Tools for FAIR and structured data

COMBINE bioassay protocol ontology

The COMBINE project developed a bioassay protocol ontology (BPO) that enables the conversion of unstructured bioassay protocol data into structured, machine-readable formats that promote reusability and allow an accurate description of in vivo efficacy study metadata for antibiotic agents.

Standardized and machine-readable bioassay metadata will enhance the reproducibility and usability of bioassays in antimicrobial resistance (AMR) associated antibacterial drug discovery and development. Standardizing entails mapping bioassay data to standard ontologies, either as study result output, or on the protocol level. The COMBINE BPO allows researchers to capture information regarding experimental details such as the type of mouse model, the bacterial strain, and the sex and growth phases of mouse and bacteria respectively from the protocol. The ontology is available for download through the Fraunhofer-ITMP GitHub repository.

FAIR data templates

The COMBINE project has developed a FAIRification framework that can facilitatee the practical implementation of FAIR principles. Tools include

  • A Data Survey that collects relevant project and data set information to set up a Data Management Plan that can serve as an input for Lab Data Template development.
  • Lab Data Templates facilitate the collection of AMR research data (in vivo and in vitro) in several sub-tables. The Excel format is compatible with upload procedures into the data repository ‘grit’ and serves as input for a knowledge graph workflow.
  • A Data Dictionary is connected to the Lab Data Templates and ensures harmonized data entries. In addition, the dictionaries collect metadata beyond the content of the Lab Data Template (e.g. bacterial strain information or compound information) and link to ontologies where possible.
  • FAIR assessments have been used as a primer for improving the template. This report is generated using the FAIR-DSM model.

The templates have been used during the IMI2 GNA NOW project to collect information and have been improved according to FAIR standards in collaboration with the IMI FAIRplus project (“post FAIRification”). By showcasing the feasibility and benefits of transitioning to FAIR data practices, this work aims to encourage broader adoption and integration of FAIR principles within a research lab setting. These tools for standardisation of data sets to allow for FAIR working and data reuse are available from Zenodo.

The grit scientific data management platform

FAIR data tools include the Open Source grit scientific data management platform.  The platform allows users to store, manage, and visualise your data across all pre-clinical drug discovery phases. In grit, all data modalities can be stored alongside pre-clinical assay data from in vitro, in vivo, DMPK, and toxicological data in SEND format.