BEXIS2

BEXIS2 manages research data for biodiversity, ecology, and environmental science projects across the data lifecycle.

Key Features:

• Data lifecycle support: Supports data structure design, data collection, discovery, dissemination, integration, quality assurance, and research planning.
• Modular, extensible architecture: Provides a modular framework that can be customized and extended, including adaptations to database schemas and new functional modules.
• FAIR alignment: Implements principles of Findable, Accessible, Interoperable, and Reusable data management, with a self-assessment reporting strong conformance to Findability and Accessibility, moderate support for Interoperability, and partial Reusability.
• Scalability: Intended for mid- to large-scale projects with multiple sub-projects and support for up to several hundred researchers.
• Heterogeneous data integration: Handles fragmented and heterogeneous data formats and facilitates integration of diverse datasets.
• Tabular-data focus and adaptability: Initially focused on tabular data while providing a generic framework adaptable to other fields and data types.
• Data and artefact preservation: Supports secure storage and availability of raw data, metadata, processed data, software, code, and associated materials.
• Community deployments: Demonstrated capacity through community deployment examples across biodiversity and ecological research projects.

Scientific Applications:

• Biodiversity research: Management and integration of heterogeneous biodiversity datasets, including tabular data.
• Ecology research: Support for ecological datasets across data collection, quality assurance, integration, and dissemination activities.
• Environmental sciences: Management and publication of environmental research data across the research lifecycle.
• Collaborative research projects: Coordination and data management for projects composed of multiple sub-projects and large numbers of researchers.
• FAIR-aligned data publication: Enabling data publication and dissemination in line with FAIR principles.

Methodology:

Provides modular software components for data structure design, collection, discovery, dissemination, integration, and quality assurance within a modular, extensible architecture.