Integration Hurdles: Merging Research Data Management and eLabFTW

Effective Research Data Management (RDM) ensures that scientific data is findable, accessible, interoperable, and reusable, as outlined by the FAIR principles. While electronic laboratory notebooks (ELNs) like eLabFTW provide structured digital documentation of experimental workflows, integrating them into broader RDM frameworks remains a considerable challenge. The ARC framework, developed by DataPLANT under Germany's NFDI, provides a structured method for managing and annotating research data. Hosted on DataHUBs (GitLab instances), ARCs offer a predefined structure that consolidates all relevant data—raw, processed, and metadata—for projects of varying scales. A key strength of ARCs lies in their emphasis on metadata and ontology-based annotation via standardized templates, ensuring consistent interpretability and machine-readability. However, ELN systems like eLabFTW often struggle to fully support these principles due to a lack of standardized vocabularies and ontological integration, hindering interoperability and long-term data reuse. From a laboratory perspective, integrating eLabFTW into daily workflows necessitates balancing structured data entry with the flexibility required in dynamic research environments. In biological projects such as microbiome studies and synthetic community experiments, linking ELN records to ARC structures improves traceability and supports reproducibility across complex datasets. Connecting raw data, protocols, and metadata within a unified system is essential for multi-partner projects, where standardized documentation fosters collaboration and enhances the long-term value of data. Integrating ARCs with eLabFTW enhances data accessibility, security, and interoperability, contributing to a more robust research data management (RDM) system. However, a key challenge is systematically linking eLabFTW records with ARC-based structures. This requires implementing persistent, unique identifiers for reliable cross-referencing and structured tagging within eLabFTW to support efficient data retrieval and mapping. Achieving such integration also demands standardizing metadata schemas, data transfer processes, and ensuring compliance with authentication protocols. From a technical perspective, data extraction and synchronization between eLabFTW and ARCs pose further challenges. API calls must be optimized for real-time, secure data exchange, while discrepancies in data formats necessitate interoperability frameworks. Additionally, eLabFTW's flexible, user-driven data entry can result in structural inconsistencies that hinder integration. Addressing these issues is an ongoing collaboration between developers and users to establish standardized workflows that align eLabFTW functionalities with ARC requirements and FAIR principles. This paper explores the potential of eLabFTW to contribute directly to FAIR research data documentation captured in ARCs. Assessing the compatibility of eLabFTW records with ARC project requirements, the paper highlights both the opportunities and limitations of connecting these systems, focusing on integrating ontologies and controlled vocabularies. The challenges and possible solutions of streamlining research documentation from the outset to data publication reveal the gaps in eLabFTW and possibly other ELN implementations that must be addressed for truly FAIR-compliant research data management.