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10.1016/S2542-5196(21)00196-0 http://scihub22266oqcxt.onion/10.1016/S2542-5196(21)00196-0 34562356!8457912!34562356     free     free     free Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\34562356.jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Lancet+Planet+Health 2021 ; 5 (10): e746-e750 Nephropedia Template TP {{tp|p=34562356|t=2021. Liberating host-virus knowledge from biological dark data |pdf=|usr=}}{{34562356}} gab.com Text Liberating host-virus knowledge from biological dark data JO: Lancet Planet Health http://www.kidney.de/pget.php?&tw=1&pmid=34562356 #FOAvip Connecting basic data about bats and other potential hosts of SARS-CoV-2 with their ecological context is crucial to the understanding of the emergence and spread of the virus. However, when lockdowns in many countries started in March, 2020, the world's bat experts were locked out of their research laboratories, which in turn impeded access to large volumes of offline ecological and taxonomic data. Pandemic lockdowns have brought to attention the long-standing problem of so-called biological dark data: data that are published, but disconnected from digital knowledge resources and thus unavailable for high-throughput analysis. Knowledge of host-to-virus ecological interactions will be biased until this challenge is addressed. In this Viewpoint, we outline two viable solutions: first, in the short term, to interconnect published data about host organisms, viruses, and other pathogens; and second, to shift the publishing framework beyond unstructured text (the so-called PDF prison) to labelled networks of digital knowledge. As the indexing system for biodiversity data, biological taxonomy is foundational to both solutions. Building digitally connected knowledge graphs of host-pathogen interactions will establish the agility needed to quickly identify reservoir hosts of novel zoonoses, allow for more robust predictions of emergence, and thereby strengthen human and planetary health systems. Twit Text FOAVip Liberating host-virus knowledge from biological dark data ????Lancet Planet Health http://www.kidney.de/pget.php?&tw=1&pmid=34562356 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34562356 #FOAvip English Wikipedia <ref>{{Cite pmid|34562356}}</ref> Liberating host-virus knowledge from biological dark data #MMPMID34562356 Upham NS; Poelen JH; Paul D; Groom QJ; Simmons NB; Vanhove MPM; Bertolino S; Reeder DM; Bastos-Silveira C; Sen A; Sterner B; Franz NM; Guidoti M; Penev L; Agosti D Lancet Planet Health 2021[Oct]; 5 (10): e746-e750 PMID34562356show ga Connecting basic data about bats and other potential hosts of SARS-CoV-2 with their ecological context is crucial to the understanding of the emergence and spread of the virus. However, when lockdowns in many countries started in March, 2020, the world's bat experts were locked out of their research laboratories, which in turn impeded access to large volumes of offline ecological and taxonomic data. Pandemic lockdowns have brought to attention the long-standing problem of so-called biological dark data: data that are published, but disconnected from digital knowledge resources and thus unavailable for high-throughput analysis. Knowledge of host-to-virus ecological interactions will be biased until this challenge is addressed. In this Viewpoint, we outline two viable solutions: first, in the short term, to interconnect published data about host organisms, viruses, and other pathogens; and second, to shift the publishing framework beyond unstructured text (the so-called PDF prison) to labelled networks of digital knowledge. As the indexing system for biodiversity data, biological taxonomy is foundational to both solutions. Building digitally connected knowledge graphs of host-pathogen interactions will establish the agility needed to quickly identify reservoir hosts of novel zoonoses, allow for more robust predictions of emergence, and thereby strengthen human and planetary health systems. |*COVID-19/epidemiology/virology[MESH] |*Host Microbial Interactions[MESH] |*Information Storage and Retrieval[MESH] |Animals[MESH] |Humans[MESH] |SARS-CoV-2[MESH]Liberating host-virus knowledge from biological dark data (epmc).pdf DeepDyve Pubget Overpricing