FAIR Data and Software Management in the Process Industry

In highly regulated sectors such as the process industry, the lack of standardized, well-documented data poses a significant barrier to transparency, reproducibility, and regulatory approval. This work showcases how combining contributions from five NFDI consortia - NFDI4Cat, NFDI4Chem, NFDI4ING, DAPHNE4NFDI, and NFDIxCS - can unlock added value and support regulatory readiness, and illustrates how interoperable building blocks can support a FAIR, future-ready data ecosystem for industrial applications in the process industry, as is shown in Figure 1. NFDI4Cat and NFDI4ING promote data interoperability and reuse in modular process plants through cooperative initiatives like the ENPRO-REUNION project, where TU Darmstadt and Industrial Science developed the Semantic PEA Data sheet (SPEAD) - a semantic graph-based documentation format for Process Equipment Assemblies (PEAs) integrated into the Asset Administration Shell (AAS) [1]. SPEAD captures technical and process-relevant data in a machine-readable, standardized format, enabling digitalized plant documentation and fostering synergies with other modularization efforts. NFDI4ING promotes SPEAD development by providing tools for handling heterogeneous data and creating FAIR metadata templates. NFDI4ING also introduced Sensor Interfacing Language (SOIL), a domain-specific meta-model that captures sensor data semantics and communication. At TU Dortmund, a collaboration between ENPRO and NFDI4Cat is developing a core metadata model that complements SPEAD by linking core-engineering data to research from catalysis science. This includes reusing metadata4ing and domain terminology such as STRENDA biocatalysis guidelines, and contributes to joint efforts with NFDI4Chem on a central metadata model for improved data discoverability. For the preceding lab development, NFDI4Chem offers smart lab solutions for fully digital workflows. The open-source Electronic Lab Notebook (ELN) Chemotion [2], which is already used successfully in the chemical industry, allows automated data acquisition, analysis and management. Further, the LabImotion extension [3] adds customized functionalities, enabling the implementation of workflows from catalysis - together with NFDI4Cat and CRC1441 TrackAct - and research at large data facilities - together with DAPHNE4NFDI and ROCK-IT. In the context of large-scale facilities, DAPHNE4NFDI evaluates [4] and integrates automation systems [5], sensors, digital twins and comprehensive datasets into a coherent workflow, and also exerts formative influence on the development of products like BlueSky Automation, SciCat, and LabImotion. Concurrently, it advances its own suite of analytical tools, such as AIXtal Refinement Platform for First-Time Users [6] and SNIP, a collaborative ELN that unifies digital excerpts with handwritten annotations, schematic illustrations, and FAIR-compliant metadata capture [4], thereby establishing fully interoperable, reproducible and reusable digital research at large scale infrastructures. In the future, the Research Data Management Container (RDMC) by NFDIxCS could offer another useful toolbox to package all necessary artifacts from various domains, such as software, data, and their context through a predefined workflow [7]. This could further be enhanced by emerging common metadata standards of One NFDI. RDMCs act as time capsules, ensuring that all artifacts remain unchangeable. An initially constructed Reusable Execution Environment (REE) can be used to unpack the artifacts and rerun the experiment in a predefined environment.