sub1:assertion {
sub1:comparatorGroup dcterms:description "Traditional data sharing via bilateral agreements and data transfer, federated analysis without cryptographic protection, analysis restricted to national boundaries only, and trusted third-party data intermediaries" .
sub1:interventionGroup dcterms:description "Privacy-preserving computation approaches enabling joint analysis without raw data transfer, including secure multi-party computation (MPC/SMPC), trusted execution environments (TEEs/secure enclaves), homomorphic encryption (FHE, PHE), federated analytics, and differential privacy for cross-border aggregates" .
sub1:outcomeGroup dcterms:description "Analytical capability for transboundary environmental assessments (accuracy, completeness, timeliness), compliance with data sovereignty requirements and national legislation, computational feasibility (latency, cost, scalability), trust establishment and governance complexity, and operational sustainability" .
sub1:population dcterms:description "Satellite-derived environmental monitoring data requiring cross-border sharing for regional and global analysis, including transboundary deforestation monitoring, shared watershed water quality assessment, cross-border air pollution tracking, migratory species monitoring, regional climate analysis, and disaster response coordination across national boundaries" .
sub1:privacy-preserving-computation-for-cross-border-ea pico:comparatorGroup sub1:comparatorGroup ;
pico:interventionGroup sub1:interventionGroup ;
pico:outcomeGroup sub1:outcomeGroup ;
pico:population sub1:population ;
dcterms:description "For transboundary environmental monitoring requiring satellite data from multiple jurisdictions, how do cryptographic privacy-preserving computation approaches compare to traditional data sharing mechanisms in enabling regional analysis while respecting data sovereignty requirements?" ;
a pico:PICO ,
sciencelive:EffectivenessResearchQuestions ;
rdfs:label "Privacy-Preserving Computation for Cross-Border Earth Observation Data Sharing: A Scoping Review" .
}