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New challenges and requirements for the management of environmental data require improved data interoperability, data integration and data sharing.
Thus, data require a range of concerted effort.
The complexity of the data require the use of novel data science techniques to be used.
Interpretation of the resulting complex data require diverse statistical and mathematical methods.
Proteomics as all high throughput omics data require extensive scrutiny of statistical analysis.
These data require validation and may inform trial design and therapy.
Simulation of the IceCube detector and processing of data require a significant amount of computational resources.
The executives point out that things like data copies of the human genome, oil reservoirs and sales data require immense storage systems.
The spectral data require accurate radiometric calibration with regard to the increasing degradation of the instrument with time.
Interchange, storage, and management of geological data require the development of knowledge-based, standardized vocabularies and data structures.
Single nuclide minimum exposure age data require that the tors have survived at least two complete glacial cycles.
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