SD5813 Advanced Data Visualisation

Academic year

2024 to 2025 Semester 1

Further information on which modules are specific to your programme.

Key module information

SCOTCAT credits

15

The Scottish Credit Accumulation and Transfer (SCOTCAT) system allows credits gained in Scotland to be transferred between institutions. The number of credits associated with a module gives an indication of the amount of learning effort required by the learner. European Credit Transfer System (ECTS) credits are half the value of SCOTCAT credits.

SCQF level

SCQF level 11

The Scottish Credit and Qualifications Framework (SCQF) provides an indication of the complexity of award qualifications and associated learning and operates on an ascending numeric scale from Levels 1-12 with SCQF Level 10 equating to a Scottish undergraduate Honours degree.

Availability restrictions

Available only to students studying the PG Cert, PG Dip, and MSc in Data Literacy for Social and Environmental Justice

Planned timetable

Not Applicable

This information is given as indicative. Timetable may change at short notice depending on room availability.

Module coordinator

Dr T C Mendo

This information is given as indicative. Staff involved in a module may change at short notice depending on availability and circumstances.

Module Staff

Dr L Cole; Dr T Mendo; Dr E Olamijuwon

This information is given as indicative. Staff involved in a module may change at short notice depending on availability and circumstances.

Module description

Building on “Welcome to Data” and “Statistical Foundations,” this module will provide students with an understanding of important concepts related to data visualization, including how humans perceive data and why certain techniques can therefore enhance the effectiveness of a visualization. They will also learn more advanced skills in creating well-designed graphics with free, open-source statistical analysis software (e.g., R/RStudio). Note this is distinct from “Visuals for Policies and Publics” because it is data visualization for statistical analyses. Students do not have to have taken SD5512 Quantitative Methods, but if students intend to take both, we recommend SD5512 prior to this module. While the important concepts are consistent and we can use the same analytical software, this module will have two pathways managed through the virtual learning environment – social science vs. environmental science – to ensure students engage with data that are appropriate for their subfield.

Relationship to other modules

Pre-requisites

IN ORDER TO TAKE THIS MODULE YOU MUST TAKE OR HAVE TAKEN SD5510 AND SD5511 OR HAVE PERMISSION FROM THE PROGRAMME DIRECTOR

Assessment pattern

100% Coursework

Re-assessment

100% Coursework

Learning and teaching methods and delivery

Weekly contact

This module includes 5 1-hour synchronous tutorial sessions and at least 5 hours of pre-recorded content (e.g., lectures). Students should consider the amount of independent study time this module involves when planning their learning.

Scheduled learning hours

0

The number of compulsory student:staff contact hours over the period of the module.

Guided independent study hours

145

The number of hours that students are expected to invest in independent study over the period of the module.

Intended learning outcomes

  • Explain key foundational concepts in humans' perception of data;
  • Describe best practices approaches for data visualization, including with regard to accessibility;
  • Plot a range of different visualizations for both discrete and continuous data;
  • Understand and apply techniques to create data visualizations that communicate messages clearly and with impact;
  • Develop enhanced capacity to use state-of-the-art tools to build useful visualizations for different types of data sets and application scenarios.

SD5813 Advanced Data Visualisation

Academic year

2024 to 2025 Semester 2

Further information on which modules are specific to your programme.

Key module information

SCOTCAT credits

15

The Scottish Credit Accumulation and Transfer (SCOTCAT) system allows credits gained in Scotland to be transferred between institutions. The number of credits associated with a module gives an indication of the amount of learning effort required by the learner. European Credit Transfer System (ECTS) credits are half the value of SCOTCAT credits.

SCQF level

SCQF level 11

The Scottish Credit and Qualifications Framework (SCQF) provides an indication of the complexity of award qualifications and associated learning and operates on an ascending numeric scale from Levels 1-12 with SCQF Level 10 equating to a Scottish undergraduate Honours degree.

Availability restrictions

Available only to students studying the PG Cert, PG Dip, and MSc in Data Literacy for Social and Environmental Justice

Planned timetable

Not Applicable

This information is given as indicative. Timetable may change at short notice depending on room availability.

Module coordinator

Dr T C Mendo

This information is given as indicative. Staff involved in a module may change at short notice depending on availability and circumstances.

Module Staff

Dr L Cole; Dr T Mendo; Dr E Olamijuwon

This information is given as indicative. Staff involved in a module may change at short notice depending on availability and circumstances.

Module description

Building on “Welcome to Data” and “Statistical Foundations,” this module will provide students with an understanding of important concepts related to data visualization, including how humans perceive data and why certain techniques can therefore enhance the effectiveness of a visualization. They will also learn more advanced skills in creating well-designed graphics with free, open-source statistical analysis software (e.g., R/RStudio). Note this is distinct from “Visuals for Policies and Publics” because it is data visualization for statistical analyses. Students do not have to have taken SD5512 Quantitative Methods, but if students intend to take both, we recommend SD5512 prior to this module. While the important concepts are consistent and we can use the same analytical software, this module will have two pathways managed through the virtual learning environment – social science vs. environmental science – to ensure students engage with data that are appropriate for their subfield.

Relationship to other modules

Pre-requisites

IN ORDER TO TAKE THIS MODULE YOU MUST TAKE OR HAVE TAKEN SD5510 AND SD5511 OR HAVE PERMISSION FROM THE PROGRAMME DIRECTOR

Assessment pattern

100% Coursework

Re-assessment

100% Coursework

Learning and teaching methods and delivery

Weekly contact

This module includes 5 1-hour synchronous tutorial sessions and at least 5 hours of pre-recorded content (e.g., lectures). Students should consider the amount of independent study time this module involves when planning their learning.

Scheduled learning hours

0

The number of compulsory student:staff contact hours over the period of the module.

Guided independent study hours

145

The number of hours that students are expected to invest in independent study over the period of the module.

Intended learning outcomes

  • Explain key foundational concepts in humans' perception of data;
  • Describe best practices approaches for data visualization, including with regard to accessibility;
  • Plot a range of different visualizations for both discrete and continuous data;
  • Understand and apply techniques to create data visualizations that communicate messages clearly and with impact;
  • Develop enhanced capacity to use state-of-the-art tools to build useful visualizations for different types of data sets and application scenarios.