More Related Content
Similar to Infographics & Data Visualisation
Infographics & Data Visualisation
- 1. INTRODUCTION TOInfographics& DataVisualisationTrisnadiKurniawan / WEB DESIGNERDelivering Awesome Web Applications
- 2. About TrisnadiSSW WebDesignerUser Experience & Interface DesignProjectsASP.NET, SharePoint, DotNetNukeClientsWorleyParsons, NineMSN, Microsoft, Energy Australia
- 4. 80% of thebrain is dedicated to visual processing
- 5. Visual processing isnot new, its part of our history
- 6. Written language originatedfrom drawing and sketching
- 14.
- 15.
- 16.
- 17. visual representations ofinformation, data or knowledge often used to support information, strengthen it and present it within a sensitive context.infographics
- 24. visually display measuredquantitiesby means of the combined use of points, lines, a coordinate system, numbers, symbols, words, shading and colour.Data Visualisation
- 25. More than simplytranslating a table of data into a visualisation
- 26.
- 28. ChecklistShow the dataAccurateDon’tdistort the dataMake large data sets coherentServe a clear purposeReveal the data at different levelsOverview vs DetailedEngagingEncourage viewer to compare different pieces of data
- 29.
- 30.
- 32. Revealing the Data8Preattentive Variables
- 33. “Certain visual featuresoperate ‘preattentively:’ they convey information before the viewer pays conscious attention”JeniferTidwell
- 42.
- 43. Find all numbersgreater than 1.0
- 44. Find all numbersgreater than 1.0
- 49. Bad Exampleswhen infographicsis less-than-helpful
- 52.
- 53.
- 54.
- 56. Looking ForwardDescry (MIXLab)http://www.visitmix.com/Lab/descryGapminderhttp://www.gapminder.org/Google Visualisationhttp://code.google.com/apis/ajax/playground/?type=visualizationDigg Labshttp://labs.digg.com/stack/
- 57. IntroductionOverview, Definition, History,ExamplesData Visualisation PatternsBar charts, Line graphs, Stacked area charts, Pie charts, Ring charts, Scatterplots, Bubble chartsPreattentive VariablesColour hue, Brightness, Saturation, Texture, Position, Orientation, Size, ShapeUser InteractionStatic, Animated, Interactive, Direct ManipulationIn Summary
- 58.
- 59. ReferencesDesigning Interfaces byJenifer Tidwellhttp://designinginterfaces.comPicturing Excess by Chris Jordanhttp://www.chrisjordan.comVisualising Databy Joel Laumans http://piksels.comMIX Descryhttp://www.visitmix.com/Lab/descryData Visualization: Modern Approach by Smashing Magazinehttp://www.smashingmagazine.com/2007/08/02/data-visualization-modern-approaches/
- 60. Thank You!Gateway CourtSuite 10 81 - 91 Military Road Neutral Bay, Sydney NSW 2089 AUSTRALIA ABN: 21 069 371 900 Phone: + 61 2 9953 3000 Fax: + 61 2 9953 3105 [email protected] Delivering Awesome Web Applications
Editor's Notes
- #5 Trivia: this day in 1633 Galileo faced court over his heliocentric research
- #7 Depicts one million plastic cups, the number used on airline flights in the US every six hours.
- #9 40 million paper cups a day
- #10 410,000 (15 minutes)
- #17 Infographics is everywhereRoadway sign,Subway map,Brochure,Product manual,Instructions on prescription bottle,Assembly guide
- #24 The main goal of data visualization is its ability to visualize data, communicating information clearly and effectively. It doesn’t mean that data visualization needs to look boring to be functional or extremely sophisticated to look beautiful.
- #27 http://www.traumkrieger.de/virtualwater/
- #30 There are countless possibilities of how to visualize data; but there are many design patterns which are proven to be effective for specific types of data. The following section provides examples of data visualization patterns and a short rationale for when to use them.Independent quantities (bar charts)Comparing the values of independent variablesContinuous quantities (line graphs & stacked area)For data that is continuous, for example when visualizing data over a period of time.Proportions (pie & ring charts)Proportions are used when the data represents parts of a whole.Hierarchies (tree diagrams)Used when the data has a strict hierarchy that needs to be communicated.Networks (diagram map)Network visualizations are used when the most important feature of the visualization is to show which data is connected to each other, as opposed to how.CorrelationsThese are used when each piece of data has two quantifiable variables which can be plotted on a grid.CartographicFor data that is relevant to specific locations or regions which can be plotted on a map.There are more. Don’t limit your scope on these! (see next example)
- #33 “Certain visual features operate ‘preattentively:’ they convey information before the viewer pays conscious attention”
- #43 There is no visual aid to help us find the values greater than 1.0, forcing us to read all of the data and understand it. Now look at the following table.
- #54 StaticThe data visualization does not change over time, and offers no user interaction.AnimatedThe data visualization changes over time - using time as another dimension or variable.InteractiveThe user can interact with the visualization by altering what data is viewed and / or how it is viewed - however the results of interactions are not immediately visible.Direct manipulationThe user can interact with the visualization by altering what data is viewed and / or how it is viewed - and the result of all interactions are immediately visible.