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FOREWORD
Introduction
What are the FAIR principles?
Ethical values of FAIR
Metadata and FAIR
Datasets to train on FAIRification
FAIR and Knowledge Graphs
Public Knowledge Graphs for Life Sciences
Selecting projects for FAIRification
Practical Considerations for a CRO to do FAIR
Glossary
FAIR RECIPES
Findability
1. Unique, persistent identifiers
2. InChI and SMILES identifiers for chemical structures
3. Minting identifiers with Minid
4. Depositing in Zenodo generic repository
5. Registering Datasets in Wikidata
6. Describe data by checksums
7. Validating data by checksums
8. Search engine optimization
8.9.1. Data page markup with Bioschemas
8.9.2. Dataset page markup with Schema.org
8.9.3. Data catalogue markup
Accessibility
1. Transferring data with SFTP
2. Downloading data with Aspera
Interoperability
1. Interlinking data from different sources
2. Identifier mapping with BridgeDb
2.11.1. Using BridgeDb web services
3. Introduction to terminologies and ontologies
4. Selecting terminologies and ontologies
5. Requesting new terms
6. Ontology-related tools and services
7. Building an application ontology with ROBOT
7.11.1. Competency questions for the Ontology ROBOT use case
7.11.2. Application ontology for metabolomics
8. Ontology mapping with Ontology Xref Service (OxO)
9. Creating a data/variable dictionary
10. Creating a metadata profile
10.4.1. Metadata profile for transcriptomics
10.4.2. Metadata profile validation in RDF
10.4.3. Bioactivity data profile
11. Converting from proprietary to open format
12. An inventory of tools for converting your data to RDF
13. File format validation, FASTQ example
14. Extraction, transformation, and loading process
15. Clinical Genetic Information as FHIR JSON
15.9.1. Converting VCF file to FHIR JSON
Reusability
1. Licensing
2. Software licenses
3. Data licenses
4. Declaring data's permitted uses
5. Provenance information
Infrastructure
1. Identifier resolution services
2. Creating resolvable identifiers
3. Building a catalogue of datasets
4. Deploying the IMI data catalogue
5. Vocabulary management
5.1. Portals and look-up services
5.2. Selecting a look-up service
5.3. Deploying the EBI OLS
6. Using OpenRefine and Karma for FAIRification
7. Developing FAIR API for the Web
Assessment
1. FAIR Evaluator tool
2. FAIRshake tool
FAIR Maturity
A Model To Gauge Dataset Maturity
Improving dataset maturity - the MIAPPE use case
Moving through maturity levels with ISA
Creating a basic ISA document
Making a community compliant - ISA in JSON
Moving to a semantically typed version - ISA in RDF
Packaging ISA as a Research Object (RO)
Making omics data matrices FAIR
1. Starting material
2. Structuring data
3. Exploring data with SPARQL
4. Integrating data
Making Computational Workflows FAIR
FAIRified Datasets
Applied examples
1. IMI eTox - toxicity datasets
2. IMI nd4bb - chemical activities datasets
3. IMI Oncotrack - clinical cohort datasets
4. IMI ReSOLUTE - transcriptomics datasets
5. IMI EHDEN-OHDSI
6. IMI EUBOPEN FAIR High-Content Screening data deposition
7. Mapping datasets to CDISC-SDTM
Tools
Search Wizard
AFTERWORD
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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Mapping of clinical trial data to CDISC-SDTM: a practical example based on APPROACH and ABIRISK
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