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.

An exploration of ROI, log-returns, and cash-flow adjustments, showing why logarithmic measures offer better comparability and how to treat long and short positions correctly in vectorized backtesting.

t-Test/Mann-Whitney-U-Test

Applied statistic lab

t-Test/Wilcoxon