AOS1: Data analysis

Interesting Data Vis Stories / Examples

• Joy Division's album Unknown Pleasures cover art

  • Inspired what's now known as a "Joyplot" [1, 2]

• Harry Potter Visualizations

  • Spells

  • "Agentive" Actions

  • jupyter notebook of vis (CSIRO - TODO fix printing!)

• Visualization of Music / Lyrics

  • Why we really really really like repetition in music (The Pudding) (and Vox video)

  • SongSim

  • History of Rock and Roll

  • Google's Big Picture - Music Timeline

  • Current Wind - Global

• ABC Data Journalism & Interactive Digital Storytelling

  • North Korean Missile Range

  • Metadata - How your phone tracks your every move

  • Who really decides - 2016 Election

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

  • Top 5 Data Vis XKCDs

  • XKCD Data Visualized

• Covid and related Data Dashboards

  • https://nextstrain.org/

  • https://ncov2019.live/data (made by a high school student!)

  • https://covidlive.com.au/

Key knowledge

Data and information

• types and purposes of qualitative and quantitative data

• characteristics of data and information

• sources, methods and techniques for acquiring and referencing primary and secondary data and information

• interpretation of information for communication and decision making

• factors affecting the quality of data and information, such as accuracy, bias, integrity, relevance and reliability

• characteristics of data types and data structures relevant to selected software tools

• procedures for the legal and ethical collection and use of data and information, such as using consent forms

• techniques for protecting data and information from misuse, such as de-identifying personal data and the use of physical and software security controls

Approaches to problem solving

• structural characteristics of spreadsheets and databases, such as cells, fields, records and tables

• types and purposes of data visualisations suitable for educating, entertaining, informing and persuading audiences

• functional and non-functional requirements of solutions, constraints and scope

• design tools for representing the functionality and appearance of databases, spreadsheets and data visualisations, such as annotated diagrams and mock-ups

• formats and conventions suitable for databases, spreadsheets and data visualisations

• software functions and techniques for efficiently and effectively manipulating, validating and testing data to develop databases, spreadsheets and data visualisations

Interactions and impacts

• Australian Privacy Principles relating to the acquisition, management and communication of data and information including non-identification of individuals (Principle 2), information only being held for its primary purpose (Principle 6) and the security measures used to protect personal information (Principle 11)

• ethical issues arising from the acquisition, storage and use of data and information.

Key skills

• acquire and reference data and information from primary and secondary sources, taking into account legal and ethical considerations

• analyse the selected data, and discuss the relationships and patterns identified

• interpret solution requirements, constraints and scope

• interpret designs using appropriate design tools to represent the functionality and appearance of databases, spreadsheets and data visualisations

• use software, and select and apply functions, formats, conventions, data validation and testing techniques to efficiently manipulate data and create data visualisations

• compare and interpret data visualisations.