Difference between revisions of "IS428-AY2019-20T1 Group09-Proposal"

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Visualisation 1: Chloropleth Map
 
Visualisation 1: Chloropleth Map
[[File:Storyboard2-1.png|500px|frameless|center]]
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* Shows comparison of crime rates across different states
 
* Shows comparison of crime rates across different states
 
* Usage of colour scale for easy identification of crimes with higher crime rates
 
* Usage of colour scale for easy identification of crimes with higher crime rates
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Visualisation 2: Funnel Plot
 
Visualisation 2: Funnel Plot
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* Would be displayed side by side with Visualisation 1
 
* Would be displayed side by side with Visualisation 1
 
* If the user clicks on a particular state on the chloropleth map, its relative position on the funnel plot will be highlighted
 
* If the user clicks on a particular state on the chloropleth map, its relative position on the funnel plot will be highlighted

Revision as of 14:39, 12 October 2019

Logo.png
Team Name


Team

 

Proposal

 

Poster

 

Application

 

Research Paper


<--- Go Back to Project Groups

PROBLEM STATEMENT


According to the Thomson Reuters Foundation Annual Poll, India is ranked as the world’s most dangerous country for women. This is not surprising, as India has had a long-standing history of violence against women, which is deeply rooted in certain cultural practices such as female infanticide and acid attacks.

Even with the increasing public outcry regarding such discrimination and the enactment of laws protecting women, the number of crimes committed against women is increasing steadily over the years.

MOTIVATION


India is one of the world’s fastest growing economies. It is currently the seventh richest country in the world, and is projected to be the third largest economy in the world. Despite its rapid growth and development, women in India still suffer from long-standing gender inequality and are the victims to brutal and inhumane crimes. Hence, there is a need to analyse various socioeconomic factors to garner insights on the root causes for crimes against women to understand why this phenomenon is so.

OBJECTIVES


Our objectives of this project are as follows:

  1. Provide an overview of the issue of crimes against women in India
  2. Draw comparisons to study the differences in crime rates between different states
  3. Study the effect of various socioeconomic factors on the number of crimes committed against women

We hope to achieve these objectives by developing interactive visualisations which can help us to understand the increasing trend of crimes against women, and what factors may contribute to such crime rates.

DATA SOURCES


We have obtained the following datasets for this research:

Dataset/Source Data Attributes Purpose
District-wise Crimes Committed Against Women, 2015
(Click to View Data)


District-wise Crimes Committed Against Women, 2014
(Click to View Data)
  • State/UT
  • Sl No.
  • District
  • Year
  • Rape
  • Attempt to commit Rape
  • Kidnapping & Abduction_Total
  • Dowry Deaths
  • Assault on Women with intent to outrage her Modesty_Total
  • Insult to the Modesty of Women_Total
  • Cruelty by Husband or his Relatives
  • Importation of Girls from Foreign Country
  • Abetment of Suicides of Women Dowry Prohibition Act, 1961
  • Indecent Representation of Women (P) Act, 1986
  • Protection of Children from Sexual Offences Act
  • Protection of Women from Domestic Violence Act, 2005
  • Immoral Traffic Prevention Act
  • Total Crimes against Women
The dataset would provide the crime rate for each type of crime against women, at a district-level. We can then aggregate the data to find trends.
dstrCAW_2013
(Click to View Data)


dstrCAW_1 (2001-2012)
(Click to View Data)
  • STATE/UT
  • DISTRICT
  • Year
  • Rape
  • Kidnapping and Abduction
  • Dowry Deaths
  • Assault on women with intent to outrage her modesty
  • Insult to modesty of Women
  • Cruelty by Husband or his Relatives
  • Importation of Girls
This data set will be used to understand the general demographic of international visitors coming to Korea from 2007 - 2018. We will be able to gain descriptive insights on the visitor demographics by Age Range.
Entry by nationality by age

(2007 - 2018)


(Click to View Data)
  • City
  • Age Range
  • Date
This data set will be used to understand the general demographic of international visitors coming to Korea from 2007 - 2018. We will be able to gain descriptive insights on the visitor demographics by Age Range.


LITERATURE REVIEW


Reference of Other Interactive Visualization Learning Point

Title: Crime Map of India

Example1.png

Source:https://tvganesh.shinyapps.io/crimesAgainstWomenInIndia/

  • The use of a chloropleth map allows us to compare the magnitude of crimes against women in different states.
  • However, it does not account for the difference in the population size within each state, and merely takes the absolute number of crimes in each state as analysis.

Title: RAPE IN INDIA: A visual exploration of systemic rape culture

Example2.png

Source:https://adityajain15.github.io/Rape_In_India/

  • This treemap displays the relationship of the rape offenders to their victims.
  • It also shows the treemap for each state, allowing for comparison across states.
  • The colour scheme of the treemap could be adjusted to be clearer to the viewer as it is hard to compare.

Title: RAPE IN INDIA: A visual exploration of systemic rape culture

Example3.png

Source:https://adityajain15.github.io/Rape_In_India/

  • This visualisation shows the efficacy of the justice system in India in handling rape cases.
  • Each dot represents a single rape case in India, and the dots will travel to show the final outcome of the case - whether it ends in conviction or acquittal, or is dropped in the middle of the process.


CONSIDERATION & VISUAL SELECTION




PROPOSED STORYBOARDS

Storyboard 1 - Overview - Introduction to Crimes Against Women in India


Visualisation 1: Bar Graph with Treemap

Storyboard1-1.png
  • Aims to show the yearly increasing trend of number of crimes against women
  • Upon hovering over a particular year, the treemap showing the breakdown of crime types will be shown for that year.


Visualisation 2: Line Graph

Storyboard1-2.png
  • Shows the trend for the individual crime type across the years

Storyboard 2 - State-Level Comparison of Crime Rates


Visualisation 1: Chloropleth Map

Storyboard2-1.png
  • Shows comparison of crime rates across different states
  • Usage of colour scale for easy identification of crimes with higher crime rates
  • Allows user to filter by year in order to visualise changes in crime rates over the years.
  • Clicking on the button at the bottom would direct the user to Visualisation 3 to view the crime breakdown per state.


Visualisation 2: Funnel Plot

Storyboard2-2.png
  • Would be displayed side by side with Visualisation 1
  • If the user clicks on a particular state on the chloropleth map, its relative position on the funnel plot will be highlighted
  • Usage of the funnel plot allows us to account for differences in population size within each state, as we would be able to plot Population size vs. Number of Crimes against Women for each State.
  • Allows us to identify states with abnormally low/high crime rates for further analysis to be done.


Visualisation 3: Geo Facet

Storyboard2-31.png
  • Bar Graph in each state shows occurrence of each crime type in each state
  • Allows easy comparison across states for which crime type is most common
  • Each cell in the grid shows the distribution of crime type versus just a single value, unlike the chloropleth map


Storyboard 3 - Analysis of Socioeconomic Factors in contributing to Crime Rate Against Women


TECHNOLOGIES


The tools we will be using for this Project is as follows:

G9 technologies.png


CHALLENGES


Challenges Mitigation Plan

Lack of proficiency in using R and R Shiny

  • Complete DataCamp courses on the relevant technologies
  • Watch tutorial videos
  • Read the documentation

District Crime Rates are in separate files, with different data attributes.

  • Clean the data to ensure that the columns are similar
  • Consolidate the data into one file for the years 2001-2015.

Difficulty in understanding some of the data attributes due to its local context, such as the different acts for protection against women found in some of our datasets.

  • Conduct more research on India and its history of crimes against women to get a better understanding of the data.

Difficulty in finding socioeconomic factors by state level

  • Look to different data sources to find more socioeconomic factors for consideration.

The socioeconomic factors identified may not be indicative of the crime rate against women in India, as there may not be a relationship between the two.

  • Do EDA to discover any correlation between each socioeconomic factor and the crime rate, then select the relevant ones from there


TIMELINE


Timeline.png


COMMENTS


Feel free to leave us any comments!

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