University of Canberra, 21 & 28 February 2015

Data visualization for researchers

by Jaume Nualart

This seminar is organized by Joëlle Vandermensbrugghe (Graduate Research Office) and it is addressed to PhD students, mainly

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what are we going to do? Why data visualization

Welcome & presentation

Why data visualization?

Data visualization is a mutidisciplinary field:

Practice: answer the question "Who we are?"


mining, formats and transformations

Data formats

Data transformations


Examples, examples & examples

The process of creating data visualizations

Data scientist skills

Functions of data visualization:

Dealing with design

Several concepts

Preparing your data visualizations for 2nd session

Describe your data

Describe the intention of your data

Conversation about best visualization options

Describe tasks to be done during the week to prepare the data.

2nd session:
practice & practice Feb 28st 2015

Next week we are going to put all this theoretical in practice

  • Defining goals of the visualization:
    • Task oriented: do it solve a task or several? Describe them
    • Storitelling oriented: which is the history and context of your discurse?
    • Tool oriented: to be used in specific contexts. To use for a specific dataset that will be shown multiple times.
    • what else?
  • 2.1 Defining the data
    • Dataset description: number of records, data-type, fields, distinct values of fields, rage,...
  • 2.1 Choice of tools
  • 2.2 Data formatting
    • Formating data tools: desktop software (google refine, tableau public, etc), spreadsheets, scripts
    • Data insights: mining, patterns, trends, irregularities
  • 2.3 Building visualizations
    • see 2,1
  • 2.4 Publishing visualizations
    • Online, interective, animated images
    • Static images
    • Printing
    • Reuse of visualization elements integrated in other projects

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