Embedded Files
On completion of this unit the student should be able to apply the problem-solving methodology and use appropriate software tools to extract relevant data and create a data visualisation that meets a specified user’s needs.
To achieve this outcome the student will draw on key knowledge and key skills outlined in Area of Study 2. See dot points below.
Visualisation Tools:
Visualisation Tools:
- Microsoft Excel / Google Sheets
- Plotly - Powerful, interactive data vis (and APIs). Cloud service not free
- DataWrapper - Easy to use data vis. Not as flexible as Plotly etc.
- Word Clouds: WordItOut, Wordle (Wordle is the classic, but Java applet based word cloud generator - almost impossible to run now!)
- Chart Chooser (Template generator)
- Based on the Choosing a good Chart infographic
- Python + [Choose library]
Some Data Sources
Some Data Sources
Student Tasks
Student Tasks
- Study a number of data visualisations you find effective. Try to identify the formats and conventions that have been used to make the solution stand out
- Climate Data Tasks (Click through!)
- Geographic Visualizations (Click through!)
- Bureau of Meteorology Task (digipubs version)
Key knowledge
Key knowledge
Data and information
Data and information
- sources of authentic data in large repositories
- factors influencing the integrity of data, for example accuracy, timeliness, authenticity, relevance (ATAR)
- characteristics of data types and data structures relevant to selected software tools
Approaches to problem solving
Approaches to problem solving
- types and purposes of data visualisations (c.f. e.g., infographics)
- problem-solving activities related to analysing needs: functional and non-functional requirements and constraints
- characteristics of file formats and their suitability to be converted to other formats
- design tools for representing data visualisations
- formats and conventions applied to visualisations to improve their effectiveness for intended users
- functions of appropriate software tools to extract targeted data and to manipulate data when developing visualisations
- criteria and techniques for evaluating visualisations.
Key skills
Key skills
- analyse needs to define specific requirements
- identify and extract, using software functions, relevant data from appropriate data sources
- prepare data structures relevant to the software tools
- interpret selected data, identifying relationships and patterns
- select and apply appropriate tools to represent the design of selected visualisations
- use appropriate software and select and apply functions, formats and conventions to manipulate the extracted data to create data visualisations
- select appropriate techniques and apply criteria to determine the extent to which data visualisations meet users’ needs.
Interesting Data Vis Stories / Examples
Interesting Data Vis Stories / Examples
- Joy Division's album Unknown Pleasures cover art
- Harry Potter Visualizations
- Spells
- "Agentive" Actions
- jupyter notebook of vis (CSIRO - TODO fix printing!)
- Visualization of Music / Lyrics
- ABC Data Journalism & Interactive Digital Storytelling
Collections of good visualizations
Collections of good visualizations
- Great Data Vis Examples (blog.hubspot)
- Best Data Vis 2015 [Click on headings to see animated/interactive versions)
- Information is Beautiful
- XKCD Webcomics
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