ETC5512: Wild Caught Data

Data can be obtained from many sources. It may be generated via experiments, collected from observational studies or surveys, obtained via sampling, or recorded using sensors.

Each type of data has its own characteristics that affect the analysis tools we use. Very large data sets come with their own challenges and require some database skills.

This unit will equip you with the tools to understand and use different sources of data. Open data sources will be emphasised.

Learning objectives

  1. Understand the definitions, allowed usage, digital identification and licensing of open data

  2. Know about common open data sources, how they are used and effectively search for new sources

  3. Explain the differences between data collection methods and the limitations for data analysis

  4. Work with the range of different data formats of open data, including APIs

  5. Understand ethical constraints and privacy limits when working with open data

  6. Recognise the components of effective curation needed for open data.

Teachers

  • Kate Saunders - Lecturer and Chief Examiner
  • Krisanat Anukarnsakulchularp - Tutor
  • Maliny Po - Tutor

Weekly schedule

  • Seminar: Monday 2 pm - 4 pm
  • Drop in & practice session: Monday 10 - 11 pm (zoom)
  • Refer to your timetable for your tutorial time
  • Refer to Moodle for room locations and zoom links

Consults

  • Kate: Monday 11 - 12 pm. (Room 64, Level 5, Building H, Caulfield Campus or see Moodle for zoom link)
  • Kris: Tuesday 2 - 3:30 pm
    (Room 232A Building 6, 29 Ancora Imparo Way Clayton Campus)
  • Maliny: Wednesday 3:30 - 5 pm
    (Room 232A Building 6, 29 Ancora Imparo Way Clayton Campus)

Schedule

Week Date Topic Tutorial Solution
1 03 Mar Open data: definitions, sources and examples
2 10 Mar Introduction to data collection methods
3 17 Mar Case Study: US airline traffic
4 24 Mar Case Study: Australian census
5 31 Mar Case Study: Australian election data
6 07 Apr Case Study: Combining census and election data
7 14 Apr Case Study: PD model and credit risk
21 Apr Mid-semester break
9 28 Apr Case Study: Data ethics and privacy
10 05 May Case Study: TBC
11 12 May Case Study: Introduction to webscraping
12 19 May Revision: Proper care and feeding of wild caught data