# Process Overview (Linear Pattern) Widget type: `opendash-widget-patternnotime` · Plugin: `@opendash/plugin-highcharts`  ## Description Plots the values of several selected dimensions side by side along the x-axis as a process profile rather than over time. Each historical record is drawn as a faint grey line across the chosen dimensions, and a bold blue "Mean" line shows the average value per dimension. This makes it easy to spot the typical shape of a multi-step process and how individual runs deviate from the average. The widget label is shown as "Process Overview in Days". ## Data requirements - Selection: one or more data item dimensions (`select: "dimension"`, min 1; no maximum). - Allowed value types: `Number`. - Data fetching: history is used and is required (`history: true`, `historyRequired: true`). Values are fetched per item over the dashboard history range (relative or absolute) with `historyType: "aggregate"`. ## Options This widget has no configurable options beyond data selection. (The settings panel is intentionally empty; the `ConfigInterface` declares `type`, `interval`, `aggregationGroup` and `aggregationOperation`, but none of these are exposed in the settings UI and the component does not act on them — the chart is always a multi-series line chart with a computed mean.) ## Presets - **Process Overview** — Visualizes daily or weekly patterns as circular chart or line. Ideal for identifying recurring patterns like peak loads or idle times. Default config: `type: "spline"`, `aggregationGroup: "hourOfDay"`, `aggregationOperation: "mean"` (these defaults are stored but not used by the component); layout `[6, 6]`, tag `chart`. ## How to use 1. Add the widget to a dashboard, or use the "Process Overview" preset in the Data Explorer. 2. Select one or more numeric data item dimensions — each becomes a category on the x-axis. 3. Set the dashboard history range; every record in that range is plotted as a grey reference line. 4. Read the bold blue "Mean" line to see the average value per dimension and compare individual runs against it.