BIOMERO 2.0: end-to-end FAIR infrastructure for bioimaging data import, analysis, and provenance

2025-11-17

AI Summary

Current bioimaging analysis lacks an end-to-end platform compliant with FAIR principles and equipped with fine-grained provenance tracking, resulting in fragmented workflows and poor reproducibility. To address this, we propose a two-layer provenance architecture that deeply integrates OMERO throughout the entire data ingestion and analysis pipeline. Leveraging our custom BIOMERO library, OMERO.web plugins, and containerized analysis components, the platform enables full-chain traceability—from image acquisition and preprocessing to analysis and sharing. It supports automated workflow orchestration, rich metadata annotation, and high-throughput computing integration, ensuring real-time logging of parameters, software versions, and analytical results. Unlike existing solutions, this work is the first to embed native provenance capture directly into the analysis stage within the OMERO ecosystem. It significantly enhances data findability, interoperability, and reusability, providing foundational infrastructure for standardized, verifiable bioimaging research.

Technology Category

• Computer Vision: Medical and Biological Imaging
• Data Mining & Knowledge Management: Representing, Reasoning, and Using Provenance, Trust
• Knowledge Representation and Reasoning: Ontologies

Application Category

• Security and Privacy: Data transparency and provenance
• Web Mining and Content Analysis: Web data provenance, reliability, and authenticity
• Semantics and Knowledge: Provenance, trust, security and privacy, and ethical issues in managing semantic data

Abstract

We present BIOMERO 2.0, a major evolution of the BIOMERO framework that transforms OMERO into a FAIR-compliant (findable, accessible, interoperable, and reusable), provenance-aware bioimaging platform. BIOMERO 2.0 integrates data import, preprocessing, analysis, and workflow monitoring through an OMERO.web plugin and containerized components. The importer subsystem facilitates in-place import using containerized preprocessing and metadata enrichment via forms, while the analyzer subsystem coordinates and tracks containerized analyses on high-performance computing systems via the BIOMERO Python library. All imports and analyses are recorded with parameters, versions, and results, ensuring real-time provenance accessible through integrated dashboards. This dual approach places OMERO at the heart of the bioimaging analysis process: the importer ensures provenance from image acquisition through preprocessing and import into OMERO, while the analyzer records it for downstream processing. These integrated layers enhance OMEROs FAIRification, supporting traceable, reusable workflows for image analysis that bridge the gap between data import, analysis, and sharing.

Problem

• Creating FAIR-compliant infrastructure for bioimaging data management
• Integrating data import, preprocessing, and analysis workflows
• Ensuring comprehensive provenance tracking across imaging processes

Innovation

• Containerized preprocessing and metadata enrichment for import
• Containerized analysis coordination on high-performance computing systems
• Real-time provenance tracking through integrated dashboards