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Data

Arguably, the most impactfull and comprehensive data dissemination resource about COV-19 epidemic was the one communicated by the report from Johns Hopkins' School of Engineering.

Dong, Ensheng, et al. “An Interactive Web-Based Dashboard to Track COVID-19 in Real Time.” The Lancet Infectious Diseases, Feb. 2020, doi:10.1016/S1473-3099(20)30120-1 [PMID:32087114].

This reference data resource is updated daily at the Whitting School of Engineering, Center for Systems Science and Engineering Center at Johns Hopkins University using GitHub. As a consequence of servind the data from the same git infrastructure where it is versioned, Github.com/CSSEGISandData/COVID-19 keeps both present and past versions of the reference daily updates and the time series records. The interoperability mechanism is now that of fecthing csv formated data as detailed in this pull request. As discussed below, the data ingestion and indexing is transferred to the clienct side enviornment, along the same lines outlined in Figure 1 of

Almeida JS, J Hajagos, J Saltz J, M Saltz (2019) Serverless OpenHealth at data commons scale—traversing the 20 million patient records of New York’s SPARCS dataset in real-time. PeerJ 7:e6230 [PMID:30671301].

CDC

A number of reference data assets are also emerging as part of public dashboards describing the development of the pandemic. They generaly follow the same approach of maintaining a static file, which the client application ingests in what becomes a reference visualization. This is illustrated, for example, by the map at the end of the coronavirus.gov page, which displays the data kept at cdc.gov/coronavirus/2019-ncov/map-data-cases.csv. As noted in teh reference above, this is an approach that shifts data ingestion and indexing in a database as a sitributed process handed to the Web Broser stack, which now includes both standard relational database and a state of the art assynchronous NOSQL data store, IndexedDB.