In the future, it is envisioned that a larger population of data can facilitate data-driven knowledge discovery activities through the utilization of data science or machine learning techniques. Figure shows the distribution of charge-carrier mobilities generated using data queried from OFET-db, showing the total spread and statistics of performance values for three relatively well-represented polymers in OFET-db: DPP-DTT, N2200, and P3HT. OFET samples fabricated from all individual polymer types show performance variations that span several orders of magnitude. The higher average and maximum charge-carrier mobility achieved for the DPP-DTT and N2200 data also reflects the general performance advantage of donor-acceptor copolymers versus the model homopolymer P3HT, even despite this large variation. Polymer material characteristics, such as molecular weight and polydispersity, are important factors in performance differences, as demonstrated by Figure . Molecular weight is a well-studied parameter for conjugated polymers in OFETs, and it is generally understood that longer conjugated backbones promote entanglements and aggregates in solution, and thereby enhance long-range molecular order and charge transport pathways in the thin film. The positive correlation between molecular weight and mobility is generally visible for P3HT and DPP-DTT, and variation in mobility for constant molecular weight is visible for all three polymers as similar polymer batches were used across experimental studies. A similar positive trend in mobility is visible for the polydispersity index (PDI), where devices made from a higher PDI polymer are more likely to have mobilities in the upper range of the dataset.