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Spatial Stories

Assembling your data

It’s now time to assemble your data. Take a moment to inventory what you have, as well as what you’ll need by returning once more to the initial project design questions as outlined by your worksheet:

  • What data do you have? What data will you need?
  • Whose data is it? Are there any special permissions you need to obtain or access restrictions to be aware of? Note where you are storing your data, any associated licences/attributions, and ensure everyone who needs access has it.
  • What format is your data in (e.g. excel document, csv, text, image, geospatial file such as shapefile or .geoJSON, historical map…)? Is your data in current format legible to the software you intend to use? If not, do you need to convert any of it into a different format?

    As you work through choosing an appropriate software, it will become clearer whether or not your data’s current form is legible to the software you intend to use. There are often ways to convert data between formats. For example, many geospatial formats can be converted from one to another in a GIS. FME is a useful interoperability resource for more complex workflows, and they are generous with free student licenses.

  • What aspect of your data is spatial? In other words, what is the location/geographical attribute? For example, is it a column of street address? The names of cities? Coordinate pairs?…
  • Do you have physical or historical maps as part of your project? Do you need to scan them? If you’re planning on using them in any way other than as decorative/informative archival images, you’ll want to look into georeferencing.


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Considerations for assembling data

The data you’ll need depends on your mapping objectives. Maybe you already have data. Maybe you want to create a reference map and all you need is contextual information and the ability to add some labels and markers. Perhaps your research lab is collecting and processing the data for you. Whether your area of interest is local or global, whether your final map will be static, interactive, or simply the results of some spatial analysis… these factors will influence where you look for data. Municipal and federal data repositories are a good place to begin looking for geospatial reference data. If you have access to a data repository, either through a group you’re working with/for or institutional library for example, reaching out to whoever coordinates on the matter can be useful. You can also begin with a web search and see what is returned. Lastly, in some cases you can make your own data. This is particularly true if you only need a reference point or simple boundary outline. Terrastories and Digital Democracy are two great resources for collecting place-based data on the go.

Whether you’re performing spatial analysis or making maps for yourself or a client, its important to keep a record of your data sources as you work. You’ll figure out a system that make sense to you. Trial and error a few times. However, The following considerations are useful to note somewhere like a document or notes file as you go.

  • What is the dataset of and where did you download it from (save a link)
  • What is the downloaded file called? Where is it stored on your computer/external storage device?
  • Is there a visual data preview such as an interactive web map?
  • What attributes are included in the dataset?
  • Who is the dataset published by and is there a contact for questions?
  • What is the dataset’s license?
  • When was it last updated?
  • What formats can the dataset be downloaded in?
  • What projections can the dataset be downloaded in?

Geospatial data

A Geographic Information System (GIS) works with data that is tied to a location on Earth. This type of data is often referred to as GIS data, or geospatial data, and is spatially referenced to Earth using location information — most commonly geographic coordinates. A GIS uses this location information to project a geospatial file into a virtual geographic space where it can then be visualized and analyzed.

Geospatial data is often referred to as having two main types: raster and vector. These two data types, while both geospatial, are very different from one another. Raster data is data which is made up of pixels arranged in a grid, whereas vector data is made up of vertices and the paths between them – creating geometries that represent real-world features or phenomena. If you’re working with satellite imagery, landuse/landcover data, or climatic data, it’s likely raster. If you’re working with points, lines, or polygons, that’s likely vector data.

Finding geospatial data

Municipal and Provincial Vector Data

Global Census Data

Global Boundary Files

Street Network Examples

Climate, Landcover, and Satellite Imagery

Learn more about Geospatial Data