Courses & Units

Making Data Work for Us - Simplifying a Complex World XBR215



What happens to you if your ancestors have a terrible start in life? Could it influence your future livelihood and health?  How is climate change affecting your favourite surf break or fishing spot? Will massive green-blobs of algae take over the coastal ocean? The answers to these questions are at the tip of everyone’s fingers, but how do we generate the knowledge to answer these questions?  Data science is rapidly growing as a new way to generate knowledge, rivalling the scientific technique of hypothesis testing & experimentation. Huge, publicaly accessible data sets are becoming increasingly available, and understanding how to gather, process, and visualize this data to generate new knowledge is a vital skill necessary for graduates across all disciplines. Utilizing concepts of computation thinking and spanning a variety of case studies in marine science, engineering, logistics and management, social history and archaeology, students will learn how to unlock insights from some of the world’s greatest data repositories and archives.  The unit widens the understanding of the complex world of data acquisition, processing, interpretation, and visualization, utilizing modern, effective, yet simple, computer-intensive procedures for visualization and analysis. Within the unit, students will familiarize themselves with how to work and interact with high-level computational environments, such as MATLAB, to access data repositories and generate new knowledge. Students will also explore how the spatial and sensory experiences of data visualizations can affect learning affect learning and debate the ethical considerations of data sharing. The unit is not meant to teach a programming language, but provide approaches to using programming recipes and tools to examine different data domains in different interdisciplinary settings in order to begin to address complexity of real world interdisciplinary problems.


Unit name Making Data Work for Us - Simplifying a Complex World
Unit code XBR215
Credit points 12.5
Faculty/School College of Sciences and Engineering
Institute for Marine & Antarctic Studies
Discipline Education|History and Classics|National Centre for Maritime Engineering and Hydrodynamics|Maritime and Logistics Management|Information & Communication Technology|Mathematics|Ecology and Biodiversity

Andrew Fischer

Teaching staff

Andrew Fluck, Hamish Maxwell-Stewart, Nataliya Nikolova, Kiril Tenekedjiev, Anya Reading, Saurabh Garg

Level Intermediate
Available as student elective? No
Breadth Unit? Yes


Location Study period Attendance options Available to
Launceston Semester 2 On-Campus Off-Campus International International Domestic Domestic


International students
Domestic students

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Key Dates

Study Period Start date Census date WW date End date
Semester 2 13/7/2020 10/8/2020 18/10/2020 18/10/2020

* The Final WW Date is the final date from which you can withdraw from the unit without academic penalty, however you will still incur a financial liability (see withdrawal dates explained for more information).

About Census Dates

Learning Outcomes

On completion of this unit, you will be able to:

  1. On completing this unit, you will be to acquire, process, interpret and visualize large data sets from the web.
  2. On completing this unit, you will have learned how to use a programming language and will be able to implement supplied recipes and algorithms to analyze large data sets.
  3. On completing this unit you will be able to begin to address complex, real-world problems using computational thinking approaches and programming tools.


Field of Education Commencing Student Contribution 1 Grandfathered Student Contribution 1 Approved Pathway Course Student Contribution 2 Domestic Full Fee
not applicable

1 Please refer here more information on student contribution amounts.
2 Information on eligibility and Approved Pathway courses can be found here
If you have any questions in relation to the fees, please contact UConnect or more information is available on StudyAssist.

Please note: international students should refer to this page to get an indicative course cost.


Teaching Pattern

On-line (equivalent of 60 min lecture weekly and 3-hr practical)


Assessment 1: Quizzes and online discussion – 20% - Students participate in online quizzes and discussion groups to solve coding challenges related to the basic principles covered in the lectures. Project 1 – 15% - Design and complete a project to demonstrate the skills learned. Components of the project should include accessing data from a data repository, some sort of the data analysis and a visualization of the data , Project 2 – 15% - Project 2 will focus on data visualization and analysis using the programming skills learned in the first seven weeks and the data accessed from Project 1, Final Project – 50% - Design and complete a project. Components of the project should include accessing data from a data repository, some sort of the data analysis and a visualization of the data. Students should submit a (~1000 word) description of their project, the code used to complete their projects, plus an audio-visual presentation.

TimetableView the lecture timetable | View the full unit timetable



Computational Thinking for the Modern Problem Solver (Chapman & Hall/CRC Textbooks in Computing) 1st Edition

The Visual Display of Quantitative Information” by Edward R.Tufte

Storytelling With Data: A Data Visualization Guide for Business Professionals” by Cole Nussbaumer Knaflic

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