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Data Tables

Data tables provide scientists and data managers with a structured way to aggregate and analyse experimental data. They are designed in a format inspired by Structure–Activity Relationship (SAR) tables, enabling efficient comparison and interpretation of results across multiple experiments.

At a high level, a data table consists of:

  • Entities – records of a configured source data type, one row per record.
  • Columns – representing assay data sheet columns.

The table is populated using experimental data corresponding to the selected entities and assay columns. Filtering and aggregation settings determine which data are included and how they are presented.

Where multiple values exist for a given entity and assay column pair, the system applies an aggregation method. Supported aggregation methods depend on the column data type and may include: minimum, maximum, average, count, standard deviation, sum, comma-separated list, and latest updated.

If assays are associated with metadata, these values can be used as filters to refine the aggregated results. This makes it possible to focus on experiments with specific metadata characteristics. In addition, subject attributes can be displayed within the table to provide contextual information.

Once constructed, a data table can be explored interactively. Users can filter and sort the results, generate plots for visual analysis, and export the dataset as a CSV file for use in external analysis tools.

A data table

Clicking on a cell with experimental data opens a dialog showing all aggregated values. Clicking a row in this table will navigate to the Experiment data sheet.

Aggregated values table