Overall Stats by Day API #

The Overall Stats by Day API provides a daily time series of label and validation activity for Hackensack, NJ, broken down by label type and by whether the actor was a human user or an AI. This lets you track productivity trends over time.

Each record covers one calendar day (US/Pacific time) and one label type. Label counts reflect labels created on that day; validation counts reflect validations completed on that day (on any label, not just ones created that day).

For aggregate counts across all Project Sidewalk deployments, see the Aggregate Stats by Day API. For a single-number snapshot, see the Overall Stats API.

Overall Stats by Day API Preview #

Live preview of the most recent 90 days of activity for Hackensack, NJ:

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Endpoint #

Returns daily label and validation counts for Hackensack, NJ.

GET /v3/api/overallStatsByDay

Examples #

/v3/api/overallStatsByDay All-time data for Hackensack, NJ in JSON

/v3/api/overallStatsByDay?startDate=2025-01-01&endDate=2025-03-31 First quarter of 2025 in JSON

/v3/api/overallStatsByDay?filetype=csv All-time data as CSV

/v3/api/overallStatsByDay?filterLowQuality=true Restrict to high-quality users

Query Parameters #

Parameter	Type	Default	Description
`startDate`	`string`	none	Inclusive lower bound on the activity date in `YYYY-MM-DD` format (US/Pacific calendar date). If omitted, all data from the beginning of the deployment is returned.
`endDate`	`string`	none	Inclusive upper bound on the activity date in `YYYY-MM-DD` format. If omitted, data up to and including today is returned.
`filterLowQuality`	`boolean`	`false`	If `true`, only include activity from users whose `high_quality` flag is set. If `false` (default), only users explicitly marked as `excluded` are omitted. Mirrors the same parameter on Overall Stats.
`filetype`	`string`	`json`	Output format: `json` (default) or `csv`.

Response Format #

The response is a JSON object with a data array. Each element covers one (date, label_type) combination. Days with no activity for a label type are omitted.

{
  "status": "OK",
  "data": [
    {
      "date": "2025-01-15",
      "label_type": "CurbRamp",
      "human_labels": 150,
      "ai_labels": 0,
      "human_validations_agree": 120,
      "human_validations_disagree": 18,
      "human_validations_unsure": 6,
      "ai_validations_agree": 0,
      "ai_validations_disagree": 0,
      "ai_validations_unsure": 0
    },
    {
      "date": "2025-01-15",
      "label_type": "NoCurbRamp",
      "human_labels": 85,
      "ai_labels": 0,
      "human_validations_agree": 72,
      "human_validations_disagree": 9,
      "human_validations_unsure": 3,
      "ai_validations_agree": 0,
      "ai_validations_disagree": 0,
      "ai_validations_unsure": 0
    }
  ]
}

Response Fields #

Field	Type	Description
`date`	`string`	Calendar date in `YYYY-MM-DD` format (US/Pacific time).
`label_type`	`string`	Label type name (e.g. `CurbRamp`, `NoCurbRamp`, `Obstacle`).
`human_labels`	`integer`	Number of labels of this type placed by human users on this date.
`ai_labels`	`integer`	Number of labels of this type placed by AI on this date.
`human_validations_agree`	`integer`	Human validations with result agree completed on this date.
`human_validations_disagree`	`integer`	Human validations with result disagree completed on this date.
`human_validations_unsure`	`integer`	Human validations with result unsure completed on this date.
`ai_validations_agree`	`integer`	AI validations with result agree completed on this date.
`ai_validations_disagree`	`integer`	AI validations with result disagree completed on this date.
`ai_validations_unsure`	`integer`	AI validations with result unsure completed on this date.

Quick Download #

Download the full Hackensack, NJ daily stats time series in your preferred format:

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.