Wellbeing Toronto

Tutorial and Guide

Welcome!

Wellbeing Toronto is an easy-to-use web mapping application that lets you pick and combine all kinds of neighbourhood data. You can view individual indicators – like the total population of seniors – on your map, or combine up to 20 indicators into your own custom index. You can also plot points on the map showing the locations of such landmarks as schools, police stations, hospitals, tourist attractions and more. Finally, you can select specific neighbourhoods and show the indicators just for them. This tutorial will guide you through the steps needed to do all those things.

The "Get Started" Screen

Figure 1

Tutorial

If you're impatient to start playing with the app immediately, here's how you begin:

  1. Click the Manage Indicators button at the bottom-right of the application window.
  2. Click on any indicators you would like to combine together. If you want to see just 1 indicator, make sure only 1 is toggled in the Manage Indicators window. You can only select a maximum of 20 indicators. Several selected indicators together is called your Composite Index.
  3. Use the sliders on the right side of the screen to weight your selected indicators. 
    Slide towards 5 to make the weight heavier (more important). Slide towards 1 to make the weight lighter (less important). Setting the slider to 0 removes the layer from the map.
  4. Press the X button in the list of selected indicators if you want to remove it from your Composite Index. Press the ? button to get more information about the indicator you selected.
  5. The Export button at the top of the app allows you to put your map, table, histogram and chart into a single PDF document for easy printing.

1. Click Manage Indicators at the bottom-right.

2. Select your indicators.

3. Weight your indicators using the slider bars.

4. Press the X button to remove an indicator from your Composite Index.

Pressing the ? button opens up the indicator information window.

The Indicator Information window gives you statistical information about your indicator and describes its source, date of collection, domain, limitations, caveats and usage recommendations. If more information is available on another website, a link will be provided. The Statistics and Histogram describe how the indicator data is distributed and some other characteristics; these are used by researchers to evaluate the data.

5. Press the Export button to create a PDF for easy printing.

This will bring up the Export window which presents you with several choices. You can give your map a custom title (such as "My Map of Income") and include the map, histogram (a chart showing the distribution of values within your index), a chart ranking all 140 neighbourhoods by your Composite Index, and a table with all the data inside it. Once you've selected all the elements you want to include, press the Export to PDF button on the top-right of the window to create your PDF. You can save to your computer and print it out later. You can scroll down through the window to see a preview of what your PDF will look like. Once you press the Export to PDF button, please be patient; it may take up to 2 minutes to create your PDF.


 

You can view a single indicator by clicking on its area (Pop 15 - 19 years in the picture) or view the whole Composite Index you created by clicking the top area (Composite Index in the picture).

Press the Table button at the top to generate a table showing your Composite Index values (1-100) and the raw values for all the indicators you currently have selected. You can export this table to an Excel or CSV (delimited text) file for use on your own PC.


 

The table shows the Composite Index in the second column from the left. Each column can be sorted by single-clicking on its header (the name in the area with the light-green tint). Clicking on the Neighbourhood column will sort the neighbourhood names alphabetically.


 

When you select the Display button, on the bottom-right you will see a listing of Additional Layers. This list contains landmarks such as schools, convenience stores, hospitals and other features whose location may be of interest to you. The list is not exhaustive, and some features are only visible when you zoom in very close to local street level. You can search for specific layers by clicking inside the Filter Layer List area, typing your search terms (such as "social") and pressing Enter.

Pressing the ? button on a reference layer will bring up a brief description of the layer's data. Advanced users can also download the Shapefile for the layer if it is available on the Open Data website (not all layers are available). Additional datasets not visible in Wellbeing Toronto are available on the City of Toronto's Open Data website at http://www.toronto.ca/open.


 


 

The Areas section allows you to select several neighbourhoods and see the indicators just for those neighbourhoods, instead of for the whole city. Click the Areas section to begin.


 

Then, pan around the map and left-click on any neighbourhood you want to add to your custom area. When you left-click a menu appears. Select Add to Custom Area. That neighbourhood is now part of your custom area. You can select neighbourhoods that are not beside each other. Whatever indicator(s) you selected for your Composite Index are now displayed just for your custom area. You can clear the custom area by pressing the Remove All button at the bottom.


 

You can control the transparency of the map using the slider under the Display section.


 

Sliding it to the Off position allows you to see the base map with streets and local features. Sliding it to the On position makes the base map disappear and allows you to see your Composite Index more clearly.


 

You can also change the base map from a streets view to an aerial photography view, or turn it off entirely.

In addition, you can modify the appearance of the map by changing the class breaks distribution from Equal Interval to Quantiles (in the Measure dropdown) or changing the colour of the map.

The bars above the Additional Layers area are a histogram that shows the distribution of the values of the indicator that is currently selected, on a scale of 1 to 100. By mousing over each bar you can see how many neighbourhoods fall within each range.


 

Wellbeing Toronto allows you to locate an address in a simple fashion. Type the address or part of an address in the bar at the top of application, then either press Enter or click on the magnifying glass icon on the right of the bar. The map window will zoom in to the address point.

Important User Information

Please keep the following in mind when using the Wellbeing Toronto application. Maps, charts and other data can be used and interpreted in many ways. This mini-guide will help with the most common questions.

The City is not responsible for misinterpretation or misuse of data in any way, nor does it endorse any results a user may create using the application. Combining indicators to create a Composite Index does not automatically mean the result is statistically accurate or meaningful in any way. The user is responsible for explaining any linkages between indicators.

  1. Read all footnotes and sources carefully. These notes will contain useful information about the date of the data, exclusions, limitations, and other important notations.
  2. Indicator data in Wellbeing Toronto is aggregated to 140 neighbourhoods. Please note that there are often differences within this geography that are not shown on the maps. For example, a neighbourhood on a map may indicate a high concentration of a particular ethnic group, whereas the concentration may actually be in only a few small blocks within that neighbourhood.
  3. The indicator data inside Wellbeing Toronto is scaled with a range of 1 to 100. Tabular data is presented as unscaled raw numbers. Please consult Appendix A for more methodological details about how the application converts raw numbers to scaled numbers to create the Composite Index.
  4. Maps that portray averages may be subject to outliers – a few large or small numbers that differ significantly from the majority of numbers – thus affecting the overall average. Tabular data should be consulted alongside the map to determine if outliers may be affecting the overall outcome.
  5. An average (the mean) is different from a median (the midpoint in a dataset where half of the data values fall below and half above the given value). Medians are preferred when examining indicators like Income because an pure averages (mean) can skew the dataset if a few people have extremely high incomes (as in common in real life).
  6. Some numbers may be subject to a high degree of volatility. Very small numbers will always show a high degree of change over time, or proportion to a total. For example, there may be 2 murders in a neighbourhood one year and 3 the next; in percent terms the rate went up by 50%, but next year if the number drops to 1, the percent reduction will be 66%. Care should be taken with small numbers.
  7. To reduce the volatility of small numbers some indicators were smoothed out over time. Usually a 3-year average was applied to show average trends over a number of years, which reflects the reality somewhat better than a single point in time.
  8. Generally the smaller the geography, the more likelihood of data suppression. This is particularly true of some variables such as income, or cross-tabulations (income by ethnicity). Data suppression occurs where there are too few people to safely guard their identity under existing privacy legislation, and so the data is removed (suppressed).
  9. "Blank" geographic spaces indicate a lack of data for that particular location, either due to data suppression on the part of Statistics Canada or simply missing data for that area.
  10. Wellbeing Toronto uses 2 types of data distribution: Equal Interval and Quantile. The pattern of data on the map may be quite different between these 2 types and thought should be given to deciding which distribution type is best for the indicators chosen. The two types differ as follows:

    Equal Interval

    The range of data values between the minimum and maximum is divided into classes of equal length. For example, if 5 classes are used and the minimum data value is 0 and the maximum data value is 9, then each class will have a length of 2 and the classes will be 0-1, 2-3, 4-5, 6-7, and 8-9. Each class may have different numbers of values or no values.

    Quantile

    The same number of data values are placed into each class. For example, if 5 classes are chosen, then one-fifth (or 20%) of the values would be placed into each class. A class cannot ever be empty. It may not always be possible to divide the data into the specified number of classes if the data values are not varied enough.

  11. Most maps deal with the largest populations for any given topic. If you do not see a indicator for your desired population, the population may be too small to include in our collection. Statistics Canada suppresses data for very small populations in order to guarantee confidentiality and anonymity in reporting. Very small samples are also prone to statistical error and so are suppressed. Wellbeing Toronto will continue to expand its collection of indicators over time.
  12. Ethnicity, race, visible minority and ancestry are separate concepts and should not be used interchangeably. For example, different techniques are used to collect data for the Visible Minority: Chinese and Ethnic Origin: Chinese categories, and so they are not the same nor are they comparable. Also, some languages such as Spanish comprise people that emigrated from many different Spanish-speaking countries – not only Spain. For detailed definitions of terms and concepts used in the demographics domain, please refer to the Census Dictionary, located at: http://www12.statcan.gc.ca/census-recensement/2006/ref/dict/azindex-eng.cfm.
  13. Aboriginal (aka Native Indian) populations are especially subject to undercounting. Extra care should be taken when including Aboriginal indicators in calculations. Please refer to the Aboriginal section of the Statistics Canada website for particulars:http://www5.statcan.gc.ca/subject-sujet/theme-theme.action?pid=10000&lang=eng.
  14. On maps that show service locations, please note that maps show only physical geographic locations. Unless stated otherwise, no other information about access to services is provided (e.g. catchment areas, hours of service, eligibility for services). Confidential locations and agencies that have only post-office boxes are not shown. Therefore, it is not appropriate to simply conclude that an area is “well-served” due to an abundance of service locations.
  15. Spatial information is not survey-accurate, and should not be used for work requiring high precision or large-scale mapping (ex. Streets are shown as buffered centre lines and are not representative of true right-of-ways). Please contact Surveys & Mapping for the appropriate survey-level information.
  16. Numbers dealing with persons within the Census are often rounded to the nearest 5. For example, 1230 may in reality be 1228, 1231 or 1232 people. Neighbourhood data is often composed of smaller geographies added together, and this may compound the rounding, creating totals that may not conform to aggregate datasets released from Statistics Canada.This is why some totals do not add up perfectly, because rounding in different locations may produce slight variations.
  17. Copies of Wellbeing Toronto outputs such as maps and charts may be made for personal use only. Any commercial use requires permission from the City of Toronto.
  18. Indicators that are very similar should not be added together, as then you are simply doubling the data without adding any new information. This implicit double-weighting may apply to indicators that share similar populations but are named differently or count slightly different things, such as Language: Chinese and Visible Minority: Chinese. Another example would be Average Family Income and Pre-Tax Household Income; these are similar enough that adding them together does not produce good results. Consult the Census Dictionary for exact definitions of each indicator: http://www12.statcan.gc.ca/census-recensement/2006/ref/dict/azindex-eng.cfm.
  19. Indicators marked with the word 'Category' indicate the total population that answered the question pertaining to the indicator below the Category one. For example, the Mobility Category is all the people who answered the question about whether they moved that year. Non-movers and Movers are the two possible answers for this question. This is used to calculate percentages or rates for certain variables. So if you wanted to calculate the percentage of people who moved in a given year, you would divide the Movers indicator by the Mobility Category indicator. This use is recommended for advanced users.
  20. More detailed information about neighbourhoods can be found in the Neighbourhood Profiles and in the Toronto Social Atlas, located at www.toronto.ca/demographics.
  21. Normalization by population and area was not done on indicators in order to provide users with the raw data and to avoid implicit analysis within the application. Total population and area information is provided for those advanced users who want to normalize any given indicator by these two variables. This can be done by downloading the raw tabular data and manipulating it on the user's computer in a spreadsheet or database application. Normalization is recommended for analysis of data strongly tied to either population or land area (e.g., crime or tree cover). Future versions of Wellbeing Toronto may support on-the-fly normalization for select indicators.
  22. Correlation does not mean causation. Just because Indicator A is high in one neighbourhood and Indicator B is also high does not mean that A causes B or that B causes A. The occurrence of phenomena that seem linked in a neighbourhood must be determined with more sophisticated statistical tests than just looking at a map.
  23. Geoprocessing and interpolation was performed on some indicators (such as the Library ones) in order to avoid boundary-averaging and other geospatial analysis problems where raw data did not precisely fit the neighbourhood geography. Please contact SPAR (spar@toronto.ca) for details.