SmartWorks Panopticon - Plotting Line Graphs with Multiple Things Visualized

To visualize the ride data across multiple Things, the Data Table in your Workbook will need to be changed to accommodate for time-series data. Multiple ride Things’ data will be combined into one Data Table through the usage of Connectors. Connectors work similarly to SQL Joins/Unions and in this tutorial, we will do a Union All represented by two stacked boxes. Once the Data Table is set up, using Panopticon, a line graph will represent the sensor values across multiple ride Things over their ride duration.

  1. In the Data Table, click on the pencil icon to edit the Data Table.
  2. Click Transform Settings.
  3. Slide the Transform to enable time series analysis to On.
  4. Turn off the following two settings:
    • one time series per data row, or close
    • time series with time slices that don’t align
  5. For the To define the time axis values, Use field, use content.time elapsed.


    Figure 1.
  6. Add a second Thing by adding another Datasource. Follow the previous section on creating a New Data Table.


    Figure 2.
  7. Once the second Data Table is created, the two Data Tables need to be combined using a Connector. Click on the plug icon to choose a join/union option. In this case, we will click on the Union All icon represented by two stacked rectangles.


    Figure 3.
  8. Click Save.
  9. Return to the Dashboard and select your Data Table.
  10. Click and drag across the dashboard to create your first visualization.
    A side bar of different visualization graphs will appear.
  11. Select the Line graph under Timeseries Visualization.


    Figure 4.
  12. Once Line Graph is selected, drag your y-axis variable, content.humidity, to the Y icon.
  13. Drag content.uid to the Items icon to differentiate the data between the two Things.
  14. Drag content.uid to the Color icon to color code the two lines.


    Figure 5.
    The result should resemble a graph like the one shown below. With these basics, you can plot any variables you want and create visualizations that suit your needs.


    Figure 6.