WHAT IS IN THE FAIR TOOLKIT?

  • Why FAIR data matters for Life Science industry
  • Use cases to exemplify the benefits of FAIR implementation by Life Science industry
  • How-to methods for FAIR tools, training and change management
  • Tips for Life Science industry and links to relevant resources

WHO IS THE FAIR TOOLKIT FOR?

  • Data Stewards
  • Laboratory Scientists
  • Business Analysts
  • Science Managers

USE CASES

The Role of Curated Data in Accelerating the Identification of Putative Drug Targets for Cancer Immunotherapies – Elucidata

Elucidata tackles challenges in finding and reusing data through its curation app and custom curation of relevant data.

  • Reduced turnaround time; unlocked previously inaccessible datasets

  • Transformed target identification timeline in cancer immunotherapy

 

Find out more >

FAIR annotation and evaluation of RNA sequencing and microarray data – Elucidata

How to unlock the value of RNA sequencing (RNA-Seq) and microarray data from a public repository Gene Expression Omnibus (GEO)

  • Using machine-learning assisted curation, guided by the FAIR principles
  • Leverage ontologies and controlled vocabularies for annotation
Find out more >

FAIR Annotation of Bioassay Metadata – Pistoia Alliance

The Pistoia Alliance Bioassay FAIR Annotation project develops digital standards for bioassay metadata, provides annotations of bioassay method descriptions according to these standards, and makes them available publicly.

  • Proposed a minimal information model for assay metadata. It is now used by the FDA IVP project.
  • Annotated close to 2,800 previously published assay methods.

 

Find out more >

View all Use Cases >

METHODS

Accessibility Maturity Indicators

Learn how to apply the FAIR Maturity Indicators to measure the ACCESSIBILITY of the data and metadata.

  • Accessibility of data is compared with your FAIR objectives to identify and make improvements in an iterative manner
Find out more >

BYOD Datathon Workshops

Discover how these interactive events, guided by experts in data management, can provide a learning experience to improve the FAIRness of data brought by the participants.

  • Practical “hands-on” training to evaluate and make data more FAIR
Find out more >

FAIRification Workflow

Find out how a generic workflow can be deployed by workshops or action team to make important datasets FAIR.

  • FAIRification as a retroactive workflow is common at this time
  • FAIRification by design (data “born” FAIR) is far more desirable for the future
Find out more >

View all Methods >

CREATED BY LEADING LIFE SCIENCE ORGANISATIONS