Measuring Intelligence, Surveillance, and Reconnaissance Effectiveness at the United States Central Command: Data Visualization Tool Documentation

10.7249/tl358 ◽  
2021 ◽  
Keyword(s):  
United States ◽  
Data Visualization ◽  
The United States ◽  
Visualization Tool ◽  
Central Command

scholarly journals Sexual Abstinence in the United States: Cohort Trends in Abstaining from Sex While Never Married for U.S. Women Born 1938 to 1983

2020 ◽  
Vol 6 ◽  
pp. 237802312090847
Author(s):  
Lawrence L. Wu ◽  
Steven P. Martin ◽  
Paula England ◽  
Nicholas D. E. Mark
Keyword(s):  
United States ◽  
Data Visualization ◽  
The United States ◽  
Sexual Abstinence ◽  
Birth Cohorts ◽  
Never Married ◽  
National Surveys ◽  
Family Growth ◽  
Using Data

In this data visualization, the authors document trends in abstaining from sex while never married for U.S. women born 1938–1939 to 1982–1983. Using data from the six most recent National Surveys of Family Growth, the authors’ estimates suggest that for women born in the late 1930s and early 1940s, 48 percent to 58 percent reported abstaining from sex while never married. Abstinence then declined rapidly among women born in the late 1940s through the early 1960s, leveling off at between 9 percent and 12 percent for more recent birth cohorts. Thus, for U.S. women born between the mid-1960s and the early 1980s, roughly one in nine abstained from sex while never married.

scholarly journals Data journalism and democracy: how American mass media framed the 2016 presidential campaign in the United States using data visualization

2017 ◽  
Author(s):  
◽  
Iuliia Alieva
Keyword(s):  
United States ◽  
New York ◽  
Data Visualization ◽  
Media Coverage ◽  
Visual Analysis ◽  
New York Times ◽  
The United States ◽  
Presidential Campaign ◽  
Design Elements

The purpose of this study is to explore the role of data visualization in the media coverage of the 2016 presidential campaign in the United States by focusing on datavisualization projects from The New York Times and The Washington Post. The research is focused on how journalists implemented data-visualization techniques and how the theory of framing is connected with that process. A secondary purpose of the research is to collect opinions from journalists working in the field about how data visualization influenced coverage of the campaign and how future reporting can be improved. This study consists of two parts: textual/visual analysis of data visualization examples from coverage of 2016 U.S. presidential campaign and interviews with the journalists involved in infographics production. Visual analysis was used for analyzing various design elements such as type of graphics, colors, fonts and how they helped to frame issues during the campaign. Textual analysis was used to identify the main issues and frames that were covered and considered important for the audience. The interviews provided information about the professional experience of data journalists and editors and their opinions about the role of data visualization and the problems and limitations that they experienced while working with it.

“Multiplied without Number”: Lynching, Statistics, and Visualization in Ida B. Wells, Mark Twain, and W. E. B. Du Bois

2021 ◽  
Author(s):  
Benjamin J. Murphy
Keyword(s):  
United States ◽  
Nineteenth Century ◽  
Data Visualization ◽  
Mark Twain ◽  
The United States ◽  
Racial Violence ◽  
Statistical Graphics ◽  
Life And Death ◽  
Du Bois ◽  
Black Life

Abstract Quantification has long played a vexed role in efforts to record and resist racial violence. Building from Ida B. Wells’s antilynching crusade, this essay examines the risks and power of calculating life and death at the close of the nineteenth century. For her part, Wells pushed mere counting past itself to a profound mode of ethical accounting. Two of her contemporaries, Mark Twain and W. E. B. Du Bois, sustained a similarly supraquantitative thrust; each attempted to harness the antilynching potential of numbers by enlisting data visualization. Twain falls short in a telling fashion, as his unpublished satire “The United States of Lyncherdom” (written in 1901) exacerbates the dehumanizing tendencies of quantification. Du Bois, however, pursues a more generative experiment, creating statistical graphics in 1900 that indict and outstrip the causal circuit that yoked scientific numbering to lynching and racial violence more broadly. This latter achievement resonates with scholarly efforts to access Black life from within a desolately tabulated archive of loss and erasure. Specifically, as triangulated with Wells and Twain, Du Bois’s graphics proffer a counterintuitive means to register life as a future-oriented, aggregate abstraction that is neither wholly conditioned by, nor separate from, a past whose violent legacies endure.

scholarly journals Does BIGMAC Index Consider as a Substitute for Inflation Rate

2019 ◽  
pp. 17-23
Author(s):  
Mai Yasser ◽  
Mohamed Mussad ◽  
Nadine Sanad
Keyword(s):  
United States ◽  
Inflation Rate ◽  
The United States ◽  
Central Command ◽  
The Cost ◽  
Power Equality

The BIGMAC Index was designed by The Economist in 1986 as a happy manual for whether monetary standards are at their "right" level. It depends on the hypothesis of acquiring power equality (PPP), the thought that over the long haul trade rates should move towards the rate that would even out the costs of an indistinguishable container of merchandise and enterprises (for this situation, a burger) in any two nations. The BicMac list has been distributed every year by The Economist since 1986 and is evaluated as a streamlined pointer of a nation's individual obtaining power. The same number of nations have various monetary forms, the institutionalized BIGMAC costs are determined by changing over the normal national BIGMAC costs with the most recent swapping scale to U.S. dollars. The Big Mac, as a top-selling McDonald's burger, is utilized for examination since it is accessible in pretty much every nation and fabricated in an institutionalized size, piece and quality. McDonald's is an overall working drive-through joint chain with central command in Oak Brook, Illinois. Its worldwide income added up to about 21.03 billion U.S. dollars in 2018. Most McDonald eateries are spread over the United States. The BIGMAC Index is determined by partitioning the cost of a BIGMAC in one nation by the cost of a BIGMAC in another nation in their separate nearby monetary forms to land at a conversion scale. This conversion scale is then contrasted with the official swapping scale between the two monetary forms to decide whether either money is underestimated or exaggerated by the PPP hypothesis.

easyBLS, a Tool for Querying Nonfatal Injury Information from United States Bureau of Labor Statistics Database

2017 ◽  
Vol 61 (1) ◽  
pp. 955-959
Author(s):  
Rong Huangfu ◽  
Robert Granzow ◽  
Sean Gallagher ◽  
Mark Schall
Keyword(s):  
United States ◽  
Data Visualization ◽  
High Efficiency ◽  
Occupational Injuries ◽  
Line Graph ◽  
The United States ◽  
United States Bureau ◽  
Labor Statistics ◽  
Bureau Of Labor Statistics ◽  
Nonfatal Injury

Every year, the United States Bureau of Labor Statistics (BLS) collects and publishes important information on the number and types of occupational injuries and illnesses affecting workers across all industries. Researchers, occupational safety and health professionals, epidemiologists and industry groups rely on this data to make conclusions about past, present, and future injury and illness trends. The data are also very important in determining the root causes of workplace injury and developing effective interventions. The BLS provides two web tools to query nonfatal injury data from the database. However, one of the tools is no longer functioning, while the other has relatively low query efficiency (more than twenty seconds per query) as tested in this study. Furthermore, there is no data visualization tool provided to help display the queried information. easyBLS (Desktop and web version) was developed to query information from the BLS database with relatively high efficiency (less than one second per query). This tool also provides two data visualization tools (line graph and map) to help users to better interpret the queried information. easyBLS web version is available to the public at http://easybls.pythonanywhere.com/ .

scholarly journals Visualizing the Geographic and Demographic Distribution of COVID-19

2020 ◽  
Vol 6 ◽  
pp. 237802312094871 ◽  
Author(s):  
Patrick Denice ◽  
Kate H. Choi ◽  
Michael Haan ◽  
Anna Zajacova
Keyword(s):  
United States ◽  
Data Visualization ◽  
The United States ◽  
Black Canadians ◽  
Race Ethnicity ◽  
High Level ◽  
Choropleth Map ◽  
Demographic Distribution ◽  
Racial Ethnic ◽  
Very High

Whereas African Americans are disproportionately among the coronavirus disease 2019 (COVID-19) pandemic’s sick and dead, less is known about whether some racial/ethnic groups are more likely to be affected in Canada. In this data visualization, the authors address two issues limiting understanding of the spatial and demographic distribution of the COVID-19 pandemic in Canada: (1) COVID-19 infection and death counts are collected at a very high level of geographic aggregation, and (2) these counts are not tallied by sociodemographic group, including race/ethnicity. The authors use a bivariate choropleth map to illustrate the correlation between COVID-19 infections and the percentage of residents who are Black across census subdivisions. Canada is more similar to the United States than expected in this respect: areas with higher shares of Black Canadians also see more infections.

scholarly journals Not Just a Pretty Picture: The U.S. Cancer Statistics Data Visualization Tool

2018 ◽  
Vol 4 (Supplement 2) ◽  
pp. 219s-219s
Author(s):  
V. Senkomago ◽  
S. Singh ◽  
M.E. O'Neil ◽  
L. Pollack ◽  
A. Kolli ◽  
...  
Keyword(s):  
Data Visualization ◽  
Survival Data ◽  
The United States ◽  
Surveillance Data ◽  
Cancer Surveillance ◽  
Mortality Data ◽  
Visualization Tool ◽  
Cancer Statistics ◽  
Cancer Data ◽  
Incidence And Mortality

Background: The United States Centers for Disease Prevention and Control (CDC) National Program of Cancer Registries (NPCR) works to disseminate cancer surveillance data to multiple audiences in accessible, discoverable, and usable formats. To this end, CDC released the official federal cancer statistics, U.S. Cancer Statistics (USCS), in a data visualization tool available at www.cdc.gov/cancer/dataviz . We made further enhancements to the online tool since its initial release in 2017. Aim: We describe the process and enhancements made to the USCS data visualization tool's content, graphical displays, and sharing capabilities. Methods: CDC partnered with Agency for Toxic Substances and Disease Registry's Geospatial Research, Analysis, and Services Program to further work initiated by a group of cancer registrars, program planners, epidemiologists, computer programmers, and communication specialists to improve the visual presentation of USCS cancer incidence and mortality data. We conducted usability testing and implemented changes to the Web site's layout and added content, including county-level data, survival data, and prevalence estimates. Results: New features include county statistics, survival, prevalence, Puerto Rico data, and tobacco-, alcohol-, and obesity-related cancers data displays. The tool was also enhanced to better display on mobile devices. Data displays on national and state incidence, mortality and trends are available as maps and bar charts with interpretive text when users scroll over each graphic. Users can customize displays of overall and cancer-specific statistics, download data tables, and share each page via social media. Conclusion: Surveillance data are fundamental to measure progress and target action. CDC's interactive USCS data visualization tool is designed to make cancer data more accessible and usable to multiple users, including the general public, media, policy makers and planners. We will continue to improve the tool's accessibility and usefulness to facilitate the interpretation and sharing of cancer data.

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