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WHAT IS 
DATA SCIENCE 
AND HOW CAN IT HELP GLOBAL HEALTH? 
PART 1 IN A SERIES 
DEVELOPED BY JOHN SPENCER 
September 2014 
h t t p : / / d a t a re v o l u t i o n . u s
DATA SCIENCE LETS USERS 
IDENTIFY AND UNDERSTAND 
PATTERNS IN DATA. 
IT BALANCES TRADITIONAL 
HYPOTHESIS TESTING AND 
PATTERN ANALYSIS. 
DATA SCIENCE ALSO 
EMPHASIZES MAKING THE 
RESULTS OF THE ANALY S I S 
EASILY UNDERSTOOD. 
F l i c k r i m a g e b y l e e c u l l i v a n 
h t t p s : / / f l i c . k r / p / 4 W 5 X y m
IT CAN BE A GREAT TOOL FOR 
MANAGING AND UNDERSTANDING 
COMPLEX DATA .
DATA SCIENCE 
BRINGS TOGETHER 
SKILLS AND METHODS 
FROM DIFFERENT 
TECHNICAL AND 
SUBSTANTIVE AREAS. 
MATH AND 
STATISTICS 
KNOWLEDGE 
HACKING 
SKILLS 
MACHINE 
LEARNING 
DATA 
SCIENCE 
DANGER ZONE TRADITIONAL 
RESEARCH 
SUBSTANTIVE 
KNOWLEDGE 
FROM DREW CONWAY: b i t . l y / 1 l y G 9 U A
IN A WORLD THAT LOOKS LIKE THIS,
DATA SCIENCE CAN BRING SOME ORDER. 
F l i c k r i m a g e D a v i d S i n g l e t o n h t t p s : / / f l i c . k r / p / 4 j h r z M
SOME EXAMPLES…
NETFLIX 
PRIZE 
Netflix uses a 
recommendation engine to 
suggest movies based on 
your likes and dislikes. 
The machine learning 
algorithms that make this 
possible rely on data science 
principles.
MALARIA ATLAS 
PROJECT 
The researchers at the 
Malaria Atlas Project create 
models of malaria risk using 
Gaussian processes. 
Malaria data as well as data 
on rainfall, temperature or 
land cover are inputs to the 
model. The model can help 
fill in the gap in areas where 
reliable data isn’t available. 
www.map.ox.ac.uk
ISN’T THAT JUST DATA ANALYSIS? 
WHAT MAKES IT DATA SCIENCE? 
F l i c k r i m a g e : D e m i - B rooke h t t p s : / / f l i c . k r / p / 4 T n d 2 s
TRADITIONAL DATA ANALYSIS 
? HY POTHE S I S 
QUESTION UNIVERSE OF DATA 
ANSWER 
! 
With traditional data analysis, a hypothesis guides data analysis. 
A few data sets are analyzed to prove or disprove the hypothesis.
DATA SCIENCE 
? 
HYPOTHESIS 
QUESTION 
UNIVERSE OF DATA ! 
ANSWER 
With data science, the data itself can guide analysis. Data 
scientists employ a mix of hypothesis testing and pattern 
recognition with as many data sets as are relevant.
Data science relies on a mix of deductive and inductive 
reasoning to create actionable knowledge. 
Traditional analysis provides understanding of 
phenomenon only where data exists. Data science can 
provide understanding where data doesn’t exist. 
F l i c k r i m a g e b y f a u n g g h t t p s : / / f l i c . k r / p / 5 n 2 e F r
WHY IS THIS IMPORTANT 
IN GLOBAL HEALTH?
Around the world, there is more data collected associated 
with health programs than ever before.
Paradoxically, despite the fact there is more data than 
before, there are still data gaps. 
It is not possible to collect data about every aspect of 
health, there will always be data that can’t be collected. 
Data science can help mitigate the effect of data gaps.
In fact, there is more data about the world in general. 
This data can provide valuable information about the 
context in which the programs exist. 
F l i c k r i m a g e : P o s s i b l e h t t p s : / / f lic.kr/p/eyGbM9
In short, there’s more data about the world than ever 
before. That includes health related data. 
There are still data gaps, things that we don’t know. 
Using the data we do have, data science can identify 
previously unrecognized patterns and can further our 
understanding about things for which data doesn’t exist.
Part 1 of a series 
Produced by John Spencer 
@Jspencerunc 
All presentations available via 
http://datarevolution.us 
Produced under a Creative Commons License

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What is data science

  • 1. WHAT IS DATA SCIENCE AND HOW CAN IT HELP GLOBAL HEALTH? PART 1 IN A SERIES DEVELOPED BY JOHN SPENCER September 2014 h t t p : / / d a t a re v o l u t i o n . u s
  • 2. DATA SCIENCE LETS USERS IDENTIFY AND UNDERSTAND PATTERNS IN DATA. IT BALANCES TRADITIONAL HYPOTHESIS TESTING AND PATTERN ANALYSIS. DATA SCIENCE ALSO EMPHASIZES MAKING THE RESULTS OF THE ANALY S I S EASILY UNDERSTOOD. F l i c k r i m a g e b y l e e c u l l i v a n h t t p s : / / f l i c . k r / p / 4 W 5 X y m
  • 3. IT CAN BE A GREAT TOOL FOR MANAGING AND UNDERSTANDING COMPLEX DATA .
  • 4. DATA SCIENCE BRINGS TOGETHER SKILLS AND METHODS FROM DIFFERENT TECHNICAL AND SUBSTANTIVE AREAS. MATH AND STATISTICS KNOWLEDGE HACKING SKILLS MACHINE LEARNING DATA SCIENCE DANGER ZONE TRADITIONAL RESEARCH SUBSTANTIVE KNOWLEDGE FROM DREW CONWAY: b i t . l y / 1 l y G 9 U A
  • 5. IN A WORLD THAT LOOKS LIKE THIS,
  • 6. DATA SCIENCE CAN BRING SOME ORDER. F l i c k r i m a g e D a v i d S i n g l e t o n h t t p s : / / f l i c . k r / p / 4 j h r z M
  • 8. NETFLIX PRIZE Netflix uses a recommendation engine to suggest movies based on your likes and dislikes. The machine learning algorithms that make this possible rely on data science principles.
  • 9. MALARIA ATLAS PROJECT The researchers at the Malaria Atlas Project create models of malaria risk using Gaussian processes. Malaria data as well as data on rainfall, temperature or land cover are inputs to the model. The model can help fill in the gap in areas where reliable data isn’t available. www.map.ox.ac.uk
  • 10. ISN’T THAT JUST DATA ANALYSIS? WHAT MAKES IT DATA SCIENCE? F l i c k r i m a g e : D e m i - B rooke h t t p s : / / f l i c . k r / p / 4 T n d 2 s
  • 11. TRADITIONAL DATA ANALYSIS ? HY POTHE S I S QUESTION UNIVERSE OF DATA ANSWER ! With traditional data analysis, a hypothesis guides data analysis. A few data sets are analyzed to prove or disprove the hypothesis.
  • 12. DATA SCIENCE ? HYPOTHESIS QUESTION UNIVERSE OF DATA ! ANSWER With data science, the data itself can guide analysis. Data scientists employ a mix of hypothesis testing and pattern recognition with as many data sets as are relevant.
  • 13. Data science relies on a mix of deductive and inductive reasoning to create actionable knowledge. Traditional analysis provides understanding of phenomenon only where data exists. Data science can provide understanding where data doesn’t exist. F l i c k r i m a g e b y f a u n g g h t t p s : / / f l i c . k r / p / 5 n 2 e F r
  • 14. WHY IS THIS IMPORTANT IN GLOBAL HEALTH?
  • 15. Around the world, there is more data collected associated with health programs than ever before.
  • 16. Paradoxically, despite the fact there is more data than before, there are still data gaps. It is not possible to collect data about every aspect of health, there will always be data that can’t be collected. Data science can help mitigate the effect of data gaps.
  • 17. In fact, there is more data about the world in general. This data can provide valuable information about the context in which the programs exist. F l i c k r i m a g e : P o s s i b l e h t t p s : / / f lic.kr/p/eyGbM9
  • 18. In short, there’s more data about the world than ever before. That includes health related data. There are still data gaps, things that we don’t know. Using the data we do have, data science can identify previously unrecognized patterns and can further our understanding about things for which data doesn’t exist.
  • 19. Part 1 of a series Produced by John Spencer @Jspencerunc All presentations available via http://datarevolution.us Produced under a Creative Commons License