The FAIR Cookbook
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FOREWORD

  • Introduction
  • Introducing the FAIR Principles
  • Reflecting on the ethical values of FAIR
  • Introducing our FAIRification framework
  • Prioritizing projects for FAIRification
  • Framing FAIR and the notion of metadata
  • Understanding the relation between FAIR and Knowledge Graphs
  • Training for FAIRification with open or synthetic biomedical datasets
  • Raising Awareness in Public Knowledge Graphs for Life Sciences
  • Reflecting on Practical Considerations for CROs to play FAIR
  • Data Protection Impact Assessment and Data Privacy
  • Glossary

Recipes at a Glance

  • All Recipes In a Table

FAIR RECIPES

  • Findability
    • 1. Introducing unique, persistent identifiers
    • 2. Creating InChI & SMILES identifiers for chemical structures
    • 3. Creating InChIKeys for IUPAC names
    • 4. Minting identifiers with Globus Minid client
    • 5. Depositing to generic repositories - Zenodo use case
    • 6. Registering datasets with Wikidata
    • 7. Creating file checksums
    • 8. Validating checksums to verify file integrity
    • 9. Introducing Search Engine Optimization (SEO)
      • 9.9.1. Marking up Data pages with Schema.org & Bioschemas for SEO
      • 9.9.2. Marking up Dataset page with Schema.org & Bioschemas for SEO
      • 9.9.3. Marking up Data Catalogue page with Schema.org & Bioschemas for SEO
  • Accessibility
    • 1. Transferring data with SFTP protocol
    • 2. Downloading data with Aspera protocol
  • Interoperability
    • 1. Registering SwissLipids identifiers in Wikidata
    • 2. Interlinking data from different sources
    • 3. Mapping identifiers with BridgeDb
      • 3.11.1. Mapping identifiers using BridgeDb web services
    • 4. Introducing terminologies and ontologies
    • 5. Selecting terminologies and ontologies
    • 6. Requesting new terms from terminologies and ontologies
    • 7. Introducing ontology-related tools and services
    • 8. Building an application ontology with ROBOT
      • 8.11.1. Building an application ontology for metabolomics - MSIO
      • 8.11.2. Defining competency questions for the Ontology ROBOT use case
    • 9. Mapping Ontologies with OxO, EBI Ontology Xref Service
    • 10. Creating a data/variable dictionary
    • 11. Creating a metadata profile
      • 11.5.1. Outlining a metadata profile for transcriptomics
      • 11.5.2. Building a community compliant metadata profile - The Covid19 sample profile use case
      • 11.5.3. Outlining a metadata profile for Bioactivity data
    • 12. Converting from proprietary to open format
    • 13. Validating file format - FASTQ example
    • 14. Inventorying tools for converting data to RDF
    • 15. Surveying extraction, transformation, load (ETL) tools
    • 16. Expressing Clinical Genetic Information as FHIR JSON
      • 16.9.1. Converting VCF file to FHIR JSON
    • 17. Creating knowledge graphs from unstructured text
      • 17.12.1. unstructured text to graph as executable notebook
  • Reusability
    • 1. Licensing
    • 2. Licensing Software
    • 3. Licensing Data
    • 4. Declaring data permitted uses
    • 5. Introducing Provenance Information
  • Infrastructure
    • 1. Introducing identifier resolution services
    • 2. Creating resolvable identifiers
    • 3. Building a catalogue of datasets
    • 4. Introducing the DATS model
    • 5. Deploying a data catalogue - The IMI data catalogue example
    • 6. Vocabulary management
      • 6.1. Introducing vocabulary portals and lookup services
      • 6.2. Selecting an ontology lookup service
      • 6.3. Deploying EBI Ontology Loopkup Service
    • 7. Using OpenRefine and Karma for FAIRification
    • 8. Developing FAIR API for the Web
  • Assessment
    • 1. Assessing with FAIR Evaluator
    • 2. Assessing with FAIRshake

FAIR Maturity

  • Changing culture with the Dataset Maturity Model
    • Improving dataset maturity - the MIAPPE use case
    • Moving through maturity levels with ISA
      • Minimal Data Maturity with ISA - ISA-Tab and free text
      • Enhanced Data Maturity with ISA - ISA-JSON and ontology markup
      • Moving to a semantically typed version - ISA-JSON-LD
      • Dissemination - Packaging ISA as a Research Object (RO)
    • Making an omics data matrix FAIR
      • FAIRifying Data Matrices - Step1 - Starting material
      • FAIRifying Data Matrices - Step2 - Structuring data
      • FAIRifying Data Matrices - Step3 - Exploring data with SPARQL
      • FAIRifying Data Matrices - Step4 - Integrating data
    • Making Computational Workflows FAIR

FAIRified Datasets

  • Applied examples
    • 1. IMI eTox - toxicity datasets
    • 2. IMI nd4bb - chemical activities datasets
    • 3. Readying IMI Oncotrack - clinical cohort datasets for deposition to EBI Biosamples
    • 4. Depositing IMI ReSOLUTE transcriptomics datasets to EBI repositories
    • 5. Enhancing discoverability of EHDEN OHDSI data with Schema.org markup
    • 6. Depositing IMI EUBOPEN High-Content Screening data to EBI BioImage Archive
    • 7. Mapping IMI APPROACH datasets to CDISC-SDTM standard

AFTERWORD

  • Lessons learned from the FAIR journey and project outlook

GLOSSARY

  • Glossary of terms and abbreviations

JOIN US

  • Community
    • Boards and contributors
    • Code of conduct
    • Platform
      • Leveraging the Turing Way Book
  • Contribute
    • 1. How to contribute
    • 2. Add via GoogleDoc
    • 3. Add via HackMD
    • 4. Add via Git
    • 5. Git recipe template
    • 6. Tips and tricks
    • 7. Markdown cheatsheet
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Glossary Findability
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  • Contact us
  • FAIRplus
  • Contributors
  • How to contribute
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The FAIR Cookbook is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.