Work

A FAIR-compliant metadata template for ecosystem digital twins

Year: 2026

Type: article

Abstract: Integrating heterogeneous ecological, geographic, and environmental datasets is essential for building ecosystem digital twins and advancing predictive ecological research. Yet, data reuse remains constrained by inconsistent, non–machine-actionable metadata that limits interoperability across research infrastructures. To address this, we developed a FAIR-compliant metadata template—aligned with the principles of Findability, Accessibility, Interoperability, and Reusability—within the Dutch LTER-LIFE project, which is developing a research infrastructure for ecosystem digital twins. Our approach combines schema crosswalks of established standards, expert consultation, and community feedback to identify, harmonize, and prioritize essential metadata fields. The resulting core schema defines a minimum set of 23 mandatory metadata fields organized into seven thematic sections and mapped to two internationally recognized metadata standards, DCAT-AP and ISO 19115. Implemented in the CEDAR Workbench, the template produces machine-readable, linked-data records (JSON-LD) and incorporates controlled vocabularies and ontology services via BioPortal to support semantic consistency. Iterative testing and refinement improved clarity, usability, and applicability across ecological domains. Initial tests indicate that the template can be integrated with metadata catalogues, enabling automated population of searchable entries and supporting federated discovery and reuse. By balancing simplicity with semantic rigor, the template provides a consistent dataset-level foundation for documenting heterogeneous datasets and supports their integration into digital-twin workflows. This work demonstrates how community-driven, standards-based metadata solutions can operationalize FAIR principles and provide a transferable foundation for ecosystem digital twin applications across ecological research infrastructures.

Source: Ecological Informatics

DOI: 10.1016/j.ecoinf.2026.103983