Data Scholarship Forum

Data visualisation with Tableau
By Pinyuan attending the Library Research Technologies NAA 2018-2019
(Computer Science with Artificial Intelligence Student)

Our project involved describing a large amount of data via Tableau. We imported a set of complicated data and extracted some features and characters from this to display information in a clear way, which makes it easy to understand and analyse.

Data visualisation is a way to discover the insights hidden in your data, with rich, interactive visuals and describes the presentation of abstract information in graphical form.

Data visualisation allows us to makes complex ideas engaging, meaningful, easy to understand and spot patterns, trends, and correlations that otherwise might go unnoticed in traditional reports, tables, or spreadsheets.

6.2.3 Pinyuan Feng
 

This NAA module provided me a meaningful experience to get to know more about data scholarship. Data visualisation is one of the fields in Computer Science and I obtained a lot knowledge from this experience, which may help me a lot in my further study. Tableau is a powerful software to present data information in a clear and easy-to-understand way. 

2018-2019 NAA - Learning Analytics Data Visualisation
By Shixin attending the Library Research Technologies NAA 2018-2019
(Finance Accounting and Management Student)

6.2.3 Shixin Shan

Data scholarship is a study of how to extract information useful from data and how to present the information. The data could be quantitative and also qualitative.

My project can was separated into two parts. The first to visualise some information about teaching sessions to reflect the performance and reaction of our students.

The second part is visualised information of our library’s book borrowing. 

 

Data visualisation provide me a new way to look inside information, a way to think how to handle data and a sight of how to produce information from data. 

From using the data visualisation software, I not only learnt how to use it, but also learnt to think which model provides a better way to show the interconnection of data.

 

2018-2019 NAA  - Visualising trends in research
By Sekun attending the Library Research Technologies NAA 2018-2019
(International Business Management Student)

My project was about visualising data generated from Web of Science, particularly focusing on technology application in business and finance subject area. The total data is 2031 items and time range is all years (1965-2018).

Not only can quantitative data can be visualised into different graphs to show trends or links but also textual data can.

6.2.3 Zekun Geng

 

 

According to frequencies, years, region or other variables, we can draw a map describing the relationship between each datum, showing the intensity and paths among those connections.

I have learnt how to do data visualisation by using CiteSpace to process thousands of data from WOS in Business and Finance subject (technology track), and with synergetic collaboration from my great teammates and supervisor, completed a literature data visualisation project. 

 

2018-2019 NAA - Visualising Influencial Research
By Shuyi attending the Library Research Technologies NAA 2018-2019
(Finance Accounting and Management Student)

This NAA module gave me a new and coherent thought of data visualisation. I also learnt how to use CiteSpace, Tableau, NVivo.

Specifically using CiteSpace, I know how to quickly understand a new domain and know the hot and key research directions, authors and articles.

My project is an analysis of papers about Information Systems in Computer Science published in Web of Science. 

6.2.3 Shuyi Xu

 

 

The contents are which country publishes most papers, what are the hot research directions, who and which papers have more influence in this field.

Data visualisation can make the words understandable, enhance and illustrate key points. The picture can convey intuitive information. In my data visualisation, node, links and color blocks separated or in combination can present different information and show inherent relationship among authors or other objects in data.