Difference between revisions of "Qui Vivra Verra - Technology"
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| − | | style="vertical-align:top;width:14%;" | <div style="padding: 3px; text-align:center; line-height: wrap_content; font-size:15px; border-bottom:2px solid #0163bd; font-family:Century Gothic"> [[Qui Vivra Verra - Project Overview | + | | style="vertical-align:top;width:14%;" | <div style="padding: 3px; text-align:center; line-height: wrap_content; font-size:15px; border-bottom:2px solid #0163bd; font-family:Century Gothic"> [[Qui Vivra Verra - Project Overview| <b>Motivation & Objectives</b>]] |
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| style="vertical-align:top;width:14%;" | <div style="padding: 3px; text-align:center; line-height: wrap_content; font-size:15px; border-bottom:5px solid #0163bd; font-family:Century Gothic"> [[Qui Vivra Verra - Technology| <b>Technology</b>]] | | style="vertical-align:top;width:14%;" | <div style="padding: 3px; text-align:center; line-height: wrap_content; font-size:15px; border-bottom:5px solid #0163bd; font-family:Century Gothic"> [[Qui Vivra Verra - Technology| <b>Technology</b>]] | ||
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JMP Pro 12 is a tool developed by the JMP division of SAS. As the data files are too large to be opened by conventional means such as Excel and Notepad, we will be using this tool to explore the data. Market Segment Analysis will also be done using the clustering function of this application. | JMP Pro 12 is a tool developed by the JMP division of SAS. As the data files are too large to be opened by conventional means such as Excel and Notepad, we will be using this tool to explore the data. Market Segment Analysis will also be done using the clustering function of this application. | ||
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| + | <div style="background: #dce6f9; line-height: 0.3em; font-family:Century Gothic; border-left: #003464 solid 15px;"><div style="border-left: #FFFFFF solid 5px; padding:15px;font-size:15px;"><font color= "#000000"><strong>Shiny R</strong></font></div></div> | ||
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| + | We will now be using only Shiny R, instead of using a combination of Shiny R and Apache Spark as mentioned in our proposal. We have chosen Shiny R mainly due to the statistical function provided by R, which would be useful to our project. R also have many ready-made visualizations which would hopefully save us some time required for coding. | ||
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Leaflet.js is an open source javascript library for interactive maps. This tool will be used to create a visualization page for the users where a map of Singapore, as well as point symbols representing various facilities will be displayed. The user can select the attribute to be considered for computing the attractiveness index by selecting or deselecting facility layers as well as varying buffer radius. This tool is selected as it provides a range of interactive maps and is easy to implement. It supports various plugins to extend its functionality. | Leaflet.js is an open source javascript library for interactive maps. This tool will be used to create a visualization page for the users where a map of Singapore, as well as point symbols representing various facilities will be displayed. The user can select the attribute to be considered for computing the attractiveness index by selecting or deselecting facility layers as well as varying buffer radius. This tool is selected as it provides a range of interactive maps and is easy to implement. It supports various plugins to extend its functionality. | ||
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| + | As the project has some geo-spatial nature, we have decided to use the leaflet package available in Shiny R for our visualization and analysis. The visualizations of the Singapore base map, as well as the various layers that will be added in like Libraries, Tuition Centres, Planning Areas, will all be done using leaflet. Users will also be able to select layers and adjust other input variables with this. | ||
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| − | <div style="background: #dce6f9; line-height: 0.3em; font-family:Century Gothic; border-left: #003464 solid 15px;"><div style="border-left: #FFFFFF solid 5px; padding:15px;font-size:15px;"><font color= "#000000"><strong> | + | <div style="background: #dce6f9; line-height: 0.3em; font-family:Century Gothic; border-left: #003464 solid 15px;"><div style="border-left: #FFFFFF solid 5px; padding:15px;font-size:15px;"><font color= "#000000"><strong>D3</strong></font></div></div> |
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| + | For visualizations not provided in R libraries, we intend to make use of D3 to bridge the gap. | ||
Latest revision as of 23:21, 10 October 2016
JMP Pro 12 is a tool developed by the JMP division of SAS. As the data files are too large to be opened by conventional means such as Excel and Notepad, we will be using this tool to explore the data. Market Segment Analysis will also be done using the clustering function of this application.
We will now be using only Shiny R, instead of using a combination of Shiny R and Apache Spark as mentioned in our proposal. We have chosen Shiny R mainly due to the statistical function provided by R, which would be useful to our project. R also have many ready-made visualizations which would hopefully save us some time required for coding.
Leaflet.js is an open source javascript library for interactive maps. This tool will be used to create a visualization page for the users where a map of Singapore, as well as point symbols representing various facilities will be displayed. The user can select the attribute to be considered for computing the attractiveness index by selecting or deselecting facility layers as well as varying buffer radius. This tool is selected as it provides a range of interactive maps and is easy to implement. It supports various plugins to extend its functionality.
As the project has some geo-spatial nature, we have decided to use the leaflet package available in Shiny R for our visualization and analysis. The visualizations of the Singapore base map, as well as the various layers that will be added in like Libraries, Tuition Centres, Planning Areas, will all be done using leaflet. Users will also be able to select layers and adjust other input variables with this.
JavaScript is a coding language for the web. We will be using JavaScript for most of the application’s user interfaces as it allows the implementation of various libraries to support user’s interactions and improve visualisation.
Turf.js was mainly used for spatial analysis. It provides the functionality to analyse, aggregate and transform data into GeoJSON.
For visualizations not provided in R libraries, we intend to make use of D3 to bridge the gap.
