Difference between revisions of "Group01 proposal"

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|-
 
|-
  
| <center>(Data Source)
+
| <center><strong>Resident by planning Area, subgroup, age Group, sex and dwelling</strong>
(Data time of coverage)<br/><br/>
+
(2000 - 2019, June)<br/><br/>
(Link to data source) </center>
+
https://www.singstat.gov.sg/find-data/search-by-theme/population/geographic-distribution/latest-data </center>
 
||  
 
||  
* '''Attribute''':
+
* Planning area
: Examples
+
* SubZone
 +
* Age group
 +
* Type of dwelling
 +
* Gender
 +
||
 +
This dataset covers a good time series from 2000-2019 and the breakdown by subzone/planning area allows it to serve as the base platform to integrating with other population data sets that are grouped by subzone/planning area as well.
 +
 
 +
From here, we can also get a good view of Singapore’s residential distribution by gender and age group that might give us a few initial findings that help for further investigation with the help of complimentary data sets.
 +
|-
 +
 
 +
| <center><strong>Singapore General Household Survey & Census of population</strong>
 +
(2000, 2010, 2015)<br/><br/>
 +
https://www.singstat.gov.sg/find-data/search-by-theme/population/geographic-distribution/latest-data </center>
 +
||
 +
Contains the following attributes by Planning Area:
 +
* Gender
 +
* Occupation
 +
* Income Levels
 +
* Travel Time to work/School
 +
* Educational Qualification
 +
* Language Preference
 +
* Religion
  
* '''Attribute''':
 
: Examples
 
 
||
 
||
<center>The dataset will be used to understand the Indonesian Export and import figure from 1996 - 2019, July across multiple categories. At the end, we wish to spot the trend or pattern of Indonesia trading and economy situation.</center>
+
This data adds a very rich level of dimensionality on top of the residential data as mentioned above.  However, it only covers limited points in time and so we intend to use this data separately for more deep time static analysis.
 +
 
 +
Also, as this data is very rich, we hope that it can further serve as a bridge to more abstract but complementary data.
 
|-
 
|-
  
| <center>(Data Source)
+
| <center><strong>Birth & Fertility Rate</strong>
(Data time of coverage)<br/><br/>
+
(1960 - 2018, annual)<br/><br/>
(Link to data source) </center>
+
https://www.singstat.gov.sg/find-data/search-by-theme/population/births-and-fertility/latest-data </center>
 
||  
 
||  
* '''Attribute''':
+
* Total Fertility rate
: Examples
+
* Fertility Rate by age group
 +
* Fertility rate by ethinic group
 +
* Gross and net reproduction rate
 +
* Crude birth rate
 +
* Total live-births
 +
* Resident live-births
 +
* Total live - birth by ethnic group and gender
  
* '''Attribute''':
 
: Examples
 
 
||
 
||
<center>The dataset will be used to understand the Indonesian Export and import figure from 1996 - 2019, July across multiple categories. At the end, we wish to spot the trend or pattern of Indonesia trading and economy situation.</center>
+
This data set gives quite good coverage on the number of births by different dimentions i.e. ethnicity, age group, educational background of parents. This will be helpful in helping us bridge this data set with the other population data sets to explore Singapore’s Birthrate problems in greater detail.  
 
|-
 
|-
  
| <center>(Data Source)
+
|<center><strong>Hospital Admission Rate By Sex and Age</strong>
(Data time of coverage)<br/><br/>
+
(1984 - 2018)<br/><br/>
(Link to data source) </center>
+
https://www.singstat.gov.sg/find-data/search-by-theme/society/health/latest-data </center>
 
||  
 
||  
* '''Attribute''':
+
* Acute / Community / Psychiatric hospital By age group  (0-14, 15-64, >65 )
: Examples
+
* Total Number of admissions by hospital
  
* '''Attribute''':
 
: Examples
 
 
||
 
||
<center>The dataset will be used to understand the Indonesian Export and import figure from 1996 - 2019, July across multiple categories. At the end, we wish to spot the trend or pattern of Indonesia trading and economy situation.</center>
+
This data helps to give a high level view on the hospitals of singapore and how many admissions they had each year.  
 +
 
 +
It will be useful to integrate this with the population data set to see how taxed each hospital is in caring for different age groups through the years.
 
|}
 
|}
 
</center>
 
</center>
 +
<br>
 +
We will be using these data sets as our main inputs. However, we are still open to add complimentary data sets to further enhance the quality insights attained from our visualisation.
 
<br>
 
<br>
 
<br/>
 
<br/>
Line 103: Line 130:
 
==<div style="background:#D4AC0D; padding: 15px; font-weight: bold; line-height: 0.3em; letter-spacing:0.5em;font-size:20px"><font color=#fff face="Century Gothic"><center>BACKGROUND SURVEY</center></font></div>==
 
==<div style="background:#D4AC0D; padding: 15px; font-weight: bold; line-height: 0.3em; letter-spacing:0.5em;font-size:20px"><font color=#fff face="Century Gothic"><center>BACKGROUND SURVEY</center></font></div>==
 
<br/>
 
<br/>
We did basic background research on some existing visualizations or dashboards we could drive inspirations from or make it better. Below are a few visuals we found:
+
To begin, we explored current charts that were used to visualise the key areas that we defined to explore (e.g. inequality, urban planning, geo-plots).  
 +
This is a summary of the more interesting visualisations we found:
 
<center>
 
<center>
 
{| class="wikitable" style="background-color:#FFFFFF;" width="90%"
 
{| class="wikitable" style="background-color:#FFFFFF;" width="90%"
Line 112: Line 140:
  
 
| <center>
 
| <center>
'''Title''': (Type Title Here)
+
'''Title''': Income distribution by country over the years
[[File:Policy_And_Planning_Background1.png|300px|frameless|center]]
+
[[File:Policy_And_Planning_Background_1.png|300px|frameless|center]]
 
<br/>
 
<br/>
'''Source''': (Source Link Here)
+
'''Source''': https://www.gapminder.org/tools/#$chart-type=mountain
 
</center>
 
</center>
  
 
||  
 
||  
'''Positive Points:'''
+
'''Learning Points:'''
# (Type point here)
+
* Highly interactive; The detailed data of the region can be displayed at corner upon selecting
 
+
* An overview of all the countries, income population, distribution in the same chart. Converted the Continent information into different colours.
'''Negative Points:'''
+
<br>
# (Type point here)
+
'''Possible Usage: '''
 +
* It allowed the team to discover all the subzone/ planning area income distribution in the same chart with a generic reference line of average income of the Singapore or world poverty line. It would be helpful for the decision maker to redistribute the resource for the needy residents
 +
<br>
 +
'''Area for Improvement: '''
 +
* The selection has the animation of highlighted areas instead of lines. The user could get wrong information as they might be misled by the proportion of the offset area.
 +
<br>
 
|-
 
|-
  
 
| <center>
 
| <center>
'''Title''': (Type Title Here)
+
'''Title''': Changing Ranks of States by Congressional Representation
[[File:Policy_And_Planning_Background1.png|300px|frameless|center]]
+
[[File:Policy_And_Planning_Background_2.png|300px|frameless|center]]
 
<br/>
 
<br/>
 
'''Source''': (Source Link Here)
 
'''Source''': (Source Link Here)
Line 134: Line 167:
  
 
||  
 
||  
'''Positive Points:'''
+
'''Learning Points:'''
# (Type point here)
+
* Provide the consistency of changing rank over the sampling period.
 +
<br>
 +
'''Possible Usage: '''
 +
* Helpful for indicating the rank of the population density rank or other rank to find the changing of the hotspots between 2 or more periods.
 +
<br>
 +
'''Area for Improvement: '''
 +
* No actual data has been displayed. Only limited insights could be found from the chart
 +
* The colour and intercepted points among the used could cause misunderstanding
 +
<br>
 +
|-
 +
 
 +
| <center>
 +
'''Title''': Interactive map visualization
 +
[[File:Policy_And_Planning_Background_3.png|300px|frameless|center]]
 +
<br/>
 +
'''Source''': https://morphocode.com/the-5-minute-walk/
 +
</center>
  
'''Negative Points:'''
+
||
# (Type point here)
+
'''Learning Points:'''
 +
* Chart A enables users to zoom into different planning areas in the geographic distribution. Then, information of the resident population by subgroup, age group, type of dwelling will be presented by the bar chart. It allows immediate comparison of the resident population between the planning areas and draws trends among other observations.
 +
* Moreover, with possible available datasets of schools, hospitals, resident household income, etc by location point, interactivity can be applied as shown in chart B. By clicking into a specific subzone, it allows users to adjust a range of radius. As the radius expands, a pie chart will show the increase in number of schools, hospitals, resident household, income, etc.
 +
<br>
 +
'''Possible Usage: '''
 +
* This can be used in our setting to do sharp analysis of specific amenities and how much of the population they cater to. E.g the user could perhaps look at common places of leisure (Parks), or Hospitals and using a radius of Planning areas, calculate the proportion of age group that the facility caters to.
 +
<br>
 +
'''Area for Improvement: '''
 +
* (Type point here)
 +
<br>
 
|-
 
|-
  
 
| <center>
 
| <center>
'''Title''': (Type Title Here)
+
'''Title''': Bricks Map
[[File:Policy_And_Planning_Background1.png|300px|frameless|center]]
+
[[File:Policy_And_Planning_Background_4.png|300px|frameless|center]]
 
<br/>
 
<br/>
'''Source''': (Source Link Here)
+
'''Source''': https://www.perceptualedge.com/blog/?p=1627
 
</center>
 
</center>
  
 
||  
 
||  
'''Positive Points:'''
+
'''Learning Points:'''
 +
# (Type point here)
 +
<br>
 +
'''Possible Usage: '''
 
# (Type point here)
 
# (Type point here)
 
+
<br>
'''Negative Points:'''
+
'''Area for Improvement: '''
 
# (Type point here)
 
# (Type point here)
 +
<br>
 
|}
 
|}
 
</center>
 
</center>

Revision as of 17:53, 28 February 2020

Policy And Planning logo.png


Team

 

Proposal

 

Poster

 

Application

 

Research Paper


<-- Go back to project groups

PROBLEM & MOTIVATION


With Singapore’s growing population and limited resources, she faces many pressing challenges for progressive development and economic growth. These challenges span across housing affordability, rising healthcare, aging population, education/income inequality, and low birth rates. For Singapore to continue progressing, it is imperative that the government continues to take proactive measures to plan and utilise its resources effectively. In this fashion, we strive to use visual analytics to help uncover some of the cracks in and opportunities in Singapore’s social demographic to assist the government in sharpening its current policies and to look into future plans. This is well in line with the government’s effort of making socially relevant data public to encourage innovation and discovery.


PROJECT OBJECTIVES


TO DO: Explain project Objectives

SELECTED DATABASE


The Data Sets we will be using for our analysis and for our application is listed below:

Dataset/Source Data Attributes Rationale Of Usage
Resident by planning Area, subgroup, age Group, sex and dwelling

(2000 - 2019, June)

https://www.singstat.gov.sg/find-data/search-by-theme/population/geographic-distribution/latest-data
  • Planning area
  • SubZone
  • Age group
  • Type of dwelling
  • Gender

This dataset covers a good time series from 2000-2019 and the breakdown by subzone/planning area allows it to serve as the base platform to integrating with other population data sets that are grouped by subzone/planning area as well.

From here, we can also get a good view of Singapore’s residential distribution by gender and age group that might give us a few initial findings that help for further investigation with the help of complimentary data sets.

Singapore General Household Survey & Census of population

(2000, 2010, 2015)

https://www.singstat.gov.sg/find-data/search-by-theme/population/geographic-distribution/latest-data

Contains the following attributes by Planning Area:

  • Gender
  • Occupation
  • Income Levels
  • Travel Time to work/School
  • Educational Qualification
  • Language Preference
  • Religion

This data adds a very rich level of dimensionality on top of the residential data as mentioned above. However, it only covers limited points in time and so we intend to use this data separately for more deep time static analysis.

Also, as this data is very rich, we hope that it can further serve as a bridge to more abstract but complementary data.

Birth & Fertility Rate

(1960 - 2018, annual)

https://www.singstat.gov.sg/find-data/search-by-theme/population/births-and-fertility/latest-data
  • Total Fertility rate
  • Fertility Rate by age group
  • Fertility rate by ethinic group
  • Gross and net reproduction rate
  • Crude birth rate
  • Total live-births
  • Resident live-births
  • Total live - birth by ethnic group and gender

This data set gives quite good coverage on the number of births by different dimentions i.e. ethnicity, age group, educational background of parents. This will be helpful in helping us bridge this data set with the other population data sets to explore Singapore’s Birthrate problems in greater detail.

Hospital Admission Rate By Sex and Age

(1984 - 2018)

https://www.singstat.gov.sg/find-data/search-by-theme/society/health/latest-data
  • Acute / Community / Psychiatric hospital By age group (0-14, 15-64, >65 )
  • Total Number of admissions by hospital

This data helps to give a high level view on the hospitals of singapore and how many admissions they had each year.

It will be useful to integrate this with the population data set to see how taxed each hospital is in caring for different age groups through the years.


We will be using these data sets as our main inputs. However, we are still open to add complimentary data sets to further enhance the quality insights attained from our visualisation.


BACKGROUND SURVEY


To begin, we explored current charts that were used to visualise the key areas that we defined to explore (e.g. inequality, urban planning, geo-plots). This is a summary of the more interesting visualisations we found:

Reference of Other Interactive Visualization Learning Point

Title: Income distribution by country over the years

Policy And Planning Background 1.png


Source: https://www.gapminder.org/tools/#$chart-type=mountain

Learning Points:

  • Highly interactive; The detailed data of the region can be displayed at corner upon selecting
  • An overview of all the countries, income population, distribution in the same chart. Converted the Continent information into different colours.


Possible Usage:

  • It allowed the team to discover all the subzone/ planning area income distribution in the same chart with a generic reference line of average income of the Singapore or world poverty line. It would be helpful for the decision maker to redistribute the resource for the needy residents


Area for Improvement:

  • The selection has the animation of highlighted areas instead of lines. The user could get wrong information as they might be misled by the proportion of the offset area.


Title: Changing Ranks of States by Congressional Representation

Policy And Planning Background 2.png


Source: (Source Link Here)

Learning Points:

  • Provide the consistency of changing rank over the sampling period.


Possible Usage:

  • Helpful for indicating the rank of the population density rank or other rank to find the changing of the hotspots between 2 or more periods.


Area for Improvement:

  • No actual data has been displayed. Only limited insights could be found from the chart
  • The colour and intercepted points among the used could cause misunderstanding


Title: Interactive map visualization

Policy And Planning Background 3.png


Source: https://morphocode.com/the-5-minute-walk/

Learning Points:

  • Chart A enables users to zoom into different planning areas in the geographic distribution. Then, information of the resident population by subgroup, age group, type of dwelling will be presented by the bar chart. It allows immediate comparison of the resident population between the planning areas and draws trends among other observations.
  • Moreover, with possible available datasets of schools, hospitals, resident household income, etc by location point, interactivity can be applied as shown in chart B. By clicking into a specific subzone, it allows users to adjust a range of radius. As the radius expands, a pie chart will show the increase in number of schools, hospitals, resident household, income, etc.


Possible Usage:

  • This can be used in our setting to do sharp analysis of specific amenities and how much of the population they cater to. E.g the user could perhaps look at common places of leisure (Parks), or Hospitals and using a radius of Planning areas, calculate the proportion of age group that the facility caters to.


Area for Improvement:

  • (Type point here)


Title: Bricks Map

Policy And Planning Background 4.png


Source: https://www.perceptualedge.com/blog/?p=1627

Learning Points:

  1. (Type point here)


Possible Usage:

  1. (Type point here)


Area for Improvement:

  1. (Type point here)





BRAINSTORMING SESSIONS


(TO DO: Insert Brainstorming charts & Explain)


(Type in methodology of brainstorming sessions and explain how each chart was derived and the potential use)


PROPOSED STORYBOARD


Below is the proposed story board for our project:

Storyboard Insights / Comments

Title: DASHBOARD X - (Type in Dashboard Title)

  • Point for insights and comments
  • Point for insights and comments
  • Point for insights and comments

Title: DASHBOARD X - (Type in Dashboard Title)

  • Point for insights and comments
  • Point for insights and comments
  • Point for insights and comments

Title: DASHBOARD X - (Type in Dashboard Title)

  • Point for insights and comments
  • Point for insights and comments
  • Point for insights and comments

Title: DASHBOARD X - (Type in Dashboard Title)

  • Point for insights and comments
  • Point for insights and comments
  • Point for insights and comments



TECHNOLOGY USED


The technologies we will be using for this Project are as below: (TO DO: Show png of the tech used)



CHALLENGES, RISK ASSESMENT AND MITIGATION


Challenges Mitigation Plan
  • Unfamiliarity of visualisation tools such as R, R Shiny, Tableau.
  • Hands on practice using the different training platforms such as Data Camps
  • Watch video tutorials from YouTube
  • Peer Learning
  • Unfamiliarity of data cleaning and transformation using Tableau Prep
  • Attend workshop on data cleaning methods
  • Watch video tutorials on how to fully utilise Tableau Prep
  • Trial and test on the different cleaned data sets while maintaining the raw data
  • Limited knowledge and the jargon used in Indonesia’s trading industry
  • Research and learn the situation of Indonesia’ export and import in the last ten years
  • Read articles or news to find out the recent trends and global updates on trade




PROPOSED TIMELINE


(TODO: Insert High level timeline & Gantt Chart)




COMMENTS AND FEEDBACK


Feel free to leave us some comments so that we can improve!

No. Name Date Comments
1. Insert your name here Insert date here Insert comment here
2. Insert your name here Insert date here Insert comment here
3. Insert your name here Insert date here Insert comment here