I spent years fighting RStudio's data viewer. Eventually I gave up and started dumping dataframes to CSV just to look at them properly. When Positron came out, I did what any reasonable person would do: I opened a dataframe, tried to filter it, and took notes. What I found was a neat little product paradox — more steps, better experience. As a certified Product Owner, I had thoughts.

The famous Iris dataset isn't FAIR—it's just a CSV. No persistent IDs, no ontology links, no provenance, no license. This proof-of-concept fixes that in an afternoon using Airtable and R. We structure the data relationally with taxonomic metadata (NCBI Taxonomy) and measurement ontologies (Plant Ontology), then auto-generate JSON-LD that meets all four FAIR principles. Each of 150 records gets a unique identifier and machine-readable semantics. The approach scales to clinical trials, genomics, or any tabular data. Code included. No enterprise tools required.

We used the mistral-large-latest large language model to automatically map AELLT (Lowest Level Term) entries to their corresponding MedDRA System Organ Class (SOC) using adverse event data from the PhUSE CS Working Group 5 CDISC pilot submission.