Abstract Modern research projects typically involve several measurement techniques and computational analyses, resulting in complex, multimodal research data objects. While the FAIR Principles provide a framework for making data Findable, Accessible, Interoperable, and Reusable, researchers must still apply community standards for each data type, where available. This challenge is particularly pronounced in computational analyses and workflows, where high methodological diversity makes it difficult to create meaningful FAIR Digital Objects that also capture experimental provenance. Such objects must describe the full research process by interlinking experimental and computational steps in a unified, queryable provenance model. The ISA framework captures laboratory protocols and processes, while computational analyses are described using workflow-centric models such as Workflow (Run) RO-Crate, which separate workflow definitions from execution traces. Despite conceptual similarities, these approaches remain largely disconnected. This paper presents the ARC Workflow Run RO-Crate profile, which aligns ISA-based experimental provenance with computational workflow and execution metadata in a single, standards-compliant container. It enables shared semantics and makes experimental assays and workflow runs interoperable within a coherent provenance graph interpretable by both ISA- and workflow-aware tools. At the same time, the profile harmonizes experimental and computational provenance and remains compatible with existing (Workflow) RO-Crate and ISA tooling ecosystems.
Ott et al. (Sat,) studied this question.