skills/fair-data/SKILL.md
# FAIR Data Principles — Findable, Accessible, Interoperable, Reusable ## Overview Guidelines for making scientific data FAIR: Findable, Accessible, Interoperable, and Reusable. ## Findable - Assign globally unique persistent identifiers (DOIs) to datasets - Rich metadata describing the dataset (title, authors, description, keywords, dates) - Metadata registered in searchable resources (DataCite, re3data, FAIRsharing) - Data indexed in domain-specific repositories ## Accessible - Data retriev
npx skillsauth add Zaoqu-Liu/ScienceClaw skills/fair-dataInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Guidelines for making scientific data FAIR: Findable, Accessible, Interoperable, and Reusable.
| Domain | Repository | |--------|-----------| | General | Zenodo, Figshare, Dryad | | Genomics | GEO, SRA, ENA | | Proteomics | PRIDE, MassIVE | | Structures | PDB, EMDB | | Clinical | ClinicalTrials.gov, YODA | | Chemistry | ChEMBL, PubChem | | Materials | NOMAD, Materials Cloud |
testing
Therapeutics Data Commons. AI-ready drug discovery datasets (ADME, toxicity, DTI), benchmarks, scaffold splits, molecular oracles, for therapeutic ML and pharmacological prediction.
tools
Genomic file toolkit. Read/write SAM/BAM/CRAM alignments, VCF/BCF variants, FASTA/FASTQ sequences, extract regions, calculate coverage, for NGS data processing pipelines.
development
Complete mass spectrometry analysis platform. Use for proteomics workflows feature detection, peptide identification, protein quantification, and complex LC-MS/MS pipelines. Supports extensive file formats and algorithms. Best for proteomics, comprehensive MS data processing. For simple spectral comparison and metabolite ID use matchms.
development
Multi-objective optimization framework. NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ), for engineering design and optimization problems.