Data Visualization and Journalism Workshop: Many Eyes

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Presentation slides from the 1st meeting of the Data Visualization and Journalism Working Group at UW-Madison J-school. Workshop on the tool Many Eyes.


<p>DATA(VIS) JOURNALISM-Working with Many Eyes</p> <p>Nakho Kim ( Dec 2011</p> <p>Short Recap (Roughly) 4-step procedure Plan: have a story to tell Collect: choose data Process: cleanup / analyze Show: choose visuals</p> <p> Pattern finding Difference Clustering Overlap Change over time</p> <p>Introducing Many Eyes Why Easy to use: menu-based. Somewhat interactive. Good enough for 'familiar' vis work. Good for trying out different types of vis on the spot.</p> <p> Limits Not very flexible. Cannot designate own colors Cannot use custom shapes Cannot modify others vis. Cannot</p> <p>(cont.) Runs as a Java applet Good for cross-browsing but needs plugin. Tries to become a kind of Youtube of datavis.</p> <p> Has been used for a variety of topics mar/17/visualise-data-trends</p> <p>Datasets Register to use your own dataset. Everything becomes public So keep a source for your dataset.</p> <p> Upload Open up as csv or spreadsheet, copy-paste your data directly. Check preview.</p> <p>Data Cleanup The first row is the header. Required. Only one.</p> <p> Units should be put in labels. Removed automatically from cells</p> <p> Use as little n/a as possible. Remove sums.</p> <p>Available VisFormat Scatterplot Matrix Chart Network Diagram Bar Chart Block Histogram Bubble Chart Line Graph Stack Graph Stack Graph for Categories Pie Chart Treemap Treemap for Comparisons Word Tree Tag Cloud Phrase Net Word Cloud Generator World Map ME category See relationships among data points See relationships among data points See relationships among data points Compare a set of values Compare a set of values Compare a set of values Track rises and falls over time Track rises and falls over time Track rises and falls over time See the parts of a whole See the parts of a whole See the parts of a whole Analyze a text Analyze a text Analyze a text Analyze a text See the world Good for Clustering Difference Clustering Difference Difference Difference Change over time Change over time Change over time Difference Difference Difference Clustering Clustering Clustering Clustering Overlap (as of Dec 11)</p> <p>Scatterplot Good for: correlation Column Data Format 1 Label 3 values : x, y, size</p> <p>Matrix Chart Good for: many comparisons at once Draws a matrix of multiple bar or pie charts</p> <p> Format 2 Labels (x, y) or 3 Labels (x,y, color) 1+ values</p> <p>Network Diagram Format: 2 values: from, to.</p> <p> Better done w/ Gephi, NodeXL, TouchGraph.</p> <p>Bar Chart Format 1 label. 1+value(s)</p> <p>Block Histogram Good for: Distribution Interface However, can't designate order</p> <p> Format 1 label 1 value</p> <p>Bubble Chart Good for Comparing many data at the same time. But colors are random. Use only for positive values. Can use 2 levels (shown as pie).</p> <p> Format 1-2 label 1 value</p> <p>Line Graph Always have series as columns (vertical). Format: 1 label series 1, series 2...</p> <p>Stack Graph Good: Time-series change of ratio. Use only positive values. Y-axis shows sum.</p> <p> Stack Graph for Categories Groups categories by colorset.</p> <p> Format 2+ labels. series 1, 2...</p> <p>Pie Chart User can switch btw series. Format Label series_value1. value2...</p> <p>Treemap Good for hierarchial allocation.</p> <p> Format 1+ hierarchial label value1 (area), value2(color).</p> <p> Treemap for Comparisons 'change tree map'. change over time series.</p> <p>Word Tree Parses out recurrent contexts. Format: free text.</p> <p>Tag Cloud Parses out recurrent keywords. Format 2 col data Text Or fragments.</p> <p> Word Cloud Generator A variation</p> <p>Phrase Net Networks words. designate filter word and draw graph. Format: text.</p> <p>Maps Better done w/ Fusion Tables limited regions. But can have 2 or all comp. colors or bubbles. can't overlap multiple values. Format region(name, ISO ccode, standard abbr) value (# or txt)</p> <p>Examples of the Week Good The Guardian: Twitter rumor spreading</p> <p> Rich information interface Vivid change over time, as expressed with time</p> <p> Good or Bad Yonhap: Credit level change over time</p> <p> Decoding information from sound Uses for the visually impaired?</p>


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