coordinated-data-views

# Coordinated Data Views Some data has more than one natural representation. A set of locations has both a map and a list. A dependency network has both a diagram and a node table. A dataset has both a chart and a raw table. When both representations are genuinely useful for different tasks, show them simultaneously and keep them synchronized — this is called a coordinated view. The core rule: **any selection or highlight made in one view is immediately reflected in the other.** --- ## When to Use Coordinated Views Use coordinated views when: 1. The two representations serve different tasks — the table is for finding/scanning; the visual view is for understanding arrangement or relationships 2. Users will frequently move between the two — not just glance at one occasionally 3. The dataset is large enough that the visual view alone doesn't identify individual items, and the table alone doesn't communicate how they relate Do not add a coordinated view purely for visual richness. If users only ever look at the table and ignore the visual view, it adds complexity without benefit. --- ## The Synchronized Selection Model Selection state is owned by a single shared store, not by either view. Both views read from and write to the same state. ``` Table row clicked → shared highlight state updated → both views re-render Visual element clicked → shared highlight state updated → both views re-render ``` **What synchronization covers:** | Interaction | Effect in table | Effe...