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Boundaries

Boundaries⚓︎

This section explains how to view and interact with dataset boundaries in the OS-CONNECT Data Viewer, including viewing boundary and dataset details and accessing QA/QC quality reports.

For a list of all guides on the TCAT Wiki, refer to the Guides List.

Dataset Boundaries⚓︎

Dataset boundaries are geographic polygons that outline the coverage area of each dataset in the OS-CONNECT collection. Each boundary represents a jurisdiction (city, county, or other area) for which pedestrian data has been produced.

To view dataset boundaries, ensure the Boundaries toggle is enabled in the layer toggles.

Boundaries toggled

Viewing Boundary Details⚓︎

Left-click in a dataset boundary polygon to view a popup containing details about that dataset:

Field Description
Name The name of the dataset (typically a jurisdiction name)
Uploaded The date the dataset was uploaded to the TDEI platform
Version The version number of the dataset
ID The unique TDEI Dataset ID (with a Copy button)
Quality Report A View Report link that opens the QA/QC Report for that dataset

Boundary popup

Tip

Use the Copy button next to the ID to copy the TDEI Dataset ID to your clipboard for reference or use in other TDEI tools.

The following naming conventions are used:

WSP_NAME_TYPE
  • WSP: Washington State Proviso
  • Name: The name of the jurisdiction or area
  • Type: The type of area covered
    • City or UI (unincorporated)

QA/QC Quality Reports⚓︎

Each dataset boundary card includes space for a Quality Report link. Selecting View Report opens the QA/QC quality report for that dataset, which evaluates the quality, completeness, and usefulness of the pedestrian infrastructure data for that jurisdiction.

The QA/QC report helps planners, transportation professionals, and community members understand whether the data for a given area is ready to support accessibility, safety, and connectivity initiatives.

Info

For detailed guidance on reading and interpreting QA/QC reports, refer to the QA/QC Reports User Manual.

Next Steps⚓︎

  • Explore the data layer to view feature types and their attributes
  • Learn how to report issues with the data