AH5803 Digital Tools: Visualisation, Interpretation and Analysis

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

Enrolment is limited to online PGT programmes.

Planned timetable

Not Applicable

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

Module coordinator

Dr E N Savage

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

Module Staff

Dr Emily Savage; Dr Natalia Sassu Suarez Ferri; Dr Billy Rough

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

Module description

This module will study the key digital tools available to art historians and the ways in which they can facilitate our analysis, interpretation, and visualisation of art historical data. What decisions do we take when creating, organising, manipulating, and sharing data? How can institutions and researchers use digital tools to increase accessibility, inclusivity, and knowledge? How do three-dimensional images and immersive experiences assist research, and what new engagement possibilities do they present for cultural heritage institutions? In this course, students will be introduced to a variety of tools and techniques, including: data and text mining; data visualization; mapping and network analysis; 3D modelling; virtual reality; computer vision; gaming; and crowdsourcing. The module will be structured into set topics. Each topic will comprise video content, set readings, and asynchronous reflective, analytical, and practical tasks.

Assessment pattern

100% Coursework

Re-assessment

100% Coursework

Learning and teaching methods and delivery

Weekly contact

There are no fixed weekly contact hours, but students should expect to engage in asynchronous discussions. There will be opportunities for synchronous one-to-one and group discussions during the module. Students should take note of the overall study hours expected when planning their learning.

Scheduled learning hours

13

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

Guided independent study hours

130

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

Intended learning outcomes

  • explain the importance of metadata standardisation and open source sharing of data
  • identify the potential sources of human bias in the creation, manipulation, and interpretation of data
  • demonstrate competence with a variety of digital tools and platforms to visualise and interpret data
  • discuss the use of machine learning in art historical research, its possibilities and limitations
  • critically examine how digital projects facilitate or limit accessibility, inclusivity, and knowledge sharing among researchers and the public

AH5803 Digital Tools: Visualisation, Interpretation and Analysis

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

Enrolment is limited to online PGT programmes.

Planned timetable

Not Applicable

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

Module coordinator

Dr E N Savage

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

Module Staff

Dr Emily Savage; Dr Natalia Sassu Suarez Ferri; Dr Billy Rough

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

Module description

This module will study the key digital tools available to art historians and the ways in which they can facilitate our analysis, interpretation, and visualisation of art historical data. What decisions do we take when creating, organising, manipulating, and sharing data? How can institutions and researchers use digital tools to increase accessibility, inclusivity, and knowledge? How do three-dimensional images and immersive experiences assist research, and what new engagement possibilities do they present for cultural heritage institutions? In this course, students will be introduced to a variety of tools and techniques, including: data and text mining; data visualization; mapping and network analysis; 3D modelling; virtual reality; computer vision; gaming; and crowdsourcing. The module will be structured into set topics. Each topic will comprise video content, set readings, and asynchronous reflective, analytical, and practical tasks.

Assessment pattern

100% Coursework

Re-assessment

100% Coursework

Learning and teaching methods and delivery

Weekly contact

There are no fixed weekly contact hours, but students should expect to engage in asynchronous discussions. There will be opportunities for synchronous one-to-one and group discussions during the module. Students should take note of the overall study hours expected when planning their learning.

Scheduled learning hours

13

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

Guided independent study hours

130

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

Intended learning outcomes

  • explain the importance of metadata standardisation and open source sharing of data
  • identify the potential sources of human bias in the creation, manipulation, and interpretation of data
  • demonstrate competence with a variety of digital tools and platforms to visualise and interpret data
  • discuss the use of machine learning in art historical research, its possibilities and limitations
  • critically examine how digital projects facilitate or limit accessibility, inclusivity, and knowledge sharing among researchers and the public