
The goal of this deliverable was to develop approaches to integrate exposure to nutrients, chemicals, and additives in HEAP’s Information Commons and Knowledge Network.We gained access to the HEAP consortium’s secure GDPR-compliant HPC resources and successfully uploaded the developed purchase data pipeline described within. The pipeline was run in Hopsworks in a manual curated session at the BYOD data meeting (held in November 2022). Hopsworks is working on an R Studio implementation to be run directly from Hopsworks to ensure the pipeline can run on the HEAP platform. The next step is testing the same pipeline in R Studio through Hopsworks, which will be demonstrated during the next BYOD (to be held in late 2024). The pipeline is already available on GitHub and can run outside the Hopsworks environment.
R studio, research, machine learning, exposome, data analytics, consumer purchase data
R studio, research, machine learning, exposome, data analytics, consumer purchase data
