First three months of COVID-19 in Croatia, Slovenia, Serbia and Federation of Bosnia and Herzegovina

The uncertainty surrounding the emerging coronavirus threat prompted countries to adopt various disease control measures (DCMs). This study compares the DCMs and the epicurves in Croatia, Slovenia, Federation of Bosnia and Herzegovina and Serbia in the first three months of COVID-19 epidemic. The open-source data of COVID-19 confirmed case and the DCMs were analyzed. For comparison between countries, seven benchmark DCMs were used: closure of educational institutions, complete lockdown, borders closure, public transport ban, restriction of movement within the country, easing of the lockdown measure, and the borders re-opening. The time passed from the first detected and confirmed COVID-19 case and each DCM was recorded as well as the time between the epidemic declaration and each DCM. The results describe comparatively the time flow of the DCMs across the countries and relative to the number of confirmed cases.

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Chinese Open Source Data Collection, Big Data, And Private Enterprise Work For State Intelligence and Security: The Case of Shenzhen Zhenhua

SSRN Electronic Journal ◽

10.2139/ssrn.3691999 ◽

2020 ◽

Author(s):

Christopher Balding

Keyword(s):

Big Data ◽

Data Collection ◽

Open Source ◽

Private Enterprise ◽

Open Source Data ◽

Source Data

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Development and user experiences of an open source data cleaning, deduplication and record linkage system

ACM SIGKDD Explorations Newsletter ◽

10.1145/1656274.1656282 ◽

2009 ◽

Vol 11 (1) ◽

pp. 39-48 ◽

Cited By ~ 20

Author(s):

Peter Christen

Keyword(s):

Open Source ◽

Record Linkage ◽

Data Cleaning ◽

User Experiences ◽

Open Source Data ◽

Source Data

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A cross-city exploratory analysis of the robustness of bus transit networks using open-source data

Physica A Statistical Mechanics and its Applications ◽

10.1016/j.physa.2021.126133 ◽

2021 ◽

pp. 126133

Author(s):

Tao Jia ◽

Wenxuan Liu ◽

Xintao Liu

Keyword(s):

Open Source ◽

Exploratory Analysis ◽

Transit Networks ◽

Bus Transit ◽

Open Source Data ◽

Source Data

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NYenviroScreen: An open-source data driven method for identifying potential environmental justice communities in New York State

Environmental Science & Policy ◽

10.1016/j.envsci.2021.07.004 ◽

2021 ◽

Vol 124 ◽

pp. 348-358

Author(s):

Michael Petroni ◽

Sarah Howard ◽

I. Brielle Howell ◽

Mary B. Collins

Keyword(s):

New York ◽

Environmental Justice ◽

Open Source ◽

New York State ◽

Data Driven ◽

York State ◽

Open Source Data ◽

Source Data

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Using Open-Source Data in Correlative Species Distribution Modeling of Marine Species

The American Biology Teacher ◽

10.1525/abt.2018.80.6.457 ◽

2018 ◽

Vol 80 (6) ◽

pp. 457-461

Author(s):

Carlos A. Morales-Ramirez ◽

Pearlyn Y. Pang

Keyword(s):

Open Source ◽

Species Distribution ◽

Open Source Software ◽

Species Distribution Modeling ◽

Science Research ◽

Marine Species ◽

Distribution Modeling ◽

Open Source Data ◽

Rapid Changes ◽

Source Data

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.

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Modelling urban energy requirements using open source data and models

Applied Energy ◽

10.1016/j.apenergy.2018.09.164 ◽

2018 ◽

Vol 231 ◽

pp. 1100-1108 ◽

Cited By ~ 11

Author(s):

Alaa Alhamwi ◽

Wided Medjroubi ◽

Thomas Vogt ◽

Carsten Agert

Keyword(s):

Open Source ◽

Energy Requirements ◽

Open Source Data ◽

Source Data ◽

Urban Energy

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Method to Characterize Potential UAS Encounters Using Open Source Data

Aerospace ◽

10.3390/aerospace7110158 ◽

2020 ◽

Vol 7 (11) ◽

pp. 158

Author(s):

Andrew Weinert

Keyword(s):

Open Source ◽

Unmanned Aircraft ◽

Unmanned Aerial Systems ◽

Horizontal Distance ◽

Geospatial Information ◽

Open Source Data ◽

Source Data ◽

Aircraft Trajectories ◽

Processing Techniques ◽

Aerial Systems

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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