| --- |
| pretty_name: "Predictions \u2014 Google Community Mobility Reports \u2014 global daily" |
| license: other |
| tags: |
| - epi-eval |
| - predictions |
| - forecast-evaluation |
| - companion-of-global-mobility |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/*.parquet |
| --- |
| |
| # Predictions for Google Community Mobility Reports — global daily |
|
|
| Community-submitted forecasts targeting [`EPI-Eval/global-mobility`](https://huggingface.co/datasets/EPI-Eval/global-mobility). |
| Each row is one quantile (or point) forecast for one target date — see the |
| schema below. |
|
|
| This repo accumulates accepted submissions from many forecasters. New |
| predictions arrive as community pull requests opened from the [EPI-Eval |
| dashboard](https://github.com/ChrisHarig/apart-forecasting-tool); a |
| maintainer reviews each PR before merging. |
|
|
| ## Schema (v1) |
|
|
| | column | type | notes | |
| | --- | --- | --- | |
| | `target_date` | string (`YYYY-MM-DD`) | The date being forecast | |
| | `target_dataset` | string | Always `global-mobility` | |
| | `target_column` | string | Truth column being forecast (see below) | |
| | `submitter` | string | Forecaster name or HF username | |
| | `model_name` | string | Identifier for the model run | |
| | `description` | string | Free-form notes on the model | |
| | `quantile` | float (nullable) | In `[0, 1]`. `null` = point estimate | |
| | `value` | float | Forecast value (in the truth column's units) | |
| | `submitted_at` | string (ISO 8601) | UTC submission timestamp | |
| | _(pass-through dims)_ | string | Categorical dims from the source CSV | |
|
|
| Long format: one row per `(target_date, [dim values…], quantile)`. A |
| forecaster providing the median plus 50%/80%/95% intervals emits 7 rows per |
| date (one point + 6 quantiles). Multiple submissions from the same forecaster |
| land as separate parquet files under `data/`. |
|
|
| ## Forecast targets |
|
|
| Truth columns from `EPI-Eval/global-mobility` you can forecast: |
|
|
| - `retail_and_recreation` (percent change vs. baseline) |
| - `grocery_and_pharmacy` (percent change vs. baseline) |
| - `parks` (percent change vs. baseline) |
| - `transit_stations` (percent change vs. baseline) |
| - `workplaces` (percent change vs. baseline) |
| - `residential` (percent change vs. baseline) |
|
|
| ## Submitting |
|
|
| The dashboard at [apart-forecasting-tool](https://github.com/ChrisHarig/apart-forecasting-tool) |
| handles the full submission flow: drag-drop a CSV, pick this dataset as the |
| "Compare to" target, review your scores against the truth, and click "Submit |
| to HuggingFace." The dashboard serializes your CSV into the schema above and |
| opens a community PR here. |
|
|
| ## Notes |
|
|
| - Predictions whose `target_date` falls outside the truth dataset's coverage |
| (forecast horizon) are still accepted. Comparison metrics on the dashboard |
| compute only on the dates where truth is available. |
| - A submission's `submitter` value is its only identity claim — there's no |
| signed authentication. Reviewers should sanity-check unfamiliar submitters. |
|
|
| _Initialized by `upload_pipeline.core.bootstrap_predictions_repos`._ |
|
|
