The FAIR Scientific Knowledge eXchange (FSKX) Format is currently designed on the basis of the Food Safety Knowledge Exchange (FSKX) format that has been proposed and maintained by the RAKIP Initiative. The re-branding of the FSKX acronym has been proposed to allow a broad adoption of the FSKX format in other scientific disciplines like One Health and Artificial Intelligence. Additional information on the new FSKX features will be published here soon.

Food Safety Knowledge Exchange (FSKX) Format

Food safety risk assessments, control of food production processes as well as the development of new food products are nowadays supported by application of mathematical modelling and data analysis techniques. This creates an increasing demand for resources facilitating the efficient, transparent and quality proven exchange of relevant information, e.g. analytical data, mathematical models, simulation setting as well as simulated data. For example, new parameterized microbial models are frequently made publicly available only in written mode via scientific publications. However, in order to apply these models to a given practical decision support question (e.g. on the growth/no-growth of a microorganism in a specific food matrix under given processing conditions) the interested end-user would have to re-implement the model based on information provided in a publication. Here, it would be more efficient if those who create parameterized models could provide their model additionally as a file complying with a standardized file format that is also capable of transferring all relevant meta data. Such a file could e.g. be provided as a supplement to the publication and could be read-in by the end user’s software tools (thus overcoming an error-prone re-implementation process).

A first standardized file format has been proposed in the “Predictive Modelling in Food Markup Language (PMF-ML) Software Developer Guide”. This document describes in detail how experimental data and mathematical models from the domain of predictive microbial modelling (and beyond) can be saved and encoded in a software independent manner. With the Food Safety Knowledge Exchange (FSKX) Format we now extend the PMF-ML format to enable the exchange of knowledge / information that is embedded in specific script-based programming languages (e.g. “R”, Matlab, Python). I.e. the FSKX guidance document primarily aims at harmonizing the exchange of food safety knowledge (e.g. predictive models) including the associated meta data where this knowledge is only available in a software dependent format. The FSKX format therefore relaxes and adapts certain specifications of the PMF-ML format while at the same time maintaining the highest possible synergies between both formats. This will also help to make sure that food safety models encoded in a software independent manner (using PMF-ML) can easily be interpreted by FSKX format import and export software functions in the future.

Details about the FSKX format

FSKX guidance document

Developer guide:

FSKX guidance document (Version 3.1)

Supplementary information for the developer guide:

Supplements for the FSKX guidance document (Version 3.1)

FSKX Schema Editor:

https://jsb.starlingcloud.dev/index.html

Upcoming version (that is not yet officially released and supported by software tools)

Developer guide:

FSKX guidance document (Version 3.2)

Supplementary information for the developer guide:

Supplement of the FSKX guidance document (Version 3.2)

Examples

Example dose-response model: ExpDR

Example data file: ExpData

Schema

Metadata schema: YAML schema

Packages schema: YAML schema

Parameter schema: YAML schema

Tutorials

To help you get started and make the most of the FSKX format and the related FSK-Lab KNIME extension, we offer a range of in-depth video and written tutorials that guide you through everything from basic setup to advanced applications. Explore these resources to learn how to integrate, share, and utilize food safety models efficiently, and discover best practices for using the FSKX format across various scientific disciplines. Check out the detailed tutorials here.