Omed BioScience run several large-scale fermentation experiments a day leading to a high amount of time series results.

To accommodate these massive amounts of data, Omed BioScience have written a custom Scifeon data loader, which stores experiment results from each time point as a JSON string.

Afterwards, they use the Scifeon JavaScript API to interact with the database. This allows them to filter and extract data similarly to what can be done with SQL.

The above image shows an example of how to use the Scifeon API to extract data from the database.

Each object in the input list defines a set of search and filtering criteria - the first object finds and returns all database instances where the ID field matches the resultSetID variable.

The second object filters the database instances in the same way, but also performs a slicing operation on the time-series data in each row, returning just two columns and a limited set of rows.

Omed BioScience has customised their Scifeon instance for easy analysis of Fermentation timeline data. The custom elements are shown in the video below.