Communication With Census Data: Data Visualization

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Communicating With Census Data: Data VisualizationSelect Topics in International Censuses1Released June 2017INTRODUCTIONThis technical note will demonstrate effective data presentation and visualization practices for census and surveydata produced by National Statistical Offices (NSOs).Data visualization can help NSOs reach a broader audience,more effectively communicate high priority information,and discover hidden patterns. Visuals can be created easilyusing common office productivity software, but constructing professional and well-designed visuals requires additional effort. Ultimately, the added effort is worthwhilesince useful visuals will substantially improve the effectiveness of statistical products.As data authorities, NSOs should prioritize the productionof effective visuals in both existing analytical products andas standalone products to improve accessibility to officialstatistics for data users, decision-makers, and the public.The first part of this technical note discusses importantconcepts associated with data visualization, such as thevalue of visuals, how to produce a visual, and good practices. The second part includes examples of good practicesfor three types of data visualization: tables, charts, andmaps.CREATING VISUALSData are presented in a variety of visual formats and mediums, all of which are complementary. For instance, whiletables of data are important, providing only tables withoutaccompanying charts or maps is limiting to the value of theoverall data presentation.Most static visuals are produced with standard office productivity software, while others require advanced tools andskills.Data visualizationTerminology used:Visual (noun): a collection of graphics and text usedto convey information, such as a chart, map, or tableVisualize (verb): the act of creating a visualThis technical note is part two of a two-part series onCommunicating With Census Data. This series illustratesthe importance of conveying census results to a wide audience through the production of relatable and engaging dataproducts.People naturally form visuals in their minds (Few 2012,p. 65). Whether reading a novel, dreaming while asleep, orgoing about daily tasks, the human brain is capable of compressing large amounts of information into a visual representation of a phenomenon. A visual is “a tool for your eyesand brain to perceive what lies beyond their natural reach”(Cairo 2013, p. 10).The act of data visualization uses this innate ability toprovide context to large amounts of data with graphics.By definition, “data graphics visually display measuredquantities by means of the combined use of points, lines, acoordinate system, numbers, symbols, words, shading, andcolor” (Tufte 1983, p. 9).1This technical note is one in a series of “Select Topics in International Censuses” exploring matters of interest to the international statistical community.The U.S. Census Bureau helps countries improve their national statistical systems by engaging in capacity building to enhance statistical competencies insustainable ways.

Technological advances and the proliferation of free andopen data have improved our ability to visualize data (Cairo2011, p. 14). Specifically, visualizing census and surveydata can add value for several reasons: Showing patterns that are otherwise obscured.Even if the underlying data are large or complex, a welldesigned visual will highlight the most important patterns. These patterns are difficult to identify without theassistance of visuals. Transmitting information quickly. Most readers cannot meaningfully interpret a table of data without extensive analysis. Visuals can turn a data table into a graphicthat can be quickly interpreted. Providing compelling evidence. Data visualizationsstrengthen the author’s narrative by easing the transferof knowledge to the audience.Subject matter experts may use visuals during the exploratory data analysis stage (see the exploratory data analysissection in Part 1 of this series). However, this technical notewill focus on the use of data visualization when presentingfindings to another audience.Visual types and mediumsOne of the earliest decisions when producing a visual is todetermine the dissemination or publication medium. Paperproducts have different requirements than Web products.For instance, paper requires attention to the weight, thickness, coating, and brightness of the paper itself. Conversely, electronic products typically require a reliableInternet connection and should be viewable across multipledevices (such as personal computers, smartphones, andtablets).A visual can be either static or interactive. Static visuals are the most common since they are the simplest toproduce. Many static visuals can be created using commondesktop productivity software.Interactive visuals are typically associated with Internetproducts. If well designed, an interactive visual can displaya greater amount of information and engage the audiencefor a longer period. However, interactive visuals demandgreater technical ability to design and may require externalconsultancy.Due to their ease to adopt and usefulness for nationalstatistical offices, this technical note will focus on staticvisuals.Static visualsAnalytical products from national statistical offices provideinformation about major trends and patterns over time2and space. For most national census and survey analyticalproducts, the primary forms of static visuals will be tables,charts, and maps. These three visual forms are popular due to their effectiveness and simplicity in conveyinginformation.Each type of visual has strengths and weaknesses. Ultimately, the choice of visual is a trade-off that acceptscertain weaknesses of the presentation format if they areoutweighed by the strengths. These considerations arediscussed in more detail later.Box 1 demonstrates a process for creating a visual. Whileauthors may be tempted to use a repetitive set of visualsthroughout a product and across multiple variables, notevery variable needs an accompanying visual. Authorsshould evaluate the advantages and pitfalls of data visualization to determine whether or not a visual is addingvalue to a product or distracting the audience from the keymessage.Box 1.FigProcess for Creating a VisualSt1) Which data are needed to visualize? When choosing anindicator to visualize, consider the main variable. This willusually become the x-axis in a two-dimensional graphicalrepresentation, e.g., census years, response categories.ThHo(PDit i2) Why is it important to visualize these data? The visualmust have a purpose. Think about interesting patterns in thedata that can only be shown with a visual.3) What type of visual should be created? The choice ofvisual depends on the data. For example, if the purpose is toshow a spatial pattern, a map is the preferable visual type. Or, ifthe purpose is to show a pattern over time, perhaps a line graphis the best visual. All visuals involve compromise.4) How does this visual complement other visuals in theproduct? Unless a visual is released as a stand alone product, itmust be chosen in consideration of the other visuals, publicationmedium, space available, and subject matter.Cocosonuac5) How will this visual be created? Software is required tocreate visuals. Maps are typically created in Geographic Information System (GIS) software, while charts and tables can becreated in office productivity software.Source: U.S. Census Bureau.Skills and software requiredProducing professional visuals requires skills in graphicdesign, Web design, programming, cartography, and/or data management. Other skills that are harder to traininclude artistic and analytical ability.SoFigure 1.applications can produce professional andMany softwareSoftwarefor ProducingVisualsattractivevisuals. ToolsSome commonlyused toolsare shown inFigure 1,includingapplicationsboth commercialand free/opensourceSpecializedmay be requiredto producecertain options where possible. Note that some softwareCategoryExamplesFutools require advanced training or extensive practice,Productivity softwareDedicated visualization toolsData analysisGraphics designCartographyWeb developmentMicrosoft Excel, OpenOfficeTableau, WEAVEStata, RAdobe Illustrator, InkscapeArcGIS, QGISD3, LeafletU.S. Census BureauCrCrDaPrMBuNote: Many of the examples provided in this table are advanced tools that requirprofessional user.

Figure 1.Software Tools for Producing VisualsSpecialized applications may be required to produce certain ductivity softwareDedicated visualization toolsData analysisGraphics designCartographyWeb developmentMicrosoft Excel, OpenOfficeTableau, WEAVEStata, RAdobe Illustrator, InkscapeArcGIS, QGISD3, LeafletCreating simple visualsCreating more complex visualsData processing and analysisProducing and finalizing graphicsMap making and geospatial dataBuilding interactive Web ncedNote: Many of the examples provided in this table are advanced tools that require extensive training and experience to become aprofessional user.Source: U.S. Census Bureau.especially in graphic design, Web development, cartography, and data See Figure 2 for an example of the distinctionbetween structured and unstructured data.For most applications, the data visualization tools providedin standard office productivity software can produce datavisuals such as tables and charts with minimal additionaltraining. Visuals produced in these applications are highlycustomizable and can be of professional quality.As a general practice, national statistical offices shouldrelease their data products as structured data to ease its usefor visualization purposes internally and externally. Theseformats align with global efforts to improve the transparency and availability of government data and increase theusefulness of national statistical data (United Nations 2013).However, not all functionality within these applications isdesirable. Authors should keep their graphics clean and00 easy to interpret. Good practices, as well as practices toavoid, are discussed in more detail later in this technicalnote for specific types of visuals.Each of these applications can be learned through training.However, training only provides a limited introduction toBox 1.thetopic.forExtensivepractice—possiblyover several years—ProcessCreatinga Visualwill be necessary to become a data visualization expert.1) Which data are needed to visualize? When choosing anTherefore,to avoidconsiderthe losstheofmainfocusfrom subjectindicator to visualize,variable.This will matusuallybecome thex-axisin a d graphicalconsider hiringrepresentation, e.g., census years, response categories.professionalgraphics artists or contracting with vendors to2) Whywithis it theimportantto visualizethesedata?visuals.The visualassistproductionof morecomplexmust have a purpose. Think about interesting patterns in thedata that can only be shown with a visual.GOOD PRACTICES3) What type of visual should be created? The choice ofvisualprimarydependsgoalon theFor example,if the purposeis toTheofdata.a visualis to improveunderstanding.showa spatial pattern,a mapauthorsis the preferablevisual type.ifToaccomplishthis goal,should followthe Or,guidancethe purpose is to show a pattern over time, perhaps a line graphbelow.Thistechnicalnoteuses compromise.examples from theis the bestvisual.All visualsinvolveU.S. Census Bureau to demonstrate good practices.4) How does this visual complement other visuals in theproduct? Unless a visual is released as a stand alone product, itUsestructureddatamust bechosen in considerationof the other visuals, publicationmedium, space available, and subject matter.The key input into a visual is the underlying data. Generally,5) How will this visual be created? Software is required totoproducevisual,mustbe organizedin aInformacomputercreatevisuals.a Mapsaredatatypicallycreatedin Geographicreadablesuch aswhileCommaSeparatedtion Systemformat(GIS) software,chartsand tables Valuescan be (CSV),created in e(XML), JavaScript ObjectNotation(JSON),orinarelationaldatabase. These formatsSource: U.S. Census Bureau.are structured data, meaning that a computer can easily read the data for analysis. These formats contrast withunstructured data, such as the Portable Document Format (PDF), which are not easily readable by data analysisU.S. Census BureauFigure 1.Software Tools for Producing VisualsStructured data can be flat or a cross tabulation. Individualcells within a flat table represent a singlewhileU.S.variable,Census Bureaucells within a cross tabulation represent the combinationof multiple variables. A visual can be created using eitherformat and will depend on the author’s purpose.Figure 2.Structured vs. Unstructured DataThe following table of information may look structured.However, when presented in a format such as this document(PDF), the numbers are not easily computer-readable. Therefore,it is onversely, the picture below shows the same table stored as acomma-separated values (CSV) file and viewed in the Notepadsoftware application. This data format is structured since eachnumber column is clearly separated by a delimiter (in this case,a comma) and each record is placed on a separate row.Source: U.S. Census Bureau.3

Provide contextContext is important with data visualization. Since readersmay only read the visuals and ignore the text in a largerproduct, every visual should have sufficient information forthe audience to interpret quickly.The title is the first item most readers will see and shouldbe descriptive. Within the title, clearly state the variable(s)shown in the visual and the period covered. Titles can alsobe used to convey the main message of the chart.Cite the sources used to produce the visual. For publishedreports, the citation should appear in the visual itself andbe cross-referenced to the footnotes or to complete citations at the end of the document. For stand-alone visualsthat appear on posters or as Internet products, the full citation should be included with the visual. Citation informationincludes the source author or organization (e.g., the NSOitself); the specific operation, report, and year (e.g., 2010Census, Summary File 1, 2011); and a hyperlink if availableonline.Also include data use instructions in the visual. Fornational censuses and surveys, these instructions commonly include links to educational documents providingvariable definitions, sampling error, and nonsampling error(e.g., coverage error and response error).For tables of data, a hyperlink is usually provided toaccess the structured (computer-readable) dataset. Asdescribed previously, organizations should aim to provideaccess to the structured datasets to increase data use byother government agencies, academia, and the privatesector.Make use of graphicsGraphic design is an art. Graphic artists are often neededto produce attractive, professional, and effective visuals.However, even data users with minimal artistic ability canproduce visuals of sufficient quality by effectively using thegraphical elements below.Authors should exercise caution when using these graphical elements. For example, a percentage of the population is unable to distinguish between certain colors due tocolorblindness (commonly red and green), and thereforecolorblind-friendly color palettes should be used for mostproducts. Color can also have either positive or negativecultural significance. These elements can also be overused, resulting in a distracting visual that is ultimately lessfunctional.Use color to draw attention to specific elements of thevisual or subdue other elements of less importance. Forexample, a line graph may contain a series of lines anda single trend line. By coloring the trend line red and the4other lines a light gray, the author can effectively drawattention to the most important element in the visual.For instance, symbols can more accurately convey proportion than pie charts since pie charts are difficult to interpretaccurately. Another common use of symbols is in graduated symbol maps, where the symbols are sized differentlyto reflect an absolute value (a larger size reflects a largervalue, and vice versa).The choice of font will also affect an audience’s interactionwith a visual. Maps, for instance, may use different fontsfor labeling natural features (e.g., water bodies) and sociocultural features (e.g., place names). Font color and style(e.g., bold, italic) will also emphasize certain elements whilesubduing others.Other examples of graphical elements to consider in visualsinclude: orientation, shape, line length, line width, size, curvature, added marks, enclosure, intensity, spatial position,and motion (Knaflic 2015, p. 105).EXAMPLES BY TYPEThe remainder of this technical note will provide recommendations for producing effective, attractive, and meaningful visuals of census and survey data for three majortypes: charts, maps, and tables. These recommendationsare in addition to the previously discussed good practicesthat apply to all visuals.CHARTSChart types of varying complexity are useful for visualizingnational statistics. For simplicity, this technical note willfocus on four chart types: bar charts, line charts, population pyramids, and pictograms.BAR CHARTSBar charts can show relative magnitude for discrete/categorical census and survey variables for the same timeperiod or over time. Bar charts can be presented as singlebars per category, stacked bar charts (with bars placed ontop of others), and double bar charts (with side-by-sidecomparisons). Bars can also be presented vertically orhorizontally.In Figure 3, for example, the total dependency ratio isseparated into youth and older dependency ratios with astacked bar chart. This technique shows that older dependency is increasing relative to youth dependency over time.Advantages: Condenses large datasets into a simpleformat; compares several categories simultaneously; it isaccessible to the public due to popularity.Disadvantages: Subjective, depending on ordering ofcategories and scale formatting; can only display a limitednumber of bars before overcrowding.U.S. Census Bureau

Figure 3.Visual Example: Bar ChartBar charts are useful for showing proportions. This example isa stacked bar chart with one set of bars (youth dependency)Figure 3.placedon top of another (older dependency). This bar chartVisual Example:BarolderChartsuccessfullyshows thatdependency has increased relativeto youth dependency, supporting the author’s narrative that theBar chartsare usefulfor showing proportions. This example isU.S.populationis aging.a stacked bar chart with one set of bars (youth dependency)placedon topRatios:of anotherDependency1980 to(older2050 dependency). This bar chart(For information on confidentiality protection, nonsampling error, and definitions, seesuccessfullyshows that older dependency has increased youthOlderdependency,theratioauthor’sYouth dependencyTotal narrativedependency ratiothat thedependency ratio supportingU.S. population is aging.828281767370Dependency70Ratios: 1980to 205067(For information on confidentiality protection, nonsampling error, and definitions, outh dependency ratioTotal dependency ratioOlder dependency 244291990200020102020453744384338203020402050Note: The total dependency ratio is the number of people aged 0 to 19 and 65 and over per 100 people aged 20 to 64. Theyouth dependency ratio is the number of people aged 0 to 19 per 100 people aged 20 to 64. The older dependency ratio is383738the number of people aged 65 and over per 100 people aged 20 to 64.Sources: 1980, U.S. Bureau of the Census, 1983; 1990, U.S. Bureau of29the Census, 1992; 2000, U.S. Census Bureau, 2001;21to 2050, U.S.222010,20U.S. Census Bureau,Census Bureau, 2012a; 1980 to 2010, decennial census; 2020 to21 2011; 20202050, 2012 National Population Projections, Middle series.1980U.S. INE CHARTSLinechartsare usefulcapturing trends in continuousSource:U.S. CensusBureau,for2014.census and survey data over time. For example, the linechart in Figure 4 shows the poverty rate as captured by censuses and surveys increasing and decreasing over time. TheFigure 4.slopeof theline presentedshould have meaning, whetherVisualExample:Line Chartused for temporal or nontemporal data.Line charts are useful for showing trends. In this case, povertyrates are broken down by age, showing how rates for certainFigure 4.groupshave increased or decreased over time. Extra informationVisualLineChartisadded Example:by highlightingyearsin which the national economywas in recession. However, this information is subdued to avoidLine charts fromare usefulfor showingtrends.AdditionalIn this case,povertydistractingthe primarydata points.notesareratesprovidedare brokendown bytheage,showing howratesforseriescertainalsoexplainingappearanceof Extrainformation2013–2014, when the survey questions were added by highlighting years in which the national economywas Povertyin recession.thisinformation is subdued to avoidRates byHowever,Age: 1959 to2014Percentdistractingfrom the primary data points. AdditionalRecessionnotes are50also45 provided explaining the appearance of the data series from2013–2014,when the survey questions were redesigned.40305025Aged 65 and olderPoverty Rates by Age: 1959 to 2014RecessionPercentUnder age 18452021.1 percent4015351013.5 percentAged 65 and older10.0 percentAged 18 to 64305250195920196519701975198019851990Under age 181995200020052010201421.1 percentNote: The 2013 data reflect the implementation of the redesigned income questions. See Appendix D for more information.15 The data points are placed at the midpoints of the respective years. Data for people aged 18 to 64 and 65 and older are not available13.5 percentfrom 1960 to 1965. For information on recessions, see Appendix A. For information on confidentiality protection, sampling error,10 nonsampling error, and definitions, see s/cpsmar15.pdf .Source:U.S.18CensusAgedto 64Bureau, Current Population Survey, 1960 to 2015 Annual Social and Economic Supplements.10.0 percent5Source:U.S. Census Bureau, Disadvantages: Can only use a few lines before overcrowding (even though it can use more lines than bars in abar chart); requires many data points to show meaningfultrends over time.POPULATION PYRAMIDSPopulation pyramids (e.g., Figure 5) are one of the mosteffective means of visualizing the structure of populationin a census or survey. For example, a pyramid with a widerbottom than top (i.e., a younger population) will reflect acountry with different needs than an evenly sized pyramid.The shape of a population pyramid can quickly tell the audience about the demographic trajectory of a country in thecoming years.Advantages: Visualize population structure; see disparities by age/sex; break down by specific subgroups, e.g.,ethnicities or languages, or by geography.2050Note: The total dependency ratio is the number of people aged 0 to 19 and 65 and over per 100 people aged 20 to 64. Theyouth dependency ratio is the number of people aged 0 to 19 per 100 people aged 20 to 64. The older dependency ratio isthe number of people aged 65 and over per 100 people aged 20 to 64.Sources: 1980, U.S. Bureau of the Census, 1983; 1990, U.S. Bureau of the Census, 1992; 2000, U.S. Census Bureau, 2001;2010, U.S. Census Bureau, 2011; 2020 to 2050, U.S. Census Bureau, 2012a; 1980 to 2010, decennial census; 2020 to2050, 2012 National Population Projections, Middle series.35Advantages: View trends over time; useful for presentingseveral variables of the same category; can combine withother visual elements to highlight important areas along thetrend.2014Note: The 2013 data reflect the implementation of the redesigned income questions. See Appendix D for more information.The data points are placed at the midpoints of the respective years. Data for people aged 18 to 64 and 65 and older are not availablefrom 1960 to 1965. For information on recessions, see Appendix A. For information on confidentiality protection, sampling error,nonsampling error, and definitions, see s/cpsmar15.pdf .Source: U.S. Census Bureau, Current Population Survey, 1960 to 2015 Annual Social and Economic Supplements.Source: U.S. Census Bureau, 2015.Disadvantages: Lost granularity if large age cohorts areused; difficult to incorporate additional variables.PictogramsPictograms are visual representations of data using smallicons familiar to the audience. Each icon is sized proportionally (e.g., one icon represents 10,000 people) and multiple icons are used to show overall trends. For example, inFigure 6, the proportion of male to female military veteransis shown using icons to demonstrate the sex ratio disparity.Advantages: Accessible by a broad audience; quick representation of general patterns or trends; good for massmedia products.Disadvantages: More abstract representation; typicallynot suitable for advanced data users or analytical reports.GOOD PRACTICESNote: These good practices are reflected in Figure 3 throughFigure 6.Show a trend or pattern: Each of these charts highlightssomething important to the author’s story. If a chart is confusing or not particularly useful, do not include the chart inthe product.Unambiguous data: Each data element is distinct fromthe others by using different colors and line borders. Forexample, the trend lines in Figure 4 are three unique colors,and the stacked bars in Figure 3 are also unique colors andinclude borders around each bar. All of these figures uselegends to clarify what each color represents. Figure 3 andFigure 4 also use labels.U.S. Census Bureau5U.S. Census BureauU.S. Census Bureau

0 to 415Figure 5.Visual Example: Population PyramidPopulation pyramids effectively visualize population distributionby age and sex. This visual also highlights a specific cohort, the“Baby Boomers,” born between 1946 and1964.Population by Age and Sex: 2010(For information on confidentiality protection, nonsamplingerror, and definitions, Boom85 and over80 to 84MaleFemale75 to 7970 to 7465 to 691050Millions51015ExcessiveAvoidcommunicatingtoo manySource: U.S.complexity:Census Bureau, 2011;2010Census.ideas at once. The chart should stay focused on a core mesSource:U.S.Census2014.sageandbeeasyBureau,for theaudience to understand.Misleading scales: Scale values should be chosen carefully and will depend on the type of data. Truncating scales(e.g., for data with a narrow range) can lead to misinterpretation or overemphasized variability.Figure 6.Visual Example: PictogramPictograms are typically used for a wide audience. Simple icons,such as the ones shown in this example, are easily understoodby readers at most education levels, including schoolchildren.In this example, one icon represents one million veterans.There are 21.8 million veterans in the United States.60 to 6455 to 5950 to 5445 to 49Male VeteransFemale Veterans20.2 million1.6 million40 to 4435 to 39Source: U.S. Census Bureau, 2012.30 to 3425 to 29Maps20 to 24Maps present the spatial distribution of data. With maps,patterns are shown that are otherwise left hidden in datatables or charts. If designed well, a map can reinforce thenarrative and support the author’s argument. On the otherhand, if designed poorly, a map may confuse the audienceU.S. Census Bureauor cause the reader to lose interest in the product.15 to 1910 to 145 to 90 to 400151050Millions51015Source: U.S. Census Bureau, 2011; 2010 Census.Source: U.S. Census Bureau, 2014.Accurate axes: The values along the x (horizontal) andy (vertical) axes should accurately reflect the chart graphics. For time series, position the data points relative to thelength of time between each data point (e.g., Figure 4).Further, quantitative axes should usually start at zero.Broadly, maps can be divided into two categories: thematicand reference. Thematic maps, as shown in Figure 7, areused to illustrate a particular theme, including social andphysical geography. Reference maps primarily show landmarks, physical features, places, and other informationfor navigation or context. This technical note focuses onthematic maps since they are most commonly used for presenting census and survey data.Figure 6.Highlightkey points:Use graphical elements to highlightVisual mple,theSimplered colorPictograms are typically used for awideaudience.icons,insuchFigure5 highlightsspecificage cohort,whilethe grayas theones showna inthis example,are easilyunderstoodby readersat mosteducationincluding schoolchildren.colorin Figure4 notesyearslevels,in recession.In this example, one icon represents one million veterans.ADVANTAGESSpatial patterns: Show geographic patterns and regionaldisparities that are otherwise obscured in charts or tables.Know your audience: Choose a chart type appropriate toThere are 21.8 million veterans in the United States.your audience and message. Figure 6 is understandable bymostMaleaudiences.Veterans Conversely, Figure 5 may be moreFemale suitableVeteransfor subject matter experts than the public. Figure 3 and20.2 million1.6 millionFigure 4 are common chart types but may still be difficult tointerpret for audiences unfamiliar with the underlying data.Enhance the narrative: The patterns

release their data products as structured data to ease its use for visualization purposes internally and externally. These formats align with global efforts to improve the transpar-ency and availability of government data and increase the usefulness of national statistical data (United Nations 2013). Structured data can be flat or a cross .

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