IS428-AY2019-20T1 Group01-Proposal

Problem Statement

Problem: Our team has identified a lack of information on HDB resale flats for homebuyers who want to understand and make decisions on the type of HDB flat to buy based on past transaction trends.

Motivation: With the increasing demand for housing, there is a need for homeowners to have a better understanding over the flats they are purchasing. Hence, there is a need to analyse the resale prices and transaction volume of the flats.

Selected Data Sets

Dataset/Source	Data Attributes	Rationale of Usage
HDB Resale Flat Prices (https://data.gov.sg/dataset/resale-flat-prices)	Month Town Flat Type Block Street Name Storey Range Floor Area Sqm Flat Model Lease Commence Date Remaining Lease Resale Price	To gain information on the HDB procurement over the years such as: The Resales prices by flat type Area size and Floor level and; The lease date of the flat.

Background Survey of Related Work

Reference of Other Interactive Visualization	What we Learnt
Title: HDB One Map Source: https://services2.hdb.gov.sg/web/fi10/emap.html	Shows detailed information on HDB flats but lacks the tool to show an overview on the hdb estates in singapore It is usability is limited by its lack of function to filter by different data variables e.g. region, street, Model, Floor Range, Floor Area and etc.
Title: SRX Heat Map Source: https://www.srx.com.sg/heat-map	Shows an overview of the price and transaction volume of the different types of estate in different towns. Bad color scheme used Could include more interactive elements to the chart & detailed information (eg when hover over a district can show price & no. of transactions)
Title: Line Chart Source: https://www.teoalida.com/singapore/hdbprices/	Able to see the trend in a glance based on the different flat type Messy, not interactive as it does not show any highlight line when users hover over to the town that they want to see
Title: Horizon Chart Source: https://flowingdata.com/2015/07/02/changing-price-of-food-items-and-horizon-graphs/	It allows users to look at patterns over time It does not come with any axis or bounds which makes it easy to implement Horizon chart also supports mouse interaction when hovered or selected in the chart. It makes use of color based code to separate positive and negative values It collapses the negative values to the positive side of the axis, taking up less space and shows the same data.
Title: Horizon Chart Source: https://www.perceptualedge.com/blog/?p=390	Using different colour codes, it made the interpretation of data between charts much easier. Using the mirrored approach, it is much easier to compare the variance of data when they are side by side.
Title: TreeMap Source: http://rpubs.com/tskam/treemap	Main benefits of tree maps is that they make efficient use of compact space, so they can legibly display many items on the screen at the same time. But treemaps with too many items tend to be hard to read because of the many lines that enclose each small node.
Title: Overlay BarChart Source: https://blogs.sas.com/content/graphicallyspeaking/2014/07/27/overlay-bar-charts/	Overlay BarChart reduces the chances of frequency measurement error.

Proposed Dashboard

Our group has proposed the following storyboard in our Visual Application:

Dashboards	Rational
Example	Example
Dashboard 2: Price/Transaction Volume Dashboard	A horizon Chart to show the Resale Prices or Transaction Volumes by Towns. When Filtered to Resale Prices and Selected Town, the right graph will display a Line chart. It will show the absolute Resale price of the selected town and the changes of Resale price from the previous year to the current year. When filtered by Transaction Volume, it will show the absolute Transaction Volume of the selected town and changes of transaction volume from the previous year to the current year.
Dashboard 3: Past HDB Resale Transactions	The user will apply filters on the price range, lease year, flat type and flat model When filters are applied, the proportional map and heat map will reflect the selections accordingly The proportional map’s symbol size is determined by the number of transactions within each town The heatmap shows the median past transaction prices by town and flat type The heatmap shade intensity is determined by the median transaction price Upon hovering over the points on the proportional map, it will show a box plot with the distribution of the transaction prices by the specific town

Milestones