IS428 AY2019-20T2 Assign DAVID CHOW JING SHAN

Assignment 3 - To be a Visual Detective: SMU libraries

Background

Every two years, SUM libraries conduct a comprehensive survey to receive feedback from the faculty, students, and staff with regards to the libraries' services. With the data collected, SMU libraries hope to gain some insights so that they can enhance their existing services and meet the emerging needs of SMU faculty, students and staff.

However, the past reports were not able to give a comprehensive and condensed summary for SMU libraries as they are mainly made-up of pages of tables. With so much information, it becomes difficult for SMU libraries to get an essential overview that allows them to gain useful insights.

Objectives

With such a massive amount of data being collected, it is important to summarize the key areas and provide proper visualizations for them. Hence, using all the visualization and analytical techniques that I have learned in class, I aim to create an interactive data visualization to help SMU libraries better understand their service feedbacks so that they can make the necessary improvements to satisfy the needs of their respective users.

With this interactive visualization, SMU libraries would be able to easily gain insights from the feedback given by the following stakeholders:

• undergraduate students
• postgraduate students
• faculty
• staff

Data and Visualization

About Data

With the given data(2018 Survey dataset), like any visualization process, it is vital to understand and look through the data before using any visualization software. I will be using Tableau as my visualization software and there is some work to be done on the given datasets before I plot my visualizations. The given data consist of two main files: One contains the tabular data while the other contains feedback comments.

For the tabular data, I plan to separate them into 'identifier questions' and 'ranking questions'.

'Identifier questions' are mainly categorical questions that are used to categorize the respondents. The important questions include:

1. StudyArea - Area of study/research/teaching
2. Position - Years of study/Occupation
3. ID - local or international student
4. HowOftenL - Frequency to library
5. HowOftenC - Frequency to the school campus
6. HowOftenW - Frequency to accessing library resources

'Ranking questions' are the main feedback from respondents. The data collected are mostly in Likert scale (from 1-lowest to 7-Highest). Most of these questions are repeated three times for different purposes: Importance(I), Performance(P) & NA. For I and NA, they both have the same 26 questions while P has one extra question, "Overall how satisfied are you with the Library?". With some references from the past reports, I will also segment the questions into four main categories:

1. Information Resources
2. Facilities Equipment
3. Communication
4. Service Delivery

This will help me to provide a more organized visualization for the user.

Data Preparation

Data preparation

Screenshot	Steps Taken
	Upon initial inspection of the tabular dataset('Raw data 2018-03-07 SMU LCS data file - KLG.xlsx'), I found out there's an invalid row: ResponseID 833. It is invalid because, apart from the many empty fields, it does not have any input under the 'Position' field as well. This makes it difficult for me to categorize this response properly. Thus, I will be removing it from the dataset by deleting that row.
	Firstly, I copied the field/question names(from I1 to I26) from the 'Legend' tab and rename the question ID in the 'SMU' tab respectively(Using transpose paste option in excel). Then, I save it as a new file that is meant for 'Importance ranking' visualization. Lastly, I would do the same for the 'Performance ranking' fields(from P1 to P27). Then save the file.
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Interactive Visualization

The interactive visualization can be accessed here:

Home Dashboard

The following shows the home dashboard:

Importance ranking

The following shows the importance dashboard:

Performance ranking

The following shows the Performance dashboard:

Level of services perceived by undergraduate, postgraduate, faculty and staff (Performance)

Now that we have created all the necessary dashboard, we are ready to use it as a platform to conduct our exploration and analysis.

Insights