Original Seeing Data Research

Seeing Data is a research project which aims to understand how people make sense of data visualisations. There is more and more data around us, and data is increasingly used to explain our social world. One of the main ways that people get access to data (big and small) is through visualisations, like those on the pages of this website. Visualisations are visual representations of data. They are used to help people make sense of data or to allow people to explore data. They take the form of graphs, charts and other more complex or less familiar diagrams.

Visualisations appear in newspapers, on television (especially in documentaries and news programmes), and on the Internet in social media like Facebook. What we don’t know is how people make sense of visualisations. How do we interact with them? How do we interpret them? Do they help us make sense of data? Do different people interact with visualisations in different ways? What messages do we take away from visualisations? On the Seeing Data project we have been exploring these questions and finding out what skills people need to help them to make sense of visualisations. The video at the bottom of this page tells you more about our project.

Our aims on Seeing Data have been:

Aims for the general public

  • To help people to develop the skills they need to make sense of data visualisations (what we call ‘visualisation literacy’).

Aims for data visualisation professionals

  • To contribute to data visualisation practice by sharing understanding of how data visualisations are received by the general public;
  • To identify the particular challenges in visualising big data (rather than small) data sets;
  • To identify whether and how we can define and measure the ‘effectiveness’ of data visualisations.

Research aims

  • To enhance understanding of engagement with data visualisations;
  • To ask critical questions and contribute knowledge about engagement with data visualisations to academic disciplines concerned with the relationship between data and society.

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