In order for the pipeline industry to usher in the next-level fracture mechanics engineering analysis, reasonable and prudent fracture toughness characterizations are needed to improve burst pressure predictions and fatigue crack growth analysis of pipelines with planar cracks. Converting Charpy V-Notch (CVN) value to fracture toughness via different empirical correlation models derived throughout the years, while laudable, have inherent shortcomings. The main issues being that the Charpy toughness test is not a fracture mechanics-based measurement and the transferability of sub-scale fracture toughness testing is often not completely understood nor is correctly applied. This paper expands on these shortcomings and presents solutions which are supported by fracture toughness data obtained from the pipe boy and seam weld of API 5L line pipe steels. In this manner, best available toughness derivations for mean toughness in base metal and long seam welds are presented. Suggestions for standard fracture mechanics sub-scale coupon testing, such as ASTM E1820, on pipeline steel samples are delineated with rationale for each test type. The transferability of fracture toughness from sub-scale coupon testing results to that exhibits in full-scale pipe failure are demonstrated in the paper. This fracture toughness test database and other similar data sets can be combined and serve as the basis for establishing an industry wide Pipeline Material Database which would mirror established material databases in the aerospace industry such as NASGRO and AFMAT. It is envisioned that a centralized and validated Pipeline Material Database will be expanded to include fatigue crack growth rate data and other pipeline material characterization data sets. These data will support minimizing material assumptions and increase the accuracy of structural integrity predictions to improve the overall pipeline performance. This combined database would be accessible to engineers, analysts, and researchers and updated at regular intervals as more data becomes available.