- Accessing the Exploration Canvas
- Overview of the Exploration Canvas
- Creating Derived Views
The Exploration Canvas is still undergoing active development. Changes to its interface will occur and new features will also be added over time. This article will be updated as changes are made. For more details on the Beta Program, check out this article.
The Exploration Canvas is a brand new platform surface for data exploration, data shaping, and derived view creation. It will be available to Open Data domains beginning October 2021, on an opt-in basis. If you are an Open Data domain administrator and would like to use the Exploration Canvas on your domain, please reach out to our Support Team at firstname.lastname@example.org.
The Exploration Canvas is inspired by the current Grid View, and is built to mirror and go beyond the capabilities of that surface. Specifically, the Exploration Canvas can:
Empower users to gain more meaningful insights from data, regardless of their technical skill level, by making advanced data shaping approachable in a new visual interface.
Reduce time spent on daily platform workflows by streamlining the steps from data exploration to view publication.
Support lightweight, read-only data exploration, making tabular data simpler to share and use.
Accessing the Exploration Canvas
During the beta, you can enter the Exploration Canvas through a banner that appears on all compatible assets. This banner will appear on the asset’s Primer page or in the Grid View:
Clicking “x” to collapse this banner will hide the banner on all assets for the remainder of your session.
Not all assets are eligible for use in the Exploration Canvas yet. The banner will only appear when an asset is compatible with this new surface.
Overview of the Exploration Canvas
The Exploration Canvas houses the tools users need to explore data, shape it, and create derived views.
The primary components of the Exploration Canvas are the data table and the Visual Query Editor. Here’s a base dataset loaded in the Exploration Canvas:
The rows and columns of data shown on the top portion of the page make up the data table. This data table can be scrolled (up and down, left and right), or paginated through, depending on the size of the dataset.
Clicking the kebab button in a column’s header will expand a menu with quick action options, and the column’s description:
On the bottom of the page, the Visual Query Editor includes three tabs which contain the Exploration Canvas' data shaping tools.
It’s easy to adjust the amount of space these tabs take up on the page. If you’d like to see more of the data table at once, or expand your view of the tabs, just click and drag to resize the section at the bottom of the page:
Visual Query Editor
The Filters, Group, and Column Manager tabs house a point-and-click visual data shaping interface. Altogether they are referred to as the Visual Query Editor (VQE).
This tab allows you to filter the data in your data table. To get started, select a column to filter on:
Then select the operator:
Finally, enter the value(s):
If needed, continue adding filters (using AND or OR):
Once you’re ready to apply your filters, click the “Apply” button on the bottom right:
The data table will update to show the results of your applied filter(s).
This tab allows you to group on dataset columns, as well as create aggregate columns. To get started, select a column to group:
To create an aggregate column, select the column to aggregate, and then select the calculation you want to use. Confirm the API fieldname for this new column (a default name will automatically appear here based on the column name and calculation type selected):
Column Manager Tab
This tab is where you can manage the columns in the data table.
Click and drag the icons under “Order” to customize the order columns appear in in the data table.
Use the checkboxes under “Include” to choose which columns to include in the data table.
Use the options under “Sort” to apply sorts to columns.
When sorting multiple columns, use the values under “Sort Order” to set the appropriate sort order.
If you have grouped any columns, the Column Manager will show only the columns available according to to the group(s) you have configured. Here’s an example:
Creating Derived Views
When first opening a published asset in the Exploration Canvas, you will see these options in the Asset Action Bar at the top of the page (whether or not you also see the “Edit” button depends on your permissions):
If you’d like to start building your own asset here, click “Create View” to create a new draft view. You’ll see a modal that prompts you to name your view before proceeding:
In the Exploration Canvas, you can explore published assets without having to create a draft first. This can help save time on performing ad-hoc exploration during during your day-to-day workflows.
To take advantage of this, simply start exploring or shaping your data with the VQE. As soon as you’ve applied your first configuration, you’ll see that the “Create View” option in the Asset Action Bar changes into “Save As”:
As soon as you’re ready to save your work, click “Save As.” This will open the same “Name Your View” modal pictured above.
If you do have unsaved work and navigate away from the Exploration Canvas, a modal will appear so that you can confirm whether or not you’d like to discard those unsaved changes:
Click “Cancel” to close the modal and continue using the Exploration Canvas.
Click “Discard changes” to discard your work and continue to your destination.
If you do want to save your work, enter a name in the text field and click “Save.”
Copy This Asset
A new “Copy This Asset” feature is also available for derived views opened in the Exploration Canvas (subject to permissions restrictions). Simply click the kebab button in the Asset Action Bar and select “Copy This Asset”:
A modal appears for you to name the new copy being created; after you submit a name, a draft of the duplicate asset will open in a new browser tab.
If you have any questions about the content of this article, please reach out to our Support Team at email@example.com.