HomeIntel

500px

Team

Proposal

Poster

Application

Research Paper

<--- Go Back to Project Groups

MOTIVATION

Our main motivation in this research is to address the lack of a convenient and comprehensive platform to study the correlations and trends amidst South Korea’s rapidly growing and developing tourism industry.

Currently, Korea Tourism Organization (KTO) provides market reports and basic info-graphics to analyze large amounts of complex data through the website and annual reports. Having mentioned KTO’s goals before, it is essential to further identify areas that need attention and further investment and clarify seasonal patterns of international visitors.

OBJECTIVES

Out of the many insights we can drive from the data set, we decided to focus on 3 main objectives. The objectives we hope to address through this project are as follows:

1. Gain overall insight on the monthly visitor arrivals and seasonal trend to South Korea over the last 10 years.
2. Identify popular tourism destinations in different regions of Korea and the yearly trend of the tourism destinations.
3. Gain insights on the purpose of visit and other demographic information of the international visitors.

By taking a look at these three information about the tourism, we would be able to understand the influx of visitors, why they come along with the places they visit when they come. This would allow us and the users of the application to know what season is the most popular, what tourist attraction is popular in each province etc.

SELECTED DATASET

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

Dataset/Source	Data Attributes	Rationale Of Usage
Visitor Arrivals Statistics (2007 January - 2018 September) (https://kto.visitkorea.or.kr/eng/tourismStatics/keyFacts/KoreaMonthlyStatistics.kto )	Month Year Country Number of Visitor Arrivals	This dataset will be used to understand the number of visitors to South Korea from 2007 January to 2018 June. This will allow us to understand the inflow of visitors and see the trend (seasonal trend) of when the visitors come in.
International Visitor Survey (2007 - 2018 ) (https://kto.visitkorea.or.kr/kor/notice/data/statis/tstatus.kto)	City Tourist Attraction Local/Foreigner Date No. of Visitors Latitude Longitude	This dataset will be used to understand the most popular tourist attraction in the different major cities in Korea. We will also be able to gain insights on the Number of visitors to each attraction and also if they are local and foreigner visitors which will allow us to see the difference between locals and foreigners.
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.
Entry by nationality by Sex (2007 - 2018) (Click to View Data)	City Sex 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 Gender.
Entry by nationality by Purpose (2007 - 2018) (Click to View Data)	City Purpose of Visit 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 Purpose of Visit.

BACKGROUND SURVEY

Before we embarked on this project, we did some basic background research on this topic to see if there were any visualizations or dashboards we could drive inspirations from or make it better. Below are a few visuals we found:

Reference of Other Interactive Visualization	Learning Point
Title: Monthly Number of Individual Travelling Visitors (2016) Source:https://www.data.go.kr/visual/content/577	We can understand the monthly visitor arrivals' patterns throughout the year. However, we feel that a time series line graph would be more appropriate, and there should be a wider year range to better understand the exact trend in visitor arrivals.
Title: Foreign tourists visiting Korea by 2015 250px Source:http://m.datanews.co.kr/m/m_article.html?no=2995	This bar chart displays the visits to various tourist attraction by year. Data labels and legends can help us see the precise figures.
Title: Most visited tourism attractions in South Korea 2015 250px Source:https://know.tour.go.kr/ptourknow/knowplus/kChannel/kChannelPeriod/kChannelPeriodDetail.do?seq=102612	This helps us to learn the most visited attractions by region as well as the increase / decrease as compared to the previous year. We can enhance on this idea to make an interactive map so that the user can analyze with filters.

CONSIDERATION & VISUAL SELECTION

Below are a few visualizations and charts we considered making for our projects.

Visual Considerations	Insights / Comments
Title: Sunburst Diagram Source:https://bl.ocks.org/mbostock/4348373	Pros: Aims to show various sub-components of a particular category Can drill down to multiple divisions to observe the distribution by percentages May be useful to analyze tourism receipts by components and country Cons: Difficult to break down the huge number of markets Does not provide a comprehensive time-series comparison
Title: Treemap 250px Source:https://www.theinformationlab.co.uk/2015/02/10/show-treemaps/	Pros: Effective visualisation to organise multivariate data by hierarchy We can effectively see the purpose of visit for the top 10 visiting countries to Korea. Cons: It would be hard to compare between years and months for different countries. The hierarchy will only be 2 levels so the interaction would not be as much.
Title: Chord Diagram 250px Source:https://beta.observablehq.com/@mbostock/d3-chord-diagram	Pros: Effective visualisation to see the influx of Visitors from and to Korea. We will be able to easily spot the country with the most travelers to Korea. Cons: This chart will make it harder to spot trends in the visiting pattern. We will not be able to see every single country as the size of the chord diagram is limited.

BRAINSTORMING SESSIONS

500px

To come up with the story board, our group met up several times to try and come up with a visual. The two charts above are a few dashboards we considered making for our project. First Chart being a Chord diagram of visitors coming in and out of Korea. With an attractive look and great interaction, at first we felt that it was a good dashboard. But with some discussion and consultations, we realised that it would not help us achieve our goal of seeing the seasonal trend of visitors through the years. The second chart is a map with a hover function to see the popularity. We still stick to a similar design but instead of a tooltip like feel, we decided to give a whole section to the popularity part.

After the sessions, we came up with our final designs which are listed below.

PROPOSED STORYBOARD

Below is the proposed story board for our project:

Storyboard	Insights / Comments
Title: Storyboard 1 - Seasonal Trend 300px	Aims to show the seasonal trend of yearly visitor arrivals by country and month. There is a slider to select the year range and two dropdowns to analyse specific months and countries.
Title: Storyboard 2 - Tourist Attractions 400px	Aims to show the yearly / monthly trend in popular tourism destinations, filtered by year and month. After selecting a region, the map will zoom in and display various tourism attractions within that region. When the user hovers over a specific destination, there will be a time series graph of the local / foreigner arrivals as well as a picture of the destination.
Title: Storyboard 3 - Demographic information 400px	Aims to provide demographic information and the purpose of arrival through trend line charts and other barcharts. Users can select the year/month and country from the dropdown list.

TECHNOLOGIES

The technologies we will be using for this Project is as below:

650px

CHALLENGES

Challenges	Mitigation Plan
Unfamiliarity of Visualization Technologies such as Tableau, R,Rshiny etc.	Attending Workshop on R and Rshiny Hands-on Practice with different technologies. Peer Learning.
Data Cleaning & Transformation from messy data.	Organize Meeting Sessions to meet and do data cleaning and transformation together. Split the work between team members. Python Scripting to find Top 10, Sort data and translate.
Integrating Relevant Data from Multiple Sources Proposed Solution.	Working together to decide on what data to extract or eliminate. Trial and test for one set of data together before splitting the work.

TIMELINE

1000px

COMMENTS

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