Aggregate Stats API #

The Aggregate Stats API provides summary statistics combined across every Project Sidewalk deployment: total distance explored, labels, validations, and deployment counts (cities, countries, languages), plus a per-label-type breakdown. This is the project-wide rollup that powers the headline numbers on this documentation site.

For per-deployment statistics for a single city, see the Overall Stats API; for the list of deployments, see the Cities API.

Aggregate Stats API Preview #

Below is a live preview of the project-wide totals across all Project Sidewalk deployments:

Loading aggregate statistics...

Endpoint #

Retrieve aggregate statistics across all deployments.

GET /v3/api/aggregateStats

Examples#

/v3/api/aggregateStats Get aggregate stats in JSON (default)

/v3/api/aggregateStats?filetype=csv Get aggregate stats in CSV

Query Parameters #

Parameter	Type	Description
`filetype`	`string`	Output format: `json` (default) or `csv`.

Quick Download #

Download aggregate statistics directly in your preferred format:

Responses#

Success Response (200 OK)#

On success, the API returns an HTTP 200 OK status code. In JSON (default) the body is an object of aggregate totals; in CSV the body is a two-column metric,value table.

{
    "status": "OK",
    "km_explored": 12345.6,
    "km_explored_no_overlap": 11890.2,
    "total_labels": 4567890,
    "tutorial_labels": 123456,
    "total_validations": 2345678,
    "num_cities": 18,
    "num_countries": 5,
    "num_languages": 7,
    "by_label_type": {
        "CurbRamp": {
            "labels": 1200000,
            "labels_validated": 800000,
            "labels_validated_agree": 720000,
            "labels_validated_disagree": 80000
        }
        // ... more label types
    }
}

Response Fields #

Field	Type	Description
`status`	`string`	Always "OK" for successful responses.
`km_explored`	`number`	Total kilometers of streets explored across all deployments.
`km_explored_no_overlap`	`number`	Total kilometers explored, excluding overlapping coverage.
`total_labels`	`integer`	Total number of labels across all deployments, excluding practice/tutorial labels. Equal to the sum of the `by_label_type.<type>.labels` counts.
`tutorial_labels`	`integer`	Number of practice/tutorial labels across all deployments. Reported separately because they are excluded from `total_labels` and `by_label_type` (they would skew the per-type ratios). Note: the count contributed by the legacy Washington, DC deployment also includes a small number of low-quality labels that its archived data cannot separate from tutorial labels.
`total_validations`	`integer`	Total number of validations across all deployments.
`num_cities`	`integer`	Number of deployment cities.
`num_countries`	`integer`	Number of countries with a deployment.
`num_languages`	`integer`	Number of natively translated languages.
`by_label_type`	`object`	Per-label-type breakdown, keyed by label type name (e.g. "CurbRamp").
`by_label_type.<type>.labels`	`integer`	Number of labels of this type.
`by_label_type.<type>.labels_validated`	`integer`	Number of labels of this type that have at least one validation.
`by_label_type.<type>.labels_validated_agree`	`integer`	Number validated as correct (agreed).
`by_label_type.<type>.labels_validated_disagree`	`integer`	Number validated as incorrect (disagreed).

Error Responses#

If an error occurs, the API will return an appropriate HTTP status code and a JSON response body containing details about the error.

500 Internal Server Error: An unexpected error occurred on the server.

Error Response Body #

Error responses include a JSON body with the following structure:

{
    "status": 500, // HTTP Status Code
    "code": "INTERNAL_SERVER_ERROR", // Machine-readable error code
    "message": "Failed to retrieve aggregate statistics: Database connection error" // Human-readable description
}

Terms of Use #

If you use Project Sidewalk data in your research, please cite the following paper (awarded 🏆 Best Paper at CHI 2019):

Manaswi Saha, Michael Saugstad, Hanuma Teja Maddali, Aileen Zeng, Ryan Holland, Steven Bower, Aditya Dash, Sage Chen, Anthony Li, Kotaro Hara, and Jon Froehlich. 2019. Project Sidewalk: A Web-based Crowdsourcing Tool for Collecting Sidewalk Accessibility Data At Scale. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI '19). Association for Computing Machinery, New York, NY, USA, Paper 62, 1–14.

Contribute#

Project Sidewalk is an open-source project created by the Makeability Lab and hosted on GitHub. We welcome your contributions! If you found a bug or have a feature request, please open an issue on GitHub.

You can also email us at sidewalk@cs.uw.edu

Project Sidewalk in Your City!#

If you are interested in bringing Project Sidewalk to your city, please read our Wiki page.