2016年寒假，一群學生在資料科學營隊中認識、發想如何使用open data關注高齡社會問題、利用WHO的友善老人手冊結合成評估工具、學習用R語言和資料科學思維來完成專案，經過幾個月的努力，投稿到今年位於史丹佛大學舉辦的國際R語言會議，找尋補助，申請開放文化基金會的國際交流計畫補助 ！ 我們將在分享會中，分享這段過程的點點滴滴！ 歡迎對學習資料科學、R語言、投稿開源會議、如何找到出國贊助的朋友，來參加我們的分享會！

1. useR!2016
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OCF

2. /
R/Bioconductor
Linux/shell script
SQL
Python
NGS/RNAseq data

3. useR!2016 conference
• 6/27 - 30,
• R (2004 - 2016)
• UseR!2017 7/4 - 7
• DSC, R

4. 1/19 - 22
DSP
useR!2016
3/25
Abstract
4/6 useR!2016
6/27-30
6/18
poster
1
2
Oral Presentation
Poster Presentation
.pdf

5. github
DSP

6. Poster
Using R with Taiwan Government Open Data to Create a
Tool For Monitoring the City's Age-Friendly Status
As the aged population rapidly growths, making a city age-friendly is
becoming a priority goal of the government’s policy. Information such
as indexes reflecting the city’s age-friendliness would be needed for
better policy-making and should also be readily accessible to the
citizens. And the R language provides a great flexibility in dealing with
the diversity of the file formats from government. Besides, the data
visualization and web application supported by R can make the
analysis result more understandable and interactive.
According to Global Age-friendly Cities: A Guide (WHO, 2005), there
are eight aspects for a comfort of elder living (outdoor spaces,
transportation, housing, social participation, social respect, civic
participation, communication, health and community support). And
we use the Taiwan government open data to integrate indexes with
normalization and to visualize the indexes geographically. In the end,
we create a Shiny application to let the result easily be approached.
The result may show how to utilize the government data and provide a
great application turning WHO guideline into a monitor tool helping
the government practice in age-friendly policy.
Abstract
Taiwan government open data
Growing aged population in Taiwan
Age-friendly City
Ting Wei Lin1, Wen Tsai Hsu2, Zheng Wan Lin3, Yu Wen Kao4, Po Shang Yang5, Chi Tse Teng6
1.System Genome and Biology Program, National Taiwan University, Taiwan 2.Department of Financial and Computational Mathematics,Providence University, Taiwan 3.Department of Information
Management, Providence university, Taiwan 4.Department of Statistics and Informatics Science, Providence University, Taiwan 5.Department of Computer Science and
Engineering, National Chung-Hsing University, Taiwan 6.Department of Computer Science and Information Engineering, Providence university, Taiwan
The international development trend on using the public data is to let
the government information transparent and easily accessible, which
can promote the citizen participation. In Taiwan, the government have
launched the open data policy in 2012 to participate in the trends to
pursue a better government transparency. On the other hand , the
calling for the open government data from the local open community
had also accelerated the Taiwan government’s path to openness.
With the cooperation from the government and numerous open data
communities, Taiwan has been ranked No.1 in the 2015 Open Data
Index by the Open Knowledge Foundation. Now, the open taiwan
government (data.gov.tw) have stored over 17281 data sets from more
than 66 central government and 26 local government departments.
The data sets had providing the information about the government
spending, national statistics, procurement tenders, national map,
legislation, pollutant emissions, election results, company register,
government budget, water quality, weather information, which
provide enormous data and resource to utilize for citizen
participation. Overall, the ultimate goal to turn the government into
more transparency and open is to promote the citizen participation
and to continue supervisor the government’s practice.
By exploring the data stored in the Taiwan government open data, we can find
that the growing aging population is a emerging serious public issue.
According to the national statistic data from the open Taiwan government, the
average population ratio over 65 years in Taiwan is increased from 11% in 2010
to 13% in 2015, which mean the aged society. The range of the population ratio
over 65 years old range from 10% to 17% in different Taiwan districts. The
National Development Council report had showed that in the 2060, the Taiwan
may be the 2nd place high aged population. Making policy to response to the
population change will be a priority and also a great challenge.
The problem of rapidly aging population is not only Taiwan’s public problem
but the global health public issue. The WHO have done a great effort on
dealing with this global aging problem and establish a serial campaigns on
promoting the concept of buiding a age-friendly city. According to the WHO
age-friendly city report, “ An age-friendly city is an inclusive and accessible
community environment that opportunities for health, participation and
security, in order that quality of life and dignity are ensured as people age.”
There are eight aspects for a comfort of elder living (outdoor spaces,
transportation, housing, social participation, social respect, civic
participation, communication, health and community support ) and the
indicators fit in above aspects can be used to assess a age-friendly status
of city. With those concepts, we can take the advantage of the rich data
from Open Taiwan Government data to create a index to reflect the age-
friendly status of the different districts in Taiwan.
Compositions of the age-friendly index
Equity measures
✪ the income difference between families
✪ the difference between the families structure
Age-friendly environment outcomes
accessible phyiscal environment
✪ neighbourhood walkability
✪ accessiblity of public spaces and buidlings
✪ accessibility of public transportation vehicles
✪ accessibility of public transportation stops
✪ affordability of housing
Inclusive Social Environment
✪ positive social attitude towrad old people
✪ engagement in voluteer activity
✪ engagement in paid employment
✪ engagement in socio-culture activity
✪ participation in local decision-making
✪ availability of informaiton
✪ availability of health and social sevice
✪ economic security
Impact on wellbeing
✪ quality of life
Workflow
Taiwan government open data
Data Gathering
readr dplyr
1.data input
2.data normalization
xij-min(xj)/max(xj)-min(xj)
3.data transformation
1- xij for negative correlation
indicators
maptools
rgeos broom
tidyr
4.input shapefile
(Taiwan area)
5.subsetting region
6.smooth the boundary
7.manual fixed centroid
data
ggmap
8.use the Stamen map
map
integration
Project Github URL
1. WHO(2015),Measuring the age-friendliness of cities A guide to using core indicators
2. 2016 Transportation Annual Statistics, Ministry of Transportation and Communications R.O.C
3. 2013 Statistic of General Health and Welfare, Ministry of Health and Welfare
4. 2016 Monthly Ratio of House Cost and Income, Department of Land Administration, M. O. I.
5. R Core Team (2016). R: A language and environment for statistical computing. R Foundation for 3. Statistical Computing, Vienna, Austria.
6. Hadley Wickham and Romain Francois (2015). readr: Read Tabular Data. R package version 0.2.2.
7. Hadley Wickham and Romain Francois (2015). dplyr: A Grammar of Data Manipulation. R package version 0.4.3.
8. D. Kahle and H. Wickham. ggmap: Spatial Visualization with ggplot2. The R Journal, 5(1),144-161.
9.Roger Bivand and Nicholas Lewin-Koh (2016). maptools: Tools for Reading and Handling Spatial Objects. R package version 0.8-39.
10.Roger Bivand and Colin Rundel (2016). rgeos: Interface to Geometry Engine - Open Source (GEOS). R package version 0.3-19.
11.Roger Bivand, Tim Keitt and Barry Rowlingson (2016). rgdal: Bindings for the Geospatial Data Abstraction Library. R package version 1.1-10.
12.H. Wickham. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2009.
Reference
Acknowledgement
1.DSP
2.Open Culture Foundation
Quality of
Life
Equity
Physical
Environment
Social
Environment
AgeFriendlyCity:Physical Environment
AgeFriendlyCity:Social Environment
AgeFriendlyCity:Equity
AgeFriendlyCity:Quality of Life
36 inch
91.44cm
40 inch
101.6cm

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9. useR!2016
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Richard Becker
Donald Knuth
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Statistics Method
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5min
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12. networking

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14. useR!2016
keynote
lighting/
contribute
other

15. useR!2016
Tutor
Sponsor: H2o data company
Develop: SparkR,R markdown
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Statistic Book Author:Max Kuhn
3 hr per workshop
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Github note
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16. useR!2016
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Richard Becker Donald Knuth Deborah Nolan Hadley Wickham
Literature
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R S
How to teach Data science
in Berkeley
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in R world

17. useR!2016
Keynote
Richard Becker
R S
why has the S language stayed around for 40 years ?
1.
2. S
3.
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5. unix
AT&T
R S
1970 1991
R
Along Came & Robert Gentleman

18. useR!2016
Keynote
Donald Knuth
Literature
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1980s TeX
R Markdown
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19. useR!2016
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Data science teacher
in UC Berkeley
Math Statistics Probability Data Analysis
Teaching without context
which is wrong
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3.
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20. useR!2016
Keynote
Hadley Wickham
Hadley“verse”
in R world

21. useR!2016
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Hadley Wickham
Hadley“verse”
in R world
Import
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22. useR!2016
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Hadley Wickham
Hadley“verse”
in R world
lazyeval
ggstat gggeom
dplyr
ggplot2
ggvis
Future: tidy verse

23. UseR!2016
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1. ....
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3. Poster

24. UseR!2016
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1. R library
-
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2.
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Karl Broman
Wisconsin-Madison University
R

25. UseR!2016
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h20
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Rstudio htmlwidge, shiny, dashboard,r notebook
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