Set of tools to process raw instrument data according to a schema into a standardised form called datagram, annotated with metadata, provenance information, timestamps, units, and uncertainties. Developed by the Materials for Energy Conversion at Empa - Materials Science and Technology.

Capabilities:

• Parsing tabulated data using CSV parsing functionality, including Bronkhorst and DryCal output formats. Columns can be post-processed using any linear combinations of raw and processed data using the calibration functionality.
• Parsing chromatography data from gas and liquid chromatography, including several Agilent, Masshunter, and Fusion formats. If a calibration file is provided, the traces are automatically integrated using built-in integration routines.
• Parsing reflection coefficient traces from network analysers. The raw data can be fitted to obtain the quality factor and central frequency using several algorithms.
• Parsing potentiostat files for electrochemistry applications. Supports BioLogic file formats.

Features:

• timezone-aware timestamping using Unix timestamps
• automatic uncertainty determination using data contained in the raw files, instrument specification, or last significant digit
• uncertainty propagation to derived quantities
• tagging of data with units
• extensive schema and datagram validation using provided specifications
• mandatory metadata (such as provenance) is enforced

The full list of capabilities and features is listed in the project documentation.

Contributors:

• Peter Kraus
• Nicolas Vetsch