Creating new dashboards
The dataset menu in the header contains a dashboard option. If no dashboard already exists for the current dataset, the option will display as "Create dashboard" (as shown below) whilst if a dashboard does already exist then it will display as "View dashboard".
Editors will see this menu option for all datasets, whereas viewers will only see it for datasets that have a dashboard enabled. Once a dashboard has been created, a "View dashboard" button will also be shown in the header for all users. If no dashboard exists already for the current dataset, the "Create dashboard" menu option will open a configuration panel for setting up a new dashboard.
Here, you can give your dashboard a custom name (which will then form part of the dashboard’s URL), choose the source of the dashboard display (a web-page of your choosing or a Crunch deck of saved analyses) and whether to make the dashboard the landing page of this dataset (default=true). In more detail...
This is the default – Users of this dataset will arrive at the Variable Summaries mode when entering a dataset, and no dashboard will be available.
Select URL to specify a custom URL that will be loaded as the dataset dashboard. This can be used to show any web-based content you host in another location, such as a Shiny dashboard built in R and hosted by Crunch. For more information about using on using Shiny with Crunch, see the “Crunchy” GitHub project and its instructions.
This is the most common choice. Select Deck to choose a deck to use as the source for a dashboard. Your dashboard will display the analyses (tables and graphs) that you have saved to your deck. See Saving, Exporting, and Sharing Analyses for instructions for how to save analyses to a deck. The selected deck will become shared (available to all users on the dataset) when it is used as a dashboard.
If you create the dashboard based on a deck that already has one or more analyses, you’ll see them displayed in the dashboard. If not, you'll be invited to switch to Tables and Graphs mode to save some analyses to your dashboard.
Once you have a dashboard, you can make changes to any of these settings by clicking the dataset name and selecting Configure Dashboard from the dropdown to re-open the dashboard configuration panel.
Dataset editors will see an “Edit” button in the top right corner of the dashboards view. Clicking this puts you into dashboard editing mode. When you enter edit mode, you'll find that each dashboard 'tile' gets its own edit button upon rollover which you can click to make changes to the contents of that tile. Note that a couple of visualization types are not yet editable, but this will be coming in the future. When you click to edit a dashboard tile, the slide-in panel that appears contains three tabs - Properties, Categories and Colors.
The Properties tab allows you to switch chart type, edit the tile title and the tile description (which displays as a subtitle). This allows you to give your dashboard tiles descriptive titles that draw attention to key points - a bit like the heading of a PowerPoint slide. You can change visualization type here too, though not all chart types will be available at once, depending on the number of dimensions in the current analysis. Other visualization types are planned for the future. If there's a particular kind you'd like to see, let us know at firstname.lastname@example.org.
The Categories tab lists all of the categories (and legend items in the case of a cross-tab) with checkboxes next to each. Simply uncheck any items you don't want to include in your dashboard chart, such as “Don’t know” and “None of these” options. The labels are editable which will enable you to avoid unsightly overlapping labels, and if you want to re-order them, simply drag them into the new order you want.
The Colors tab allows you to set colors of your choosing for each category (or legend item, as applicable). We intend to introduce a choice of color palettes in the future to make this stage quicker, but you can still make some great-looking charts in the meantime.
Moving and Resizing Tiles
When in edit mode, each tile can be dragged and dropped to place it somewhere else on a flexible 12-square grid. You’ll see that the other dashboard tiles simply move out of the way to accommodate the new position, making it really easy to get the layout you want.
Upon hover, the dashboard tiles also show a draggable corner (bottom right) that allows you to resize that tile. Some visualizations naturally look better larger, smaller, taller, wider, etc. so get creative and come up with some layouts that really make your data shine.
A Dedicated Dashboard Mode
The dashboards themselves have customizable names which are then reflected in the URLs (which makes it easier to return to them again in your browser history). Dashboards sit in a separate mode of the application which is more suitable for those users who only consume dashboards (though it's still easy to jump from the dashboard to the dataset when you want to via the “View Dataset” button in the header).
And finally, you get the choice of whether to make the dashboard view the start view of a dataset - i.e. whether a user arrives at the dashboard when they click on a dataset (the default) or whether they arrive at Browse mode (a.k.a. Variable Summaries mode). If no dashboard has been configured for a dataset, the user will always arrive into Browse mode.
Here are a couple of examples of the kinds of dashboards you can create in minutes using Crunch...