This document discusses how data science can be used for social good. It provides examples of using data science to predict things like diabetes, detect carcinogens during cancer treatment trials, predict soybean yields to help farmers, and predict optimal times for wind energy to help wind turbines. Additional examples discussed include mapping health services availability across regions to identify gaps, and using predictive maintenance to determine when sensors may wear out based on location and past issues. The document emphasizes that data science can help improve areas of social good like public health, transportation, the environment, and more.

1. Data Science for
SOCIAL GOOD
by Albert Gavino, MBA
Data Scientist, Climate Reality Leader
DSCON2016

2. What is Social Good?
Clean air
Clean water
Affordable Electricity
Public Health Services
Efficient Public Transportation
Low Crime Rates
Sinkhole in Fukuoka, Japan
11/15/2016

3. Regular things affect us
Smog, Taken 6:20 am,
42nd floor Rufino Tower
November 21, 2016
MRT station Makati, Philippines

4. Some DS apps for Social Good
Predicting Diabetes Type I and Type II through
image processing.
Detecting carcinogenic mg in clinical trials for
cancer treatment in mice. (CAX)
Predicting soybean yield with input such as soil
type, rain, season for farmers in North America
(Syngenta Crop Challenge)
Predicting what time of the day the wind
energy is at an optimal value - helping wind
turbines reach their maximum potential to
harness energy. (North America)

5. Use case: Mapping Health Services
Mapping Health
services available to a
certain region such as
Cavite and comparing
it to more NCR areas
such as Manila and
Makati.

6. Talas use case: weather
Preventive maintenance to detect whether a sensor
Will wear out due to factors such as location,
frequency of Breakdowns, recency of breakdown
and monetary value of equipment

7. Thank you to our Partners for Social
Good
“In spite of everything, I still believe that people are really
good at heart” -Anne Frank