scholarly journals COVID-19 open source data sets: a comprehensive survey

Author(s):  
Junaid Shuja ◽  
Eisa Alanazi ◽  
Waleed Alasmary ◽  
Abdulaziz Alashaikh
2020 ◽  
Vol 69 ◽  
pp. 88-97 ◽  
Author(s):  
Damien Leger ◽  
Christian Guilleminault

2015 ◽  
Vol 32 (18) ◽  
pp. 2693-2723 ◽  
Author(s):  
William S. Parkin ◽  
Jeff Gruenewald

To date, no discussion has taken place in the social sciences as to the appropriateness of using open-source data to augment, or replace, official data sources in homicide research. The purpose of this article is to examine whether open-source data have the potential to be used as a valid and reliable data source in testing theory and studying homicide. Official and open-source homicide data were collected as a case study in a single jurisdiction over a 1-year period. The data sets were compared to determine whether open-sources could recreate the population of homicides and variable responses collected in official data. Open-source data were able to replicate the population of homicides identified in the official data. Also, for every variable measured, the open-sources captured as much, or more, of the information presented in the official data. Also, variables not available in official data, but potentially useful for testing theory, were identified in open-sources. The results of the case study show that open-source data are potentially as effective as official data in identifying individual- and situational-level characteristics, provide access to variables not found in official homicide data, and offer geographic data that can be used to link macro-level characteristics to homicide events.


2018 ◽  
Vol 80 (6) ◽  
pp. 457-461
Author(s):  
Carlos A. Morales-Ramirez ◽  
Pearlyn Y. Pang

Open-source data are information provided free online. It is gaining popularity in science research, especially for modeling species distribution. MaxEnt is an open-source software that models using presence-only data and environmental variables. These variables can also be found online and are generally free. Using all of these open-source data and tools makes species distribution modeling (SDM) more accessible. With the rapid changes our planet is undergoing, SDM helps understand future habitat suitability for species. Due to increasing interest in biogeographic research, SDM has increased for marine species, which were previously not commonly found in this modeling. Here we provide examples of where to obtain the data and how the modeling can be performed and taught.


2018 ◽  
Vol 231 ◽  
pp. 1100-1108 ◽  
Author(s):  
Alaa Alhamwi ◽  
Wided Medjroubi ◽  
Thomas Vogt ◽  
Carsten Agert

Aerospace ◽  
2020 ◽  
Vol 7 (11) ◽  
pp. 158
Author(s):  
Andrew Weinert

As unmanned aerial systems (UASs) increasingly integrate into the US national airspace system, there is an increasing need to characterize how commercial and recreational UASs may encounter each other. To inform the development and evaluation of safety critical technologies, we demonstrate a methodology to analytically calculate all potential relative geometries between different UAS operations performing inspection missions. This method is based on a previously demonstrated technique that leverages open source geospatial information to generate representative unmanned aircraft trajectories. Using open source data and parallel processing techniques, we performed trillions of calculations to estimate the relative horizontal distance between geospatial points across sixteen locations.


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