Benchling In Vivo’s Data Tables provide a structured way to capture, organize, and analyze study data. They support multiple data types—including numeric values, timestamps, measurements, and formulas—so you can collect and review information in a consistent format. This guide walks through how to create and customize different types of data tables, how to use features like formulas, PK planning, and templates, and how to export results. Together, these tools help standardize data capture across studies while giving you the flexibility to adapt tables to your specific workflows.

Create data tables

You can create data tables from scratch or from a template if one has already been created. Templates are especially useful because they standardize data collection across your organization and significantly speed up data table setup.

There are three types of data tables. Timeseries and numeric tables are less flexible and purpose-built while custom tables are more flexible.

When creating a data table from a template, you may be required to complete additional configuration to ensure the template maps correctly to the measurements and dates in your current study.

• Measurement mapping: You must map measurement variables from your study Preset to the variables saved in the template. If the Preset variables match the template variables, the mapping will happen automatically and you will only need to review. If they do not match, you will need to perform the mapping manually.
• Reference date: Every data table template stores study days (not calendar dates) for each measurement and observation column saved in the template. When you create a data table from a template, you must select a reference date. This is used to calculate all corresponding calendar dates for the table. By default, the reference date is automatically set to the calendar date that ensures the original study day aligns with that saved in the data table. You can adjust the reference date to shift all column dates at once, or manually update individual column dates for more customization.

Note: Once a data table is created, you cannot edit column dates. To change them, delete the applicable column and add a new one.

Create a new data table 

1. Navigate to the Data Tables section within your study
2. Click Create new Data Table and select Add new
3. Enter a descriptive name for the table
4. Select the table type
5. Sort and select the animals to include
   • Note: Animals must be sorted into the desired order before creating the table; you cannot reorder animals after the table is created
6. Click Create to finalize setup

Create a data table from a template

1. Click Create new Data Table
2. Select Create using template
3. Select the desired template from the dropdown

4. Map the measurement columns, if required
5. Adjust the reference date, if needed
6. Sort and select the animals to include
   • Note: Animals must be sorted into the desired order before creating the table; you cannot reorder animals after the table is created
7. Click Submit  

Use the data table toolbar

The toolbar at the top of a data table provides quick access to key actions:

• Undo or redo actions
• Add rows (animals)
• Add columns
• Search for an animal using any identifier
• Configure navigation
• Save the table as a template
• Adjust which animal fields are displayed as columns

Keyboard shortcuts

You can also use shortcuts to work more efficiently in a data table:

• Select data
  • Click a column header to select an entire column
  • Click the primary animal identifier cell to select an entire row
  • Hold Shift + arrow keys to select multiple cells
  • Hold Shift + click to select a block of cells
• Move between cells
  • Tab: Move to the cell on the right
  • Enter: Move to the cell below
  • Arrow keys: Move in any direction

Delete rows

1. Hover over the animal name to reveal the Delete row button
2. Confirm deletion

Note: Deleted rows, including any saved data, can be restored by adding the animal back with the Add row button in the toolbar. Deleting a row with a measurement column removes it from the table but does not delete the underlying measurements from the associated animals, since these are saved automatically. If you add the row back, all applicable measurements for those animals will reappear. If you want to remove the measurement data as well as the row, delete the measurement data in the cells before removing the row.

Add columns to data tables

Once a data table is created, you can add, edit, and delete columns to capture the data you need. Editable columns can also be locked to prevent erroneous updates to the column after data entry is complete.

Add a column

1. Click Add column in the toolbar
2. Choose a column type
3. Enter a column name and configure any units or settings
4. Click Add column

Edit a column

1. Click the arrowhead in the column header
2. Select Edit to modify the name, units, or formula
3. Drag and drop column headers to reorder columns

Note: Measurement and observation columns cannot be edited. To change one, delete the column and create a new one with the desired parameters. If you want to remove the data as well as the column, delete the data in the column before removing it.

Lock a column

1. Click the arrowhead in the column header
2. Select Lock
3. Repeat the process and select Unlock to unlock the column

Delete a column

1. Click the arrowhead in the column header
2. Select Delete to remove the column
3. Confirm deletion

Note: Deleting a measurement column removes it from the table but does not delete the underlying measurements from the animals, since these are saved automatically. If you add the column back, all measurements for that day will reappear. If you want to remove the data as well as the column, delete the data in the column before removing it.

Capture data in columns

Once a column has been added to a data table, you can begin entering data. Each cell saves automatically when you leave it.

You can:

• Type values manually
• Copy and paste values into cells
• Use a connected instrument that outputs as a keyboard to transmit values into cells

Enter data

1. Click a cell and enter a value using your keyboard, copy-and-paste, or by writing a value from your connected device
2. Press Enter to save and move to the next row.
   • Note: Data is saved automatically when you leave the cell. If data is entered in an invalid format, an error message will appear.
3. Continue entering values across rows or columns as needed

Note: For timestamp cells, pressing Enter stamps the current datetime and advances to the next row.

Configure Navigation

Navigation in data tables helps you move quickly and consistently when entering data. 

You can configure it to define how animals are located (by scanning or selecting IDs) and where the cursor moves after each entry. This creates a clear, repeatable flow for searching animals and capturing data across multiple columns.

Configure Navigation

1. Click the Configure Navigation icon (curly arrow)
2. Choose a navigation method
   • Scanning an ID to scan or type in an animal ID to locate an animal
   • Choosing a specific column to automatically move to the next animal (row) after completing the configured columns for a row
3. Select the editable column where data capture should begin
4. Select Add step to include multiple columns in the flow (steps will occur in the order you add them)
5. Click Save to activate navigation
6. A blue circle will appear on the navigation icon when active

Edit Navigation

1. Reopen the Configure Navigation modal
2. Adjust as desired
3. Select Save

Use Navigation

1. If using Scanning an ID, a search field will appear to capture the Animal ID
   • Note: Any animal identifier is searchable in this field.
2. Enter data and press Enter to move to the next field
3. Complete all data entry fields
4. When prompted, enter or scan in the next Animal ID

Note: You can temporarily exit the navigation flow at any time by clicking outside of configured columns. To resume, click the Configure Navigation icon and select Save. 

To reset and exit Navigation

1. Click the Configure navigation icon (curly arrow)
2. Select Clear setup

Rename and delete data tables

Rename a data table

1. Navigate to the Data Tables section within your study
2. Click ••• at the end of the row for the table
3. Select Edit to update the table name

Delete a data table

1. Navigate to the Data Tables section within your study
2. Click ••• at the end of the row for the table
3. Select Delete to permanently remove the table

Note: Deleting a data yable is a permanent action. Measurements recorded in a data table are not deleted when the table is removed. If you also want to delete the measurements, you must delete them within the data table before deleting the table, or delete them directly from the animal page. All non-measurement data in the table will be permanently deleted.

Use custom data tables

Custom Data Tables are the most flexible type of data table in Benchling. Unlike Timeseries or Numeric tables, which are purpose-built for narrow use cases, custom tables allow you to combine multiple column types in a single table. This makes them well-suited for capturing and analyzing a wide range of study data. The following column types are available in custom data tables.

• Number: captures numeric values only
• Text: captures alphanumeric values
• Formula: displays the result of a custom formula built from other numeric and measurement columns using math operators
• Timestamp: captures a datetime timestamp
• Measurement: captures measurement values using the variables specified in the study Preset. If a measurement value already exists from data capture in Workflows or on the animal page, the column displays that value. A measurement column must be associated with a specific preset measurement variable and a specific date. These do not vary per row
• Observation: displays animal observations.  An observation column must be associated with a specific observation variable, score type, and a specific date. These do not vary per row
• Timestamp - PK Dose: plans and records timestamps for PK dosing across animals based on defined criteria
• Timestamp - PK Bleed: plans and calculates timestamps for PK bleeds across animals based on PK doses and other defined criteria

Measurement columns are the only column type that store data on the animal object itself, making the data viewable outside of the data table. All other column types store data only within the data table and are not accessible elsewhere.

Note: Contact Benchling Support to enable measurement or observation columns if they do not appear in your tenant.

Use formulas in custom Data Tables

Formula columns allow you to calculate values based on other data in the table. Formula columns must include a reference to at least one other column in the table. You can combine Number or Measurement columns using math operators (+, −, ×, ÷), however functions not clickable in the formula builder are not supported. 

Create a formula column

1. Click Add column and choose Formula
2. Enter a column name
3. Use the formula builder to construct the desired formula
4. Click Add column

Note: Values in a formula column cannot be edited directly, but you can copy them out. Errors may appear if the formula is invalid (e.g., “Syntax error at character X” or “At least one column must be selected”).

Use PK columns to plan study execution

PK studies require precise planning and execution to ensure no critical timepoints are missed. Animals are dosed, and bleeds are planned relative to those doses. Managing many dose and bleed times across multiple animals can make it easy to miss a clash, where extra lab support or adjustments to the study design may be needed. 

Custom data tables include PK-specific column types to help plan dosing and bleeds. These columns automate scheduling, flag potential conflicts, and provide structure for study execution.

Note: PK columns are for planning and tracking only. They do not record actual dose events or create samples tied to treatments and animals.

To manually connect planning with execution, you can add additional columns (such as Volume and Comments) to align with the bulk sample creation flow. This makes it easy to copy data directly from the Data Table into the bulk sample flow to create samples.

Create a PK Dose column

1. Click Add column > Timestamp: PK Dose
2. Set a start date and dose interval
3. Set a timestamp clash window to flag conflicts if desired
4. Select Add

Note: Dose columns are editable. To preserve data integrity, it’s recommended to lock dose columns after dosing. 

Create a PK Bleed column

Once you’ve created a PK Dose column, you can add a PK Bleed column. PK bleed times are automatically calculated based on the dose schedule. Bleed columns are not editable.

1. Click Add column > Timestamp: PK Bleed
2. If there are more than one PK Dose columns, specify the PK Dose column to reference for PK Bleed timestamp calculations
3. Enter Time from dose (e.g., 30m, 2h)
4. Select Add

Note: Actual bleed times should be logged in a separate, regular timestamp column as PK Bleed columns cannot be edited and are meant to display the planned bleed time only.

Identify and resolve time clashes

Clash detection requires at least one PK Dose and one PK Bleed column. For example, with a 2-minute clash window, a bleed scheduled within 2 minutes of a dose will trigger a warning. A timepoint clash warning is displayed using a yellow highlight for the applicable cells. To resolve the timepoint clash, adjust the future dose times to avoid clashes with bleed times. These warnings do not need to be formally resolved, however, and can be used as informative only for identifying times when you may need additional assistance in the lab.

Register Samples from Timestamp Columns

In addition to timestamp columns, you can add a numeric column for Volume and a text column for Comments to your data table. When these three columns (timestamp, volume, comments) appear in immediate sequence, you can copy and paste them directly into the bulk sample collection flow to create samples.

1. Open or create a custom data table for PK sample planning
2. Create a timestamp column for sample timestamp
3. Create a numeric column for volume
4. Create a text column for comments
5. Ensure the columns are ordered in immediate sequence as sample timestamp, volume, and finally comments
6. Copy the sample timestamp, volume, and comments columns
7. Begin the bulk sample collection flow
8. Paste the columns into the bulk sample collection table
9. Complete the sample creation

Note: To ensure the correct sample information is accurate for each animal, confirm that the animal order in the data table matches the order in the bulk sample collection table. Also verify that the volume units in sample collection are consistent with those recorded in the data table.

Use timeseries data tables

Timeseries data tables let you capture numeric data across multiple timepoints for each animal in a study. They are best for structured, repeated measurements over time that you do not need to have captured and stored against the animal outside of the datatable.

Example: Monitor blood glucose (mmol/L) every 10 minutes for 1 hour after feeding.

Note: Only numeric values can be entered. Data captured in timeseries tables is only accessible within the table itself—it is not viewable elsewhere in In Vivo or via Study Exports.

Set up a timeseries Data Table

When creating a data table, select Timeseries as the type. You must then choose how to define your timepoints:

• Automatic setup: Generate columns at regular intervals based on your settings
• Manual setup: Add each timepoint individually

Automatic setup

Complete the following fields when creating the data table:

1. Start: Enter the first timepoint (this becomes the first column header)
2. Every: Define the interval between timepoints
3. End: Define the last timepoint

Example:

• Start = 0 seconds
• Every = 10 seconds
• End = 60 seconds

This creates 7 numeric columns labeled 0s, 10s, 20s, 30s, 40s, 50s, and 60s.

You can add more timepoints later by clicking Add column in the toolbar. New columns will extend the sequence using the previously defined interval (e.g., 70s, 80s, etc.).

Manual setup

1. Specify your first timepoint
2. Click Add timepoint to add each additional column
3. Columns are added in the order specified

You can continue adding columns at any time to capture new or irregular timepoints.

Use numeric data tables

Numeric data table let you capture numeric data across a defined scale for each animal in a study. They are useful for structured, repeated measurements where the values do not need to be stored against the animal outside of the data table.

Example: Monitor blood glucose (mmol/L) across different environmental temperatures.

Note: Only numeric values can be entered. Data captured in numeric tables is only accessible within the table itself—it is not viewable elsewhere in In Vivo or via Study Exports.

Set up a numeric data table

1. When creating a data table, select Numeric as the type
2. Define the units for your numeric scale; these will become the column headers
3. Add numeric columns to the table
4. For each new column, enter the numeric value it represents. The predefined units will automatically be appended to the column title

Create Data Table Templates

Data Table Templates let you create, save, and reuse table structures across multiple studies. This improves efficiency and ensures consistency when working with data table in Benchling. Data Table Templates are created from existing data tables in a study. Templates are found and managed in each study under the Templates subtab of the Data Tables section. There are two types of templates:

• Personal templates: Created by you and only visible to you
• Published templates: Created and shared by an administrator; visible to everyone

Templates cannot be edited once saved. If you need to make updates, you should create a new template and delete the old one. To track changes and data table utility, consider adding version numbers to descriptive template names.

Create a data table template

1. Open the data table you want to save as a template
2. Click the Save as template icon

3. Enter a name for the template and click Save
4. The template will then appear in the Templates subtab of the Data Tables section of the study
5. [Admins only] To publish the template, click the ••• at the end of the row for the template and select Publish

Note: Templates cannot be edited after saving.

Create a new version of a data table template

1. Create a new data table using the original template
2. Make the desired updates
3. Save the updated table as a new template
4. Delete the old template

Rename a data table template

1. Navigate to the Data Tables section within your study
2. Select the Templates subtab
3. Click ••• at the end of the row for the template
4. Select Edit to update the template name

Delete a data table template

1. Navigate to the Data Tables section within your study
2. Select the Templates subtab
3. Click ••• at the end of the row for the template
4. Select Delete to permanently remove the template

Export data tables

While only measurement columns are incorporated into study data outside of data tables, you can still export an entire data table as an Excel file.

1. Open the desired Data Table
2. Select Export

Note: Exports include only the values stored in the data table. Underlying formulas are not exported.

Frequently asked questions

Q: Can I paste data from Excel?

A: Yes. Copy the data and paste directly into the grid. Formatting must match the column types.

Q: Can I export a data table?

A: Yes. You can export data tables as Excel files. Only stored values are exported—formulas are not included.

Q: Can I change the type of a column after it’s created?

A: No. You must delete the column and add a new one.

Q: Can I reorder animals in a data table?

A: No. Animals must be sorted before creating the data table. If you need a different order, delete the table and recreate it with the new animal order.

Q: What happens if I delete a data table?

A: Deleting a data table is permanent. Measurement data remains saved on the animal record, but all other data captured in the table will be lost.

Q: Can I apply formulas to summarize data across multiple animals?

A: No. Formulas work across columns and per row. They cannot summarize data across animals.

Q: Can I use non-numeric values in Timeseries or Numeric tables?

A: No. Timeseries and numeric tables only accept numeric values. For text or mixed data types, use a custom data table.