An introduction to data visualisation using administrative data

Date:

25/07/2024 - 26/07/2024

Organised by:

Swansea University

Presenter:

Rowena Bailey

Level:

Entry (no or almost no prior knowledge)

Contact:

Christopher Roberts
DataciseOpenLearning@Swansea.ac.uk

Map:

View in Google Maps  (SA2 8PP)

Venue:

Data Science Building, Swansea University, Singleton Campus, Singleton Park, Swansea

Description:

Course description

This course teaches learners the fundamental principles of approaching data visualisation and illustrates the techniques that enable effective communication using visual representations of data. The course will focus on key aspects of the design processes, drawing on expertise from a community of contemporary experts in this field and providing an overview of best practices and industry standards. The course is highly interactive, with input elicited throughout to illustrate the importance of communicating with others when developing design ideas. This training course covers:

  • Fundamental principles of data visualisation: Learners will learn the foundational concepts of data visualisation and understand the principles behind effectively communicating information through visual representations.
  • Techniques for effective communication: This course will cover various methods for communicating data effectively through visuals. This could include understanding how to choose appropriate visualisations for different data types and how to enhance clarity and impact.
  • Key aspects of design processes: Learners will gain insights into the key steps involved in the design process for data visualisation. This might include understanding how to conceptualise visualisations and refining visualisations based on feedback.
  • Overview of best practices and industry standards: This course will draw on the expertise of contemporary experts in data visualisations. Learners will be introduced to data visualisation best practices and industry standards. providing an overview of current trends. These could include aspects such as accessibility and integrity.
  • Highly interactive learning: This course emphasises interactivity, with opportunities for Learners to engage actively throughout the learning process. This could involve hands-on exercises, group discussions, and real-world case studies.
  • Importance of collaboration in design: Emphasis will be placed on the importance of collaboration and communication when developing design ideas. This recognises that effective data visualisation often involves input from multiple stakeholders and disciplines.

 

Learning mode

This course will be delivered in person over two days.

The Datacise online learning platform will provide additional resources and teaching materials, such as recommended reading, online tutorials, group discussions, and informal Q&A. This highly interactive course also allows learners to ask questions and discuss topics related to their current work or projects.

Assignment 1: Develop a brief (300-500 words) and complete a checklist of specifications for a visualisation proposal (can be based on the learner’s work or using case studies presented in the course) to be submitted at the end of the first day.

Assignment 2: Draft a design using the developed brief as a case study and a short presentation (oral) to the group to describe the ideas developed to the group.

 

Who should attend?

This course is suitable for those who want to learn how to use data visualisation tools and improve communication skills using graphical representations of data.

  • PhD students
  • Researchers in any domain
  • Analysts
  • Communication officers

 

Skills area and competencies

Data science skills framework: Skill areas and competencies

Skill areas:

  • Problem definition and communication with stakeholders
  • Problem solving, analysis, statistical modelling, visualisation

 

Skill competencies:

  • Problem definition and communication with stakeholders
    • Identify and elicit project requirements.
    • Determine success criteria and frame these in the context of the business.
    • Clearly articulate the problem statement.
    • Identify and critically evaluate assumptions.
    • Recognise and quantify biases and identify solutions to manage and mitigate these.
    • Assess risk.
  • Relationship management
    • Communication in an effective manner for diverse audiences, including technical colleagues, subject matter experts and leadership.
    • Effectively manage the expectations of diverse stakeholders with conflicting priorities to mediate equitable solutions.
    • Use relevant communication techniques (written, oral or visual), appropriate for the audience
    • Build appropriate and effective business relationships.
    • Show experience in human factors considerations with respect to data-driven solutions.
  • Data analysis and model building
    • Adopt appropriate method to visualise data and communicate complex findings.

 

Learning outcomes

This course aims to teach students a framework for designing and developing good data visualisations, critically appraise design ideas, and apply practical knowledge to identify a design brief’s key features.

  1. Explain the fundamental principles of data visualisation and the underlying purpose of using graphical representations of data
  2. Understand the power of visual data representations to support communication strategies.
  3. Objectively evaluate the success of visualisations within their research domain
  4. Learn how to make good design choices in the context of project-specific constraints and requirements.
  5. Experience the design process, share creative ideas with others and learn how to elicit feedback.

 

Transferrable skills

  • Creative thinking
  • Objective appraisal of success
  • Communication
  • Teamwork

 

Schedule

DAY 1: Introduction to key concepts and framework for evaluation

  1. Framework for critical appraisal of visualisations
  2. Defining the purpose of a visualisation
  3. Developing a design brief

 

DAY 2: Overview of the implementation process

  1. Understanding our data
  2. The function of charts
  3. An introduction to colour theory
  4. Composing a visual solution

 

Cost:

PhD student or Administrative Data Research Wales core-funded staff or SAIL Databank TRE users (UK and worldwide): £650.00 per delegate UK non-commercial organisation: £850.00 per delegate UK commercial organisation: £1,050.00 per delegate

Website and registration:

Region:

Wales

Keywords:

Data Visualisation, Data Visualisation, Administrative Data

Related publications and presentations:

Data Visualisation

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