Realising Data-Centric Scientific Workflows with Provenance-Capturing on Data Lakes

Abstract Since their introduction by James Dixon in 2010, data lakes get more and attention, driven the promise of high reusability stored due to schema-on-read semantics. Building on this idea, several additional requirements were discussed literature improve general usability concept, like a central metadata catalog including all provenance information, an overarching governance, or integration with (high-performance) processing capabilities. Although necessity for logical physical organisation order meet those is widely recognized, no concrete guidelines are yet provided. The most common architecture implementing conceptual zone architecture, where assigned certain depending degree processing. This paper discusses how FAIR Digital Objects can be used novel approach organize lake based types instead zones, they abstract implementation, empower generic portable capabilities provenance-based approach.