University of Technology Sydney

42096 Data Visualisation Foundations

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Subject handbook information prior to 2024 is available in the Archives.

UTS: Information Technology: Computer Science
Credit points: 2 cp
Result type: Grade and marks

Requisite(s): 32146 Data Visualisation and Visual Analytics

Description

This subject introduces key concepts in data visualisation and visual analytics. Students develop the ability to recognise and apply a range of different data visualisation techniques in different contexts. They learn how to manage and prepare data for visualisation and to compare and evaluate specific visualisation methods.

Subject learning objectives (SLOs)

Upon successful completion of this subject students should be able to:

1. Recognise and compare a range of standard data visualisation techniques. (D.1)
2. Be able to apply a range of standard data visualisation techniques. (D.2)

Course intended learning outcomes (CILOs)

This subject also contributes specifically to the development of the following Course Intended Learning Outcomes (CILOs):

  • Technically Proficient: FEIT graduates apply theoretical, conceptual, software and physical tools and advanced discipline knowledge to research, evaluate and predict future performance of systems characterised by complexity. (D.1)

Teaching and learning strategies

Microcredential presentation includes weekly synchronous one-hour online workshops facilitated by an expert UTS academic(s) supporting self-study and online (LMS) learning activities. Case studies of real-world organisations illustrate applications of data visualisation techniques. The workshop sessions focus on hands-on experience creating data visualisations guided by the real world case studies, and critically evaluating the results. Regular formative quizzes and questions throughout the semester will allow learners to gauge their progress.

Content (topics)

  1. Introduction to data visualisation: history, purpose & challenges
  2. Different kinds of data visualisation and their advantages and disadvantages
  3. Data collection, formatting and transformation for visualisation
  4. Comparing and evaluating data visualisations for particular purposes

Assessment

Assessment task 1: Compare and evaluate different visualisations of a data set

Intent:

Develop the ability to compare and evaluate different visualisations

Objective(s):

This assessment task addresses the following subject learning objectives (SLOs):

1 and 2

This assessment task contributes to the development of the following Course Intended Learning Outcomes (CILOs):

D.1

Type: Report
Groupwork: Individual
Weight: 100%
Length:

2,000 words

Minimum requirements

In order to pass the subject, a student must achieve an overall mark of 50% or more.