Outstanding questions

Lifecycle-aware evaluation of biomedical data ecosystems

NoteOutstanding Questions
  • At what break-even point does the curation cost of a shared dataset get recovered by downstream reuse, and how should that point inform the decision to invest in further sharing versus letting a resource sunset?

  • As the data-citation gap persists, what KPI should replace raw citation counts as the primary measure of data-resource impact, and how do we collect it at portfolio scale without burdening individual projects?

  • How should cross-disciplinary co-authorship arising from a shared dataset be weighted relative to direct citation when evaluating a resource’s scientific influence?

  • What is the right cadence for re-assessing the FAIR maturity of an active data resource, who owns the re-assessment, and how do we keep the process tractable as portfolios grow?

  • As AI-driven and agent-based traffic on data portals continues to grow, how do we partition it into noise to remove versus signal to interpret as evidence of resource value?

  • What governance structures keep federated evaluation frameworks honest as they evolve, so that metrics continue to serve funders’ strategic questions rather than drifting toward data managers’ reporting convenience?