University of Technology Sydney

42097 Advanced Data Visualisation

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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

In this subject, students develop the ability to visualise data sets using more complex and sophisticated techniques. Data sets that include time-series, textual and spatio-temporal data are explored and appropriate visualisation methods are developed with an emphasis on making the data coherent and legible for particular users. The ways that data visualisations can be made interactive, and the implications that interactivity has for visualisation designers are considered through practical work.

Subject learning objectives (SLOs)

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

1. Design interactive data visualisation techniques. (C.1)
2. Apply interactive data visualisation techniques. (D.1)

Course intended learning outcomes (CILOs)

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

  • Design Oriented: FEIT graduates apply problem solving, design thinking and decision-making methodologies in new contexts or to novel problems, to explore, test, analyse and synthesise complex ideas, theories or concepts. (C.1)
  • 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. Chart-based visualisations of complex data types
  2. Hierarchical data visualisations & high-dimensional visualisation techniques
  3. Interactive data visualisations and user-centred design

Visualising changing data and comparing data sets.

Assessment

Assessment task 1: Create an interactive data visualisation of a dataset that includes a range of complex data types

Intent:

Develop the ability to create interactive data 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):

C.1 and 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.