Art of the Possible - Data Science Campus · 2019. 1. 11. · Predicting Viral Outbreaks Data...

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Data Science Campus | datasciencecampus.ons.gov.uk | datasciencecampus@ons.gov.uk | @datascicampus Public | 1

Art of the Possible

9th January, 2019

Ceri ReganAcademic Manager

Data Science Campus

Government Data Science Conference, London, 2017

• What is Data Science and why do

we need it?

• Example Showcase

• Discussion

• Support & Building Capability

Overview

But first…

… What words come to mind when

you hear ‘Data Science’?

• Positive

• Negative

• Not sure?

“Work that takes more programming

skills than most statisticians have and

more statistical skills than most

programmers have”

David Taylor, http://www.prooffreader.com

What is Data Science?

Domain

expertise

Machine

learning

science

The Data Science Venn Diagram, designed by Drew Conway

What is Data Science?

“Data Scientists solve complex

business problems using a

combination of domain

expertise, coding knowledge,

machine learning and statistics

skills on large and varied

datasets.”

Government Data Science Partnership

John Manzoni, Chief Executive of the UK Civil Service, Sprint 18, London, 2018

Why do we need Data

Science?

• “Getting data right is the next

phase of public service reform”

• Deliver more insight from the

data we hold

• Drive more insight through use

of new data sources

John Manzoni – Chief Executive of the UK Civil Service

Making Better Use of

Prof. David Hand

Imperial College London

The world of data is changing:

• Survey data is what people say

they do

• Modern types of data show what

people actually do

➢ Modern data are closer to

social reality

Data Observatory, , Data Science Institute, Imperial College London,

London, November 2017

Opportunities for Gov

• Automating processes which are

currently done manually

• Making operational efficiencies (eg. In

survey collection)

• Combining lots of different data

sources to:

• Improve timely production of

statistics

• Quality assure existing statistics

• Fill in gaps (e.g. in geographical

granularity)

Data Science Campus | datasciencecampus.ons.gov.uk | datasciencecampus@ons.gov.uk | @DataSciCampus

Making Better Use of Data

Challenges Ahead

• Size of modern data sets

• Quality

• Rate of Acquisition

• Ethics

Prof. David Hand, Imperial College London

Making Better Use of Data

Opportunities

• Size of modern data sets

• Quality

• Rate of Acquisition

• Ethics

• Scope of new data

acquisition methods

• The rate of acquisition

• Insight from linking and

merging datasets

Challenges Ahead

Prof. David Hand, Imperial College London

Dawn Duhaney and Gareth Llewellyn from GDS at the Government Data Science

Community of Interest Meet-up London, November 2017

Examples of

Data Science in

Government

London Transport workers manually examine over 4 million

tickets to identify most and least popular routes, March 1939Gerry Cranham/Fox Photos/Hulton Archive/Getty Images

Predicting Viral Outbreaks

£120mEstimated cost to the country in lost working

hours due to Norovirus

£20kTotal cost of the project, including publicity

campaign

2.8mCases of Norovirus per year in the UK

Fig 1. Wordcloud of Norovirus Keywords Fig 2. Norovirus Keywords in Tweets compared to reported incidents

Early Indicators of GDP

Length of time from 2008 for the UK

economy to return to pre-recession size

Fig 2. ONS National Accounts Publication Timetable

Fig 1. UK GDP Growth Rate Early

Intervention

Indicators

-6%Change in UK GDP between first quarter of

2008 and second quarter of 2009

5 years

£12bEstimated value for earlier identification of

2008 downturn

Early Indicators of GDP

Length of time from 2008 for the UK

economy to return to pre-recession size

-6%Change in UK GDP between first quarter of

2008 and second quarter of 2009

5 years

£12bEstimated value for earlier identification of

2008 downturn

VAT turnover

returns

HMRC VAT Data AIS Ship Location

Road Traffic Broadband Traffic

Reproducible Analytical Pipeline

SolutionThe Challenge

• Producing official statistics for publications is a

key problem: as it is a time consuming

meticulous process

• It is time consuming as the analysis has to

pass through multiple systems and multiple

individuals

• The systems are diverse and do not always

conform to good software engineering practice

• Use of software engineering

tools and techniques such as

version control.

• Automated generation of

tables/charts and statistical

verification

• Process from data storage to

report generation

£8.8kEstimated average annual saving per

publication

Statistical

SoftwareSpreadsheet

Processorpdf

StoreR Markdown £118m

Estimated annual efficiency savings across

government stats publications

Efficiency Savings

Web Scraping and High Frequency Indices

Comparison of the web scraped and published CPI item indices for food and non-alcoholic

beverages

CPI (Published)

Web scraped

Consumer Prices Index

• Field Interviewers collect Prices around

• Webscraped - 33 items from 3 retailers

(Tesco, Waitrose & Sainsbury’s)

• Daily collection of prices (June 2014 +)

• High frequency and timely indices

Data Scientists from across the public sector at the

Government Data Science Conference London, April 2017

• How could data science transform

your work?

• What impact could this have?

• What are the barriers?

• How could you overcome these?

Discussion

Capability Building & DS

Community

Building Data Science Capability

AwarenessBig Data & Data Science Explained; Awareness of New Coding Tools; Art of the

Possible

Working

(Undergraduate)Trainee Data Scientist

Junior Data Scientist

Level 4 Apprenticeship in Data Analytics; Level 6 Apprenticeship in Data Science;

Data Science Accelerator Programme (GDS)

Learning Academy/Campus Training Programme

Intro to R; Intro to Python; Intermediate R, Python; Machine Learning, NLP, etc

Practitioner

(Graduate)Data Scientist

Masters in Data Analytics for Government; CPD modules; Internal (ONS) Seminar

Series

Expert

(Post-Graduate)Senior Data Scientist

Alan Turing Institute intensive workshop programme; External Seminar Series

Modular programme – supports Analysts who want to upskill in

data science without becoming dedicated data scientists

• DS Apprenticeships – contact gss.careers@ons.gov.uk for more info

• Data Science Accelerator Programme –

https://www.gov.uk/government/publications/data-science-accelerator-programme

• Learning Academy/Data Science Campus training offerings – contact

learning.academy@ons.gov.uk for more info

• Online learning – DataCamp portal (www.datacamp.com/courses)

• MSc in Data Analytics for Government and CPD modules – contact

learning.academy@ons.gov.uk for more info

• Alan Turing Events - https://www.turing.ac.uk/events

• External Seminar Series – contact datacampus@ons.gov.uk

Developing a DS Community

• Slack - https://govdatascience.slack.com. Can also be set up for your

department/branch for internal discussions

• Seminars – sharing across Dept what is going on

• Coffee and Coding – regular friendly space to chat about coding

• Internal Accelerator Programme - offer internal DS projects for staff to work on

• Sharing of code via Github

• Community of Interest meets – also via Google Hangouts http://bit.ly/2gMvvvF

Developing a DS Community

• Can be used at various levels (across Gov, Dept, Directorate, team, etc)

and used to discuss DS issues and help to develop and support the

community – www.slack.com

• Cross Gov Slack channel - https://govdatascience.slack.com.

• MDataGov slack channel - https://mdatagov.slack.com/ (to be added to this

channel, please contact Anthony.Fitzroy@ons.gov.uk)

• GSS Slack channel - https://gov-stats-service.slack.com/

Support/Mentorship

from the DSC

Support Available

Data Science Campus support

• Joint projects – working collaboratively with the Campus

• Mentorship – have a dedicated Data Scientist assigned to your

project work

• Advice and guidance on building capability through training offerings

• https://datasciencecampus.ons.gov.uk/

DSC - Joint Research Projects

What will we learn?

• data sources & techniques

• building campus capability

• building ONS / Govt capability

Can the learning be applied to other problems?

Deal breakers

• Is it ethical?

• Is it possible?

• Does it have an owner?

Does it add value?Does it increase our understanding of the UK’s economy and society?

Is it a stakeholder priority?

Criteria

Data Science Campus | datasciencecampus.ons.gov.uk | datasciencecampus@ons.gov.uk | @DataSciCampusONS Data Science Campus, October 2017

Image credits: ONS stock: (Dave Johnson); GDS pp2,3,9,13,18; FSA p14,15;

Gerry Cranham / Fox Photos / Hulton Archive / Getty Images p6; drawnalism p14

ONS Data Science Campus

Email: datasciencecampus@ons.gov.uk

Web: datasciencecampus.ons.gov.uk

Twitter: @DataSciCampus

Ceri Regan

Academic Manager

ceri.regan@ons.gov.uk

Art of the Possible - Data Science Campus · 2019. 1. 11. · Predicting Viral Outbreaks Data...

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