Visualising Information – Data Journalism Workshop – Our plan

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Visualising Information – Data Journalism Workshop – Our plan

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tol-skoleni-2

školení běloruských novinářů pro Transitions On-Line

On Github tocit / tol-skoleni-2

Visualising Information

Data Journalism Workshop

Petr Kočí [@tocit] Marcel Šulek [@veproza]

http://ihned.cz/data

Prague, February 21 - 23, 2014

This presentation

http://ddj.pribehy.cz/prague

Slides from Vilnius

http://ddj.pribehy.cz/vilnius

I removed the book :)

Our plan

Friday

Why visualise data, brief history of data visualisation How we think about visualisation, best and worst practices, learning from mistakes Demo: Two examples of our day-to-day news visualisations - How and why did we make these? Not set in stone, let's improvise!

Saturday

Hands-on: Free tools for data visualisation: Google Charts, Google Fusion Tables, Datawrapper, infogr.am, Wordle, Timeline.js, Timeline Setter “Program or be programmed”: Disadvantages of free tools Hands-on: Visualising Data with R and R Studio Interactive Data Visualisation for the Web: Technology Fundamentals: HTML, CSS, JavaScript, SVG, D3.js Hands-on: Let's make a simple chart with D3.js

Sunday

Creating news maps for print and the web Hands-on: Free tools for on-line mapping_ Google Fusion Tables, QGIS, Google Geochart API Hands-on: Let's make a map with D3.js Workshop: Let's visualise together some data that matters to you and your readers!

It's not set in stone. Let's improvise and get our hands dirty with data!

Our Data Toolbox

Please download and install

Optional

Why visualise data?

"Data is structured information with potential for meaning."

Visualisations help us discover the meaning, understand it and communicate to others.

Raw data

Visualisation

History of Data Visualisation

John Snow

Cholera Map of London

Parking map of Prague

London Underground Map 1932

London Underground Map 1933

Minard's Map of Napoleon March

Edward Tufte's Principles of Visualisation

  • The representation of numbers, as physically measured on the surface of the graph itself, should be directly proportional to the numerical quantities represented.
  • Clear, detailed and thorough labeling should be used to defeat graphical distortion and ambiguity. Write out explanations of the data on the graph itself. Label important events in the data.
  • Show data variation, not design variation.
  • In time-series displays of money, deflated and standardized units of monetary measurement are nearly always better than nominal units.
  • The number of information carrying (variable) dimensions depicted should not exceed the number of dimensions in the data. Graphics must not quote data out of context.

Edward Tufte's Data/Ink Ratio

Above all else show data. Maximize the data-ink ratio. Erase non-data-ink. Erase redundant data-ink. Revise and edit.

Interactive Visualisations Principle

Overview Zoom Explore

Overview - Zoom - Explore Example

Choose the Right Chart Type

The Problem with Pie Charts

A Good Use of Pie Chart

Less Common Chart Types Worth Considering

Sanity Check!