Visualisation Tools to Support Data Engagement

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  • Also how you position marks on a canvas in relation to each other
  • Visualisation Tools to Support Data Engagement

    1. 1. #CASEprog Data Engagement: Visualisation Tools Tony Hirst Dept of Communication & Systems The Open University
    2. 2. http://www.communities.gov.uk/documents/corporate/pdf/1318351.pdf
    3. 3. From: DCLG DataViz Report
    4. 4. From: DCLG DataViz Report
    5. 5. http://www.improving-visualisation.org/
    6. 6. My Assumptions• Your end users are developing policy• You have data that might help• There are case histories available demonstrating how visualisation techniques can help make sense of data in a way that relates to policy questions
    7. 7. The goal? - to provide access to visualisation techniques to promote your data and provide a way for end users to engage with it
    8. 8. “…there’s a false expectation that visualising datais easy. The JFDI attitude prevalent in other areasof digital tools for local government may havecreated false expectations on ease of access tovisualisation.”
    9. 9. “Cut-and-paste” chart templates
    10. 10. IBM Many Eyes Embeddable  Interactive 
    11. 11. Embeddable Interactive 
    12. 12. Google Fusion Tablepowered maps
    13. 13. Timemaps
    14. 14. “DataLiberation” (Data as such…)
    15. 15. “Import * + Excel/XLS CSV Google Spreadsheet from URL”
    16. 16. Google Refine
    17. 17. (Data Cleansing inGoogle Refine)
    18. 18. Not quite ready yet…
    19. 19. Wizard for creating Googlespreadsheet powered databases
    20. 20. Online interface to R/ggplot2
    21. 21. ggplot() + geom_linerange(data = d1,aes(x= car, ymin = ymin,ymax = ymax)) + geom_point(data = d2,aes(x= car, y= value,shape = variable),size = 2) + opts(title="F1 2011 Korea nRace Summary Chart", axis.text.x=theme_text(angle=-90, hjust=0)) + labs(x = NULL, y = "Position", shape = "")
    22. 22. [ Rstudio ]
    23. 23. [ Rstudio ]
    24. 24. Google Visualisation API/Chart Tools
    25. 25. ScraperView
    26. 26. An in-browserdata context
    27. 27. .5 distinctions
    28. 28. Exploratory Visualisation Vs. Presentation Graphics
    29. 29. “Infographic generators”
    30. 30. sort filter facet group by/aggregate join/merge
    31. 31. FILTER SORTFACET Google Visualisation API/Chart Tool Components
    32. 32. FilterSort
    33. 33. Nested Group-By Optional grouping calculations Google Fusion Tables – Aggregate View
    34. 34. Group by  Hierarchy inside
    35. 35. Data FormatDatasets Datasets Data Views Data Views Data Renderings Data Data Renderings Representation  Data Shape & Structure 
    36. 36. Platonicsolids
    37. 37. -Tabular data-(Geo)spatial data-Temporal data-Network data-Hierarachical data
    38. 38. ANY QUESTIONS??? Tony Hirst @psychemedia blog.ouseful.info

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