Data curation during a pandemic and lessons learned from COVID-19

Kraemer, M. U. G.; Scarpino, S. V.; Marivate, V.; Gutierrez, B.; Xu, B.; Lee, G. H.; Hawkins, J. B.; Rivers, C.; Pigott, D. M.; Katz, R.; Brownstein, J. S.

Kraemer, M. U. G.; Scarpino, S. V.; Marivate, V.; Gutierrez, B.; Xu, B.; Lee, G. H.; Hawkins, J. B.; Rivers, C.; Pigott, D. M.; Katz, R.; Brownstein, J. S..

Nature Computational Science ; 1(1):9-10, 2021.

Article in English | Web of Science | ID: covidwho-2151133

ABSTRACT

ABSTRACT

Detailed, accurate data related to a disease outbreak enable informed public health decision making. Given the variety of data types available across different regions, global data curation and standardization efforts are essential to guarantee rapid data integration and dissemination in times of a pandemic.

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Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: Nature Computational Science Year: 2021 Document Type: Article

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