The X Maps Spot team has compiled a list of commonly used terms you can refer to as you learn about GIS and how it can help your shelter save more lives. Much of the vocabulary specific to GIS and the supporting data processes may be new to you, so use these definitions to provide clarity as you explore the tools.
Accurate: Data which is correct and entered in a way which is useable.
Aggregate: When looking at data in summary form as opposed to individual data pieces. In mapping, this includes summarizing data points within geographic areas to identify hotspots. Examples of aggregated point data include the grid cell based maps in the Core Statistics and Maps Index.
Animal Address or Animal Location: The address where an animal lives or was found. This can be an exact street address or cross streets. Make sure Animal Address or Animal Location is what you are using for GIS.
At-risk: Animals within a community who have a higher than average chance of entering an animal shelter and once there being euthanized. An example of an at-risk group would be feral cats in many communities.
Boots on the ground: This term refers to the types of interventions that rely on people being in a target area to do the work by interacting directly with residents in a respectful way. We have found this type of outreach has been the most impactful when using geographical targeting. Read more about boots on the ground work in Cleveland.
Clean data (percentage): Data which has been accurately entered and complete and is usable in an analysis. This term is often used when describing the percentage of usable data for a GIS analysis. We recommend having at least 80% clean data before progressing with a GIS project.
Community data: The combined data of multiple organizations in a community that is used for the most complete view of the community’s animal situation. An example would be combining the spay/neuter data from multiple clinics throughout a city.
Core statistics: The set of statistics that we recommend be produced and reviewed when completing a GIS analysis of shelter intake. An example would be graphs/tables displaying cat intake by age and for each month for a one-year period. See the Core Statistics and Map Index for additional information and examples.
Data subset: A grouping of data that is part of a larger set of data. An example of a data subset is intake data. Intake data is one grouping of data belonging to an organization’s full data set. A subset of intake data would be stray intake data.
Density surface: One method of identifying hotspots is to use GIS to create a surface map using your datasets. A density surface can display the highest concentrations of your point data in an easy to understand image. See examples of density surfaces in the Core Statistics and Maps Index.
Dirty data: Data which is inaccurately entered or missing from a data subset and thus not able to be used for a GIS analysis (and many other types of analyses). An example of dirty data is an address that doesn’t include a street name.
Geocoded: Geocoding attaches geographic coordinates (latitude and longitude) to your data based on the addresses you collect. When data has been successfully linked to a location on a map we refer to that data as geocoded.
GIS: A geographic information system (GIS) is a computer system designed to capture, store, manipulate, analyze, manage, and present all types of geographical data. GIS allows you to view your data on maps then analyze the data based on geography.
High intensity: The suggested type of interventions our research has shown to be effective in reducing intake. High intensity interventions use a boots on the ground approach and a multitude of resources to make a focused effort in one location or area. An example of high intensity interventions can be seen in the GIS Checklist tool.
Hotspot: This term describes locations within a community which are identified as having high concentrations of data points. A hotspot can be used to describe an area of high adoptions, intake, spay/neuter or any other data subset you can look at geographically.
Individual animal data: The data relates to one single animal rather than a large group. In a table, this type of data would include one row for each animal. An example of individual animal data can be found in the Prepare to Map Your Data tool.
Intervention(s): A set of programs or projects designed to help achieve a specific result in a targeted area. For example, a spay/neuter project in a hotspot to reduce juvenile animal intake.
Mapable: This term is used to describe animal addresses and animal data which are able to be geocoded and used in a GIS analysis of a community.
Saturation: This is the level of uptake you want to achieve when working in a geographically targeted area. In order to reach saturation, a high percentage of pets or people within that target area must have taken advantage of a service such as spay/neuter. Though the exact number may vary in each community, our research shows there may be a saturation level that impacts shelter intake. You can read more about that research here.
Summary data: The compiled data of a group of animals that does not show individual animal data. Summary data is useful when identifying what you would like to look at using GIS. For example, if the summary data shows a large number of juvenile Bully Breeds coming into the shelter but not a lot of adults, it would be worthwhile to look at the juvenile data using GIS but not the adults. An example of summary data and its use for GIS purposes can be found in the GIS Checklist tool.
Targeting: Once a geographic analysis has been prepared and hotspots have been identified, we use this term to describe efforts or interventions (see definition above) in those hotspots. Geographically-focused efforts can be more effective and efficient.