Open AccessTools for visualizing data: a review
Author(s) -
Jim Ridgway,
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James Nicholson,
Pedro Campos,
Sónia Teixeira,
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Publication year - 2018
Language(s) - English
Resource type - Conference proceedings
DOI - 10.52041/srap.17201
Subject(s) - computer science , variety (cybernetics) , data science , data exploration , visualization , data visualization , raw data , software , curriculum , human–computer interaction , world wide web , data mining , artificial intelligence , programming language , psychology , pedagogy
There has been an explosion in the range of tools available for presenting data, many of which are available to support statistics teaching. These include tools that allow users to ‘drag and drop’ data sets (e.g. RAW), tools designed to display particular data sets (e.g. eXplorer) and software libraries (e.g. D3.js). We report on a review of visualisation tools, where we have described the sorts of visualisations facilitated by each tool, along with features such as ease of use and cost. Data visualisations can give new insights into complex data sets, and can be used directly to reshape teaching. We map out teaching opportunities facilitated by different tool types. Understanding novel data visualisations has become an important element of statistical literacy, and so curricula should expose students to a wide variety of examples.