Difference between revisions of "Group01 proposal"

Revision as of 20:56, 28 February 2020

Team

Proposal

Poster

Application

Research Paper

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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 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 Source: https://www.census.gov/dataviz/visualizations/023/	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 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: This chart needs very specific location data which is not available for us. Thus we will need to re-think how to use the "radius" filter function accordingly.
Title: Bricks Map Source: https://www.perceptualedge.com/blog/?p=1627	Learning Points: (Type point here) Possible Usage: (Type point here) Area for Improvement: (Type point here)
Title: Circular Network Diagram Source: https://www.census.gov/dataviz/visualizations/stem/stem-html/	Learning Points: Help to find the relationship of redistribution between 2 and more variables. Possible Usage: Display the same subzone and planning relationship and distribution between the education level and income level. Area for Improvement: No actual data has been displayed. The circle design and proportion used may not reflect the distribution accurately due to the transformation to the round shape.

BRAINSTORMING SESSIONS

From our initial survey above, we have internalised some of the models and these are some of the ideas we came up with in our Brainstorming sessions: