Tips and Tricks for Data Display

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Health Progress and Performance Reviews Workshop
Bangkok, Thailand July 2011
Jason Smith and Candy Day

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  • UN Guide on Making Data Meaningfulis particularly well done and covers issues thoroughly and yet briefly“A guide to writing stories about numbers”“A guide to presenting statistics”
  • This tool kit focuses on specific tools that can be applied to facilitate data use. The tools can be used independently or a combination of tools may be applied, depending on need and context. 
  • Audiovisual guidelines by which no transparency of slide should contain more than six words per line of text and no more than six lines of text.
  • Vulnerable to the power of first impressionspeople routinely judge policy briefs by theircovers. It is essential, therefore, that a policybrief’s first page represent a project’s very bestwork. The form should be visually appealingand the writing must be highly coherent.Page one of the brief presents the project’spolicy relevance in condensed form. It identifiesthe project, outlines the main policy problem itwas designed to address, introduces key findingsand advocates a specific course of action.Given the unique burden of responsibilitythis page carries, putting extra effort into it isjustified.
  • Colour coding is a strategy to group data and suggest actionMost commonly red, green and yellowSee at a glance where action is requiredExcel 2007 can easily show colour ranking directly on the data – (can also do inline mini-graphs – see later)
  • Health summary bulletins usually contain information on key health indicators in a specific program area. The information is usually presented in tables and graphics with some explanatory text. Summary bulletins often contain large amounts of information compiled from different data sources. This information is usually not interpreted in the context of specific decision making and recommendations for programmatic changes are usually not provided. However, they are an important way to display synthesized data that provides an overall picture of the health status in a given country. Typically, they are often best targeted to program managers and other decision makers with in-depth knowledge of the specific program area. •Executive summary to transmit key arguments without reading whole document.•Problem description / diagnosis of the situation•Chart of policy options- highlights different views and acknowledge key actors•(Conclusions and results)•Policy recommendations•References and authors
  • For example the Countdown ReportsHealth status report cards report on key health indicators in a specific country or program area. A report card is different from a health summary in that it reports on fewer health indicators and compares current progress to a target or to past report card trends. A grade is developed to convey the program’s success in meeting the specific target or in improving progression in each health indicator over a period of time to allow for direct comparison between reports. The grade is usually depicted to match the common grading system for the specific country. The grading provides decision makers with an at-a-glance indication of whether or not a specific service or health indicator needs attention.
  • Policy Briefs highlight actionable recommendations for decision-making in a 2-6 page format. The typical format identifies a problem, proposes a solution and presents a compelling and feasible recommendation. Non-academic language is used and images, quotes, photographs, and bullets are recommended. The supporting evidence is also highlighted. This format is ideal for conveying specific evidence-based policy recommendations. Who is the brief aimed at?• Does the audience know us?• How much does the target audience know about the issue?• How do they perceive the issue?• What questions do need answers to?• How open are they to your message(s)?Design to make people pick them up•Key points – three short statements, key messages•Boxes to indicate related but not integral content (case studies, methodology)•Policy implications or recommendations•References / useful resources•Authors not given prominence
  • Data Dashboards visually presents critical data in summary form so that decisions can be made quickly. Dashboards give an at-a-glance perspective on the current status of a project in the context of predetermined metrics for that project. Dashboards are linked to a database so that users can change key inputs to see how they affect what is displayed on the dashboard and also so that users can drill down to source data to understand the relationships they see on the dashboard. Dashboards assist in the management of the large amount of data that are being collected by health programs by tracking key program metrics and displaying trends. This allows users to identify problems and target specific follow-up activities to improve services.Difficult to show in a static presentation:Eg Tableau – on server, or packaged workbook
  • Stephen Few, Perceptual Edge – various books and articles on communicating numbers
  • Most graphs are two-dimensional, with one axis running vertically and the other running horizontally. Two-dimensional graphs work well because they use the two most powerful attributes of visual perception for encoding quantitative values: line length (or the length of shape similar to a line with an insignificant width, such as bars in a bar graph) and 2-D position Only these two, of all the attributes of visual perception, including color, shape, and size, do an effective job of graphically representing quantitative values. “Can’t the size of objects be used to encode quantitative values?” you ask. It can to a limited degree, in that you can tell that one of the circles in figure 16 is bigger than the other, but you can’t easily determine how much bigger it is.
  • He continues to show the 4 best graphs types based on these aspectsAnd once again stresses using minimal formatting – removing any features that don’t add to the communication but may be a distraction – eg grid linesAlso covers lots of details about legend placement, axes etc
  • Use two-dimensional graphs so that information is not distorted and bar levelscan be read easily.
  • Confidence intervals or ranges of uncertainty can intuitively show whether values over time or between groups are really different – probably confidence bands are even easier for some audiences
  • A variation on confidence intervals, this range of uncertainty makes it easy for the reader to understand how much doubt there is about the actual estimate, without needing a deep understanding of statisticsa – and in this case it is also helpful to see how closely alternative data sources match with the main estimate.
  • Linear, log and other fitted lines help interpreting directions of trendsLoess regression very useful for large quantities of data where there is a lot of noise in the data and where the trend does not fit well with a standard regression lineLOESS is one of many "modern" modeling methods that build on "classical" methods, such as linear and nonlinear least squares regression. Modern regression methods are designed to address situations in which the classical procedures do not perform well or cannot be effectively applied without undue labor. LOESS combines much of the simplicity of linear least squares regression with the flexibility of nonlinear regression. It does this by fitting simple models to localized subsets of the data to build up a function that describes the deterministic part of the variation in the data, point by point. In fact, one of the chief attractions of this method is that the data analyst is not required to specify a global function of any form to fit a model to the data, only to fit segments of the data. The trade-off for these features is increased computation. Because it is so computationally intensive, LOESS would have been practically impossible to use in the era when least squares regression was being developed. Most other modern methods for process modeling are similar to LOESS in this respect. These methods have been consciously designed to use our current computational ability to the fullest possible advantage to achieve goals not easily achieved by traditional approaches.
  • Sparklines are small, word-sized line charts that show trends over time. They have the benefit of showing a great deal of information at a glance and can be placed alongside words that explain their meaning.World Health Statistics
  • Excel has some direct functionalityThere are also some add-ins that can draw inline mini-graphs or “sparklines”
  • Segmenting the data is useful for several scenarios including whereToo much data to show in one graph – eg 52 districts Relationships of differences between sub-sets of data
  • Another use for multiple panes Show graphs of different indicators on the same or individual axesToo many dimensions to include all of this information in one conventional graphThis sort of technique may be more useful in data analysis, and not necessarily for communication to a formal or non-technical audience
  • A way to use movement in AV presentations. Hard to show in a static poresentation like this.Gapminder – Google Motion chartsTableau animation – cycle through years of dataTrails etc
  • A whole area in its own rightConventional thematic / choropleth mapsCanadd graphing – eg pie charts to mapsAdding contextual layers – eg Google Earth/Maps
  • Instead of shading each geographic area, a bubble is placed over the centroid of the area and sized according to the indicator valueBy fading out the boundary data and using a light colour for areas with a small HIV problem, it really draws a lot of attention to where the VOLUME of the problem is(Tableau)http://www.tableausoftware.com/learning/examples/aids-perspective
  • In addition to using colour and size, animation enables watching how the mapped distribution changes over time
  • Not a GIS - Data display tool onlyDoesn’t do spatial analysis like buffering, density estimation, spatial stats, etc. and it can’t manage layersBut, it is a quick, easy to use toolAdvantages over a GIS:Quick mapping of administrative unit data Excel is widely usedGoogle Earth is freeAvailability:Boundaries for over 40 countriesFrench version available on requestAvailable on MEASURE Web pagehttp://www.cpc.unc.edu/measure/e2g
  • Tips and Tricks for Data Display

    1. 1. Tips and Tricks for Data Display<br />Health Progress and Performance Reviews Workshop<br />Bangkok, July 2011<br />Jason B. Smith, MEASURE Evaluation<br />Candy Day, Health Systems Trust<br />
    2. 2. Guides<br />Several guides to preparing effective data presentations<br />
    3. 3. Making Data Meaningful<br />
    4. 4. Data Demand and Use Tool Kit<br />Quick Guide: Tools for Data Demand and Use in the Health Sector<br />Framework for Linking Data with Action<br />Assessment of Data Use Constraints<br />Information Use Map<br />The Stakeholder Engagement Tool<br />Performance of Routine Information System Management (PRISM) Framework<br />http://www.cpc.unc.edu/measure/tools/data-demand-use<br />
    5. 5. General Content Guidance<br />
    6. 6. Readability (Please)<br />
    7. 7. Use Visuals<br />Appealing and coherent<br />The power of page one - people often judge by the cover.<br />
    8. 8. Use Color<br />* Indonesia<br />
    9. 9. Summarizing Data for Decision-Makers<br />
    10. 10. Health Summary Bulletins<br />Key health indicators in a specific area<br />Tables, graphics, text<br />Large amount of compiled information<br />Overall picture of health status<br />
    11. 11. Health Status Report Cards<br />Reports on key health indicators<br />Compares current progress to target or trends<br />Grading system for success<br />
    12. 12. Policy Briefs<br />Highlight actionable recommendations<br />Identifies problem<br />Proposes solution<br />Recommendation<br />
    13. 13. Tips for Effective Policy Briefs<br /><ul><li>Use a professional vs academic tone
    14. 14. Ground the argument in evidence
    15. 15. Make it interesting – images, quotes, photos, boxes
    16. 16. Make recommendations feasible
    17. 17. A few pages
    18. 18. Consider providing supporting documents</li></ul>MakingResearch<br />FindingsActionable<br />Aquickreferencetocommunicatinghealth informationfordecision-making<br />
    19. 19. Data Dashboards<br />At-a-glance perspective<br />Linked to database<br />Drill down in data<br />Management of large <br /> amounts of data<br /><ul><li>Some tools:
    20. 20. Tableau http://www.tableausoftware.com/
    21. 21. Instant Atlas http://www.instantatlas.com/
    22. 22. StatPlanethttp://www.sacmeq.org/statplanet/
    23. 23. Geocommonshttp://geocommons.com/</li></li></ul><li>Improving Graphs<br />
    24. 24. Choosing Graph Types<br />Is a table, graph or both needed?<br />Best means to encode the values<br />Where to display each variable<br />Best design for remaining objects<br />If particular data should be highlighted, and how<br /><ul><li>Stephen Few, Perceptual Edge – various books and articles on communicating numbers</li></li></ul><li>Best Means of Encoding Data<br />The most powerful for visual perception are<br /> line length and 2-D position<br /><ul><li>Stephen Few, Perceptual Edge – various books and articles on communicating numbers</li></li></ul><li>Best Graph Types<br />Points, lines, bars and boxes are best<br />Format to remove distractions – e.g., grid lines<br /><ul><li>Stephen Few, Perceptual Edge – various books and articles on communicating numbers</li></li></ul><li>Avoid 3-D graphs<br />Adds nothing to graph<br />Difficult to determine exact values<br />
    25. 25. Confidence Intervals<br />
    26. 26. Uncertainty: IHME - MMR<br />Supplement to: Hogan, Foreman, Naghavi, et al. Maternal mortality for 181 countries, 1980–2008: a systematic analysis of progress towards Millennium Development Goal 5. Lancet 2010;<br />
    27. 27. Trend Lines<br />Help interpretation of trends<br />Smooth noise in data and outliers<br />
    28. 28. Mini-Graphs / Sparklines<br />World Health Statistics, 2011<br />
    29. 29. Mini-Graphs<br />
    30. 30. Lattice/faceted graphsmulti-dimensional data<br />
    31. 31. Tips<br />
    32. 32. Animation<br />Gapminder, Google Motion charts<br />Tableau and other software products<br />
    33. 33. USING MAPS<br />
    34. 34. Maps: Layering<br />Map <br />showing <br />slum <br />areas<br />
    35. 35. Maps – Using Size and Color<br />
    36. 36. Maps – Size, Colour and Animation<br />
    37. 37. Excel to Google Earth Macro<br />MEASURE Evaluation tool that allows Excel data to be mapped in Google Earth<br />http://www.cpc.unc.edu/measure/e2g<br />

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