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Geographic Information Systems (GIS): Search Strategies

This guide helps you get started learning about GIS and how to find geospatial data.

Where to Start?

There are a few distinctions between data sources to be aware of when looking for geospatial data, as it affects where you search for data:

  1. The first distinction is between library licensed data and the growing availability of open data. Library licensed data (i.e., data with a cost associated with it) may be found in our dataset repository, Abacus (see box below on the right). Meanwhile there is a growing availability of geospatial data online, so turning to web searching may be the way to go.
     
  2. The second distinction is to consider who would be interested in and be able to collect and share the data. One way that data, especially geospatial data, can be organized is by level of geography. For Canada, there will be data portals at the national and provincial levels (and a growing number at the municipal level). Another way it can be organized is by subject. Certain organizations, charities, or other community groups will collect and share data on topics of special interest to themselves.

Key Things to Remember

Documentation: Always download the documentation (i.e., metadata), as it will have essential information you’ll need to make sense of the data.

Sources & Organization: Always make note of where you downloaded the data sets from, as you go (it is easy to lose track!), and keep your downloaded data organized.

Licences: Always review the data set's licence (if applicable) for use restrictions and citation requirements. See the Citing Data tab for more information.

Need Help?

Need help finding data? Contact a member of our team.

Internet Search Strategies

Geospatial Data Source Lists

To start off, we maintain a list of helpful geospatial data sources, available by geographical area (National & Provincial, Regional & Municipal, US or International) and then subdivided by subject.

Internet Searching

But you may find you’re looking for something that you can’t find on these lists. Then you’ll need to turn to Internet Searches. There are different approaches to try here:

  • Try using terms such as “download”, “data”, “GIS”, “shapefile”, "geospatial data", etc. along with your subject or geographic area of interest.
  • Try to consider who would be interested in and be able to collect and share the data. Then go to their website and see if they share data on it,  try adding the name of the organization to your search, or use the “site” operator to use google to search a particular website or domain name. For example, add "site:.gc.ca" to limit your search to Canadian federal government sites or "site:.gov.bc.ca" to limit your search to BC provincial government sites. 

Internet Search Considerations

Searching for geospatial data online can be frustrating and time-consuming. Here are some things to keep in mind as you go through the process:

Search Terms

As with any search, you may find that your term is too specific in terms of topic or geography to find anything. The data may be within a greater data set that covers many topics, so you may have to broaden your search terms. For example, glaciers may be in a land cover data set or grocery stores may be within a points-of-interest data set. Data sets may also cover a larger area than you are looking for. Although your study area may only be around one municipality or landform, the data may only exist at the provincial or national level. For example, depending on your topic, you may not find a lot of data for just a small town in BC, but you may find it within other data sets that cover the larger region, or the whole province, or even Canada.

Note: What you should consider is that once you have this larger dataset, you should clip your data to the region you’re looking at instead of just continuing to working with the larger set. You don’t need to keep and store unnecessary data or slow down your ArcMap projects working off large datasets.

Time

Allow enough time to find data. It can take quite a few hours or days of searching to find the data you need. And sometimes you may find data you want, but you need to apply for access first, which can also take time.

Format

When you find data you want, it may not be in the format you want. You may have to use specialized software to convert from one format to another. We have some software here in our labs, such as Stat Transfer and FME workbench that can help with that. Data sets you find may also not be GIS-ready. The information you are seeking may be in tables or reports. So you may need to put the data into a format that can be read by GIS software (such as by adding columns for latitude and longitude coordinates).

Cost

Data sets may not be free. Some government and many commercial data products may require a fee to access the data. So keep this in mind. Check out Abacus to see if the library has paid for the dataset you're looking for or contact a member of our team.

Quality and Detail

Data quality and detail need to be considered. This is where reading all documentation (i.e., metadata) is so important for any data you find.

For an example of quality, you should check to see how and when the data was collected. For example, if the data you obtained was from tracing a map instead of from surveying a location, there could be inaccuracies in the underlying map that might affect the data. Or you may find out that the data you found is several years/decades old, and so it may be out of date or not appropriate for your research.

For an example of detail, for geospatial data, one question to ask is at what scale was the data created? The Vancouver coastline will not be represented well in a shapefile created at 1:1,000,000, covering all of Canada.

In terms of detail, you also need to check for completeness. Does the data set include all the information you need? Does it cover the time period you’re looking for? Can you understand and interpret the data? All of this information should be included in the documentation so remember to read it carefully!

Image References:

UBC's Dataset Repository: Abacus