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The paper emphasizes the importance of strong data foundation principles, coupled with geoscience expertise, to drive scalable curation and integration technologies for subsurface data, and to speed up interpretation and informed decision making. It outlines the key processes which were implemented on a large-scale, multidisciplinary dataset, integrating up to 14 different data types over 250,000 discrete and interval samples covering 1,468 wells. Most of these data types are related to direct recovery of subsurface rock samples via either conventional cut coring or sidewall coring, which requires significant financial investment. The processes ensure the data is organized, harmonized, and transformed to maintain its usability, whilst also linking every dataset derived from a core sample back to its source for a seamless integrated analysis. This ensures the value of the investments are not eroded and allows experts to focus on data interpretation rather than spend most of their time wrangling and intersecting the data. What would take traditional data management months to achieve, now takes a matter of days and the speed and efficiency of insights generation increased by over 50%.