CIA World Factbook

The 2012 Army Weapon Systems Handbook is available in a new, easier to access format.

I know, because Terry Edwards, Director of the Army’s System of System’s Engineering (SoSE), asked me to do it, but more to the point, I learned some lessons from the previous version (simpler is better) that I want to share with readers, especially those that want to build their own dashboards.

First some background: “The Army Acquisition Executive has launched a new highly collaborative SoSE campaign aimed at synchronizing development and delivery of technologies across the entire Army systems portfolio, service officials have said.

“Among the effort’s central tenets is a need to align programs more closely and establish an acquisition strategy that draws simultaneously from programs of record (PORs), commercial-off-the-shelf products, and emerging technologies from the Army’s Science and Technology Directorate–all as a way to maximize efficiency across the Army’s developmental spectrum.”

That led to a dashboard which is an important step to implementing Dynamic Case Management, such as Be Informed 4, and Business Events, such as TIBCO Solutions for the Army SOSE.

I first decided what this dashboard should be about: What should be Linked Open Data be like and what should be Structured Data be like. I concluded they should be similar to work done with the CIA World Factbook recently.

This is really important to the Quint (CIA, DIA, NGA, NRO, and NSA). Do not worry about what all those acronyms mean, just that they keep us safe, especially if they all work together “to connect the dots” and connecting the dots involves connecting unstructured and structured data by making unstructured data Linked Open Data as a first step.

Leaving out most of the details, I copied the Army Weapons Systems Manual table of contents to my wiki-scraper tool and gave it well-defined web addresses and drilled down within each item to give it additional well-defined web addresses (not to short and not too long). Boring, but absolutely essential work to succeed. That all goes into a spreadsheet which gets imported to a dashboard tool where the data sets can be sorted, searched, merged, etc. The detailed results are shown elsewhere.

One can go from the DoD System of Systems to the Army Weapons System of Systems to the individual systems. Now what you really want to do is use that to manage an enterprise of 153 weapons systems efficiently and effectively as Terry Edwards described above, in his work which is described further at “Army’s Resource Forest Is Good Metaphor For System Of Systems Approach.” Keep reading →

The Occupy Wall Street (OWS) demonstrations that began Sept. 17, 2011, in New York City’s Zuccotti Park in the Wall Street financial district, launched by the Canadian activist group Adbusters have become a worldwide movement. The protests have focused on social and economic inequality, high unemployment, greed, as well as corruption, and the undue influence of corporations-particularly that of the financial services sector-on government. The message is perhaps best summed up with the protesters’ slogan, “We are the 99%,” referring to the growing difference in wealth in the U.S. between the wealthiest 1% and the rest of the population.

One measure of inequality is the Gini coefficient which is a measure of statistical dispersion developed by the Italian statistician and sociologist Corrado Gini and published in his 1912 paper “Variability and Mutability” (Italian: Variabilità e mutabilità).

The Gini coefficient is a measure of the inequality of a distribution, where a value of 0 expresses total equality and a value of 1 maximal inequality. It has found application in the study of inequalities in disciplines as diverse as sociology, economics, health science, ecology, chemistry, engineering and agriculture.

For example, in ecology the Gini coefficient has been used as a measure of biodiversity, where the cumulative proportion of species is plotted against cumulative proportion of individuals.

The Gini coefficent for Income Disparity in the CIA Fact Book of 2009 shown above is where 0 is perfect equality and 100 is perfect inequality (i.e., one person has all the income). Worldwide, Gini coefficients for income range from approximately 0.23 (Sweden) to 0.70 (Namibia) although not every country has been assessed.

While developed European nations and Canada tend to have Gini indices between 0.24 and 0.36, the United States’ and Mexico’s Gini indices are both above 0.40, indicating that the United States (according to the US Census Bureau) and Mexico have greater inequality.

Using the Gini coefficent can help quantify differences in welfare and compensation policies and philosophies. However it should be borne in mind that the Gini coefficient can be misleading when used to make political comparisons between large and small countries. The Gini index for the entire world has been estimated by various parties to be between 0.56 and 0.66.

I created an interactive dashboard of the GINI coefficient and other world country statistics from the CIA Fact Book and used it to identify the top ten highest GINI coefficient countries and the US position as follows on a 100 point scale: Honduras 56.3, Nicaragua 60.3, Colombia 57.10, Brazil 60.70, Bolivia 58.9, Paraguay 57.7, Chile 56.7, Sierra Leone 62.9, Central African Republic 61.3, and South Africa 59.3. The United States at 40.8 is ranked about 40th out of 239 Counties.

The data set and related information are available on my social knowledgebase.

So while the United States has greater inequality (40.8) according to the U.S. Census Bureau than countries such as Canada, France, Spain, and Australia (see map above), it is lower than the world average index (0.60 ) and is not among the top ten countries (62.9-56.3).