

• Data Mining

• Visualization/Simulations

• Keyword Searches & Syntax Analysis

Step 5. Analysts/Visualization.

How should the data be used?

• Present data visually so it can be explored

• Use data as is to support/enhance/improve existing organizational processes / policies

• Monitoring performance on strategy outcomes

• Informed decision making (improved inputs).

Moving ahead …Organized Big Data Project …

Assess StrategyDefine

BIG DATA

ProjectInputs Plan

Execute OutcomesReview

What we need to Run Big Data Project in

Culture Sector?Sufficient and necessary conditions

Adequate Staffing

IT and supporting Infrastructure

Adequate budgets

Road map

A Data-Driven organizational

culture

Openness to organizational

change

Leadership support

Cooperation with partners

Project Planning

Data Analysts/IT Specialists,

etc…

Data storage, Software,

Hardware, Connectivity, etc…

Technological investment

Data Prioritization

Evaluation process

Food 4 Thought

Some Cases from others experiences

Quick wins .. Start simple ..

Social media as example ..!!

What Social media tell us?

Multidimensional Topic

Culture Sector Domains

AFTER SCHOOL GAB .. Food 4 THOUGHT

Young people face a number of dangers during the hours

after school. There are approximately 20 to 25 hours per

week that children are out of school while most parents are

at work, creating an “after-school gap.”

Self-care and boredom can increase the likelihood that a

young person will experiment with drugs and alcohol by as

much as 50 percent.

Youth tend to develop patterns of alcohol, tobacco, and

other drug use - or nonuse – from ages 12 to 15.

On school days, 3-6 PM are the peak hours for teens to

commit crimes, be in or cause car crashes, be victims of

crime, and smoke, and other social diseases.

Teens who do not participate in afterschool programs are

nearly three times more likely to skip classes at school than

teens who do participate.

Country Practices: Success stories

The case of Museums - UK:

• Big Data can be a smart project to encourage discovery

and learning,

• Online tourism topics can generate from multiple sources

new stories about culture;

• it's also an opportunity for both virtual and physical

audiences to tell cultural stories on their own terms

• Creating evidence-based cultural stories

• This Interactive process will create new ways of working,

as well as new forms of storytelling that allow cultural

institutions to develop new models of participation with

audiences.

Example: sharing some collections on line and collect and

analyses responses!

Case Example: Consumer confidence (Netherland)

Consumer confidence: Twitter Data

Youth at Risk Policy has been insufficient in fighting serious/life-threatening youth problems

Analyzing social data – buzz patterns related to suicide among youth – allows formulation of policies to effectively prevent suicide by better understanding the circumstances and psychological states of the youth

(Source) National Information Society Agency Pilot Project (Jul-Sept, 2012)

3 / 15

e.g.) Suicide Context Pool e.g) Online spread of harmful content e.g.) Influence by Major Players Online

Case Example: Supporting Youth At Risk Policy (S K)

Suicide risk factor

Harmful Contents

Wikipedia as a big data source (E C case)

Insights on world heritage from analysis of Wikipedia use

Chart shows people's Popularity of WHS over time

(What happened in March 2013?!)

How the Society feels ? (N L case)

4

7

A number of basic emotions

Happy

Sad

Angry

Scared

Tender

Excited

How the Society feels ? (N L case)

Youth Empowerment Strategy (YES) in UAE

and Innovation Enablers

YES

Entrepreneurships

starters

Patent Rights Auth.

Investment Capital

Innovation

empowerment

Making it Works ,,,

• Leader

• Training

• Policy notes S.C Index

• analytics

• Private Sector

• Academia

• Social media

• Tell. Com.

Data

InputsBI Tool

TeamResults

Developing Social Composite Index…

This project can help the Ministry to Track YES

in Different Fields …

MCYCD

B.D Project

Ministry policies 4

development

Impact Tracking

Intervention measures

Promoting Innovation

Partnerships

Society engagement

To conclude …

Something we can start on the Fast Track …

PARTNERSHIPS … Core stone

• Expand and invest in the talent pool by creating a formal track for IT/Data

managers with training and certification in BIG DATA Analytics and data

scientist technologies.

• Establish and broaden coalitions between culture academic and

associations to develop professional standards and shared best practices

for the field.

• Expand “college-to-government service” internship programs focused on

technical aspects of BIG DATA for Cultural agenda.

• Align incentives to promote data sharing for projects in culture activities.

• Provide further guidance with data sources and stakeholders on privacy

and data protection practices.

• Develop intellectual property policies to promote innovation.

Things 2 do on the Fast Track

• BD Vision supported by leadership: leadership that

can authentically build bridges across the different

spheres and interests that make up the cultural

sector in UAE.

• Orchestrated and engagement programs with all

partners in the culture sector, more ideas more

success, (Partnerships).

• Shift the interest of BD from data’s value as an

accountability tool to data’s value as a decision-

making tool, and until we are using data to inform

decision-making about programming, we can’t truly

be said to be engaging in data-informed decision-

making.

Things 2 do on the Fast Track

• To develop an agenda for future research and data

collection, with clear objectives and a plan of

action to utilize BD for culture sector.

• Develop and encourage training and professional

development in data-related skills for staff

members; open eye on BD analytics.

• Open the gate for innovation through improving the

cultural data infrastructure and partnerships.

• Leading the shift: Managing the change; transform personal and organisational ways of dealing with culture issues, improve training, and consider credentials.

• Clarify and streamline legal framework for BD usage: develop policies for using BD for culture needs, develop a fast-track procedure where there is a strong case for quick wins.

• Short time to market: Ensure effective enforcement; implement fine provisions quickly; provide new powers; ensure adequate resources; and revise structure where needed.

Generic and policy Recommendations

Generic and policy Recommendations

• Develop mechanisms for safe and secure research and

statistical analysis: develop ‘safe havens’ as

environment for Culture-Based Research for the

Ministry to serve also national needs in this sector.

• Safeguard and protect publicly available (online)

information: coordination with relevant partners in the

government.

• Develop a project: BID Data for Culture Sector, with

complete strategy and action plan and well defined

deliverables according to time schedule.

Some use full references?

• New Data Directions for the Cultural Landscape: Toward a Better-

Informed, Stronger Sector

• Alan Brown, Principal, WolfBrown

• John W. Jacobsen, CEO, White Oak Institute and President, White Oak

Associates, Inc.

• Roland J. Kushner, Associate Professor of Business, Muhlenberg

College

• Lawrence T. McGill, Vice President for Research, The Foundation

Center

• UNSD big data for official statistics, UAE 2015.