DataTables

Silico supports multiple ways to source and use data within your projects, one of these is the DataTable element. DataTable elements can be used as an inline place to store data, suitable for either adhoc or small experiments. For more robust handling of data, DataTables can be used to import data from Sync into a project. Segmented data must also be imported using Sync and DataTables.

Feature Status

Some DataTable features are only available to organisations on silico.app and on private enterprise clusters. These features include importing data from Sync. Inline use of data using DataTables is possible on all accounts.

Creating a new DataTable

You can add a DataTable to your project, as another other element, by using the right-click menu, or by using the keyboard shortcut 'd'. Double-click on the DataTable element to step inside.

Inline DataTables

Once inside, you can add additional columns to the table using the + button.

The simplest way to populate a datatable is to copy and paste from a spreadsheet, with pasting multiple columns supported. Note that DataTables follow the time settings of your project, so make sure the rows in your spreadsheet correspond with the time steps of your project.

Once you've populated your DataTable, you can refer to its columns from other elements using the arrow syntax, e.g. "DataTable1"->"Column 2".

Importing Data from Sync

Enterprise and organisational users with access to Silico’s Sync area can use DataTables to make the content of their Sync Datasets available to Digital Twin projects.

Selecting the Sync Dataset

To integrate a Sync Dataset into a Digital Twin project, create a DataTable as described above and click into it. Use the dropdown in the top-left corner of the DataTable to select a Dataset set up in Sync. The “Manual” option provides the inline DataTable described above.

Configuring the Sync Dataset

Once selected, use the set-up button in the top-right corner to set up the DataTable. Initially, all columns of the Sync Dataset will be displayed in the left column of the set-up window.

Select the columns you want to import by ticking the box next to the column name. Where applicable, you must also distinguish between variable and segmentation columns by dragging segmentation columns into the right half of the set-up window. You need to assign a project segmentation to each of the segmentation columns. Thus, Dataset and project segmentations do not need to align. You also do not need to use all segmentation columns of a dataset, as the software will aggregate unused segmentation columns.

Click select “Save” to finish importing this Dataset into the project’s DataTable. You will now see the imported data. Time, as described in the project’s time settings, runs top-down. Each column reflects, respectively, a segment of a variable using a specified aggregation model. By clicking on one of the column headers, you determine if data is converted into a time series using summation, averaging, or both. Moreover, you can select if missing values are filled with zeros or by holding the last available value.

Referring to Imported Data

To use the imported data in a Digital Twin’s simulation elements, connect the DataTable to the variables, stocks, and flows they feed into. You can use the simulation elements’ formula field to refer to the DataTable using the syntax "DataTableName"->"VariableName”->”AggregationMode". The inspector’s autofill feature will help you in this process.

For segmented variables, ensure that the DataTable segmentations correspond to the referring variable's segmentations.

Refreshing Data

DataTables load data from the latest version of their Sync Dataset when accessing the model, refreshing the page, and clicking on the refresh button inside the DataTable.