Key references

Lifecycle-aware evaluation of biomedical data ecosystems

NoteKey References
  1. Wilkinson MD et al. The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 2016 [1]. The foundational definition of the principles that anchor the scientific-quality framework throughout this paper.

  2. Wilkinson MD et al. A design framework and exemplar metrics for FAIRness. Scientific Data, 2018 [2]. Operationalizes FAIR as machine-measurable indicators, which is what makes automated FAIR-compliance monitoring tractable at the portfolio scale we describe.

  3. Tedersoo L et al. Data sharing practices and data availability upon request differ across scientific disciplines [3]. Provides the bibliometric evidence that fewer than 30% of secondary analyses formally cite source data, the core empirical basis for our argument that citation-count KPIs systematically understate reuse.

  4. The GTEx Consortium. The Genotype-Tissue Expression (GTEx) project. Nature Genetics, 2013 [4]. The paradigmatic example of a high-reuse public biomedical data resource (8,630 citations as of January 2026), used here to anchor the public-value framework with a concrete case.

  5. Centers for Disease Control and Prevention. Standard Evaluation Framework for Large Health Care Data [5]. The 49-attribute fitness-for-purpose framework whose representativeness and linkability attributes are particularly load-bearing for federated ecosystems like the CFDE.

References

1.
2.
Wilkinson, M.D. et al. (2018) A design framework and exemplar metrics for FAIRness. Sci Data 5
3.
4.
Lonsdale, J. et al. (2013) The Genotype-Tissue Expression (GTEx) project. Nat Genet 45, 580–585
5.
El Burai Felix, S. et al. (2024) A Standard Framework for Evaluating Large Health Care Data and Related Resources. MMWR Suppl. 73, 1–13