Digital Media & Information Studies MA

Data Analysis, Visualisation and Communication INFOST4003

  • Academic Session: 2023-24
  • School: School of Humanities
  • Credits: 20
  • Level: Level 4 (SCQF level 10)
  • Typically Offered: Either Semester 1 or Semester 2
  • Available to Visiting Students: Yes

Short Description

Data science is no longer only the domain of computer scientists and engineers. Given the increasing amount of data created and captured every day, it is important for students in the humanities to develop the basic skills to analyse, interpret, and communicate a variety of data in digital format. This course seeks to develop these skills by providing an introduction to different types of data, and approaches to analyse and interpret them in electronic form.


1x1hr lecture and 1x1hr seminar or lab session per week as scheduled in MyCampus. This is one of the Honours options in Information Studies and may not run every year. The options that are running this session are available in MyCampus.

Excluded Courses

ARTMED4036 - Data Analysis, Visualisation and Communication

INFOSTUD4004 - Data Analysis, Visualisation and Communication 




Project output: The students have to work on a data science project and deliver the output at the end of Week 11. This output will consist of a data set created or developed by the student, analysed and visualised using appropriate tools and methods. - 50%

Report (2000 words) - 50%

Main Assessment In: April/May

Are reassessment opportunities available for all summative assessments? Not applicable for Honours courses

Reassessments are normally available for all courses, except those which contribute to the Honours classification. Where, exceptionally, reassessment on Honours courses is required to satisfy professional/accreditation requirements, only the overall course grade achieved at the first attempt will contribute to the Honours classification. For non-Honours courses, students are offered reassessment in all or any of the components of assessment if the satisfactory (threshold) grade for the overall course is not achieved at the first attempt. This is normally grade D3 for undergraduate students and grade C3 for postgraduate students. Exceptionally it may not be possible to offer reassessment of some coursework items, in which case the mark achieved at the first attempt will be counted towards the final course grade. Any such exceptions for this course are described below. 

Course Aims

This course aims to:

■ Deliver an introduction to the field of data science

■ Provide a grounding on the main principles of data and best practice of data analysis

■ Explain methods for data analysis, visualisation methods, and its use for communication

■ Emphasis the research potentials of data analysis in the field of information and communication studies

■ Introduce standard techniques for analysing, visualising and communicating data

■ Analyse how data analysis methods are used in the humanities and how this can change the way in which scholars use and interact with data

Intended Learning Outcomes of Course

By the end of this course students will be able to:

■ Identify relevant research questions and assess how data analysis can help answer these.

■ Assess how data analysis can change the way in which data is used and analysed in the humanities

■ Be proficient in exploring, analysing, manipulating, interpreting and visualising data using data science techniques, software and technologies to make sense of data

■ Design and apply appropriate methods to visualise information based on data analysis

■ Recognise and use standards and best practice generally accepted by the research community.

■ Develop, test, justify and deliver methods to communicate research outcomes based on the analysis of data

Minimum Requirement for Award of Credits

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.