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Databases

In the good, old days (that is, during the 1960's and early 1970's) before the advent of personal computers, records generally were stored in filing cabinets in the form of paper. If, for instance, you purchased furniture on credit at the local furniture store, the furniture store owner would create either a handwritten or a typewritten payment ledger of your debt. The store owner would file your ledger card in a filing cabinet. When you came into the furniture store to make your monthly payment on the debt, the store owner would pull your ledger card from the filing cabinet and record both the payment made and the balance due. The store owner then would give you a handwritten receipt of payment containing the same information. The process would be repeated each month until the debt was paid in full.

Looking back at the good, old days before the advent of personal computers, assume you were a student during the 1960's who needed to complete a research paper to fulfill a classroom assignment. To do so, you went to the school's library to begin your research project. You went to the library's card catalog to explore topics of interest and to find books related to your chosen topic of interest. The library's card catalog adhered to the Dewey Decimal Classification system whereby the books on the shelves were organized by subject. The first step of your research project was to explore the library's card catalog for research ideas. Ultimately, you picked a topic, selected several books from the library shelves, checked them out, went home, read the books, and began writing your research paper. Yes, that is the way things were done in the good, old days.

Fast forward to the Personal Computer Era of the 1970's and 1980's. With the advent of the personal computer and with a bevy of software application to complement personal computers, it seemed as if most of the world went digital. All of those paper records were tossed into a trash can. Paper records were ported to an electronic database management system. The essence of the personal computer was that it introduced databases to the mass public, which indicated a sign of progress. At the library, for instance, now you could log into the library's computer network either in person or remotely, connect to the online card catalog database, and search for books of interest based on subject, title, or author. In some instances, you even could check out the book electronically across the World Wide Web in the form of an eBook download. WorldCat's search page represents a case in point of digitized card catalog system:

Click here to visit WorldCat's search page

DATABASE MANAGEMENT SYSTEM (DBMS)

A database is an electronic mechanism for organizing, storing, and quickly retrieving all kinds of data. A database can contain employee data, product data, membership data, consumer data, population data, scientific data, school data, and so forth. In a real-world production environment, users are able to add, delete, change, and search for records in the database. On this page, the three databases to be illustrated will be limited to searching for records or data in the database. The ability to add, delete or change a record has been disabled for the three web-based database illustrations below.

An electronic database management system (DBMS) represents a comprehensive set of inter-related tools for both interacting with (in terms of inputs and outputs), maintaining, and securing a database. For instance, many databases use the SQL (Structured Query Language) language as a tool for extracting and displaying specific records from the database. Most databases are designed to be shared by multiple users simultaneously. As a result, another feature of a DBMS is inclusion of a mechanism to maintain the integrity of the data. Say, for instance, a mechanism might exist to prevent two users at different locations from trying to edit the same record at the same time. One of users would not be able to update or edit the record until the other user's update was released or saved. Another feature of a DBMS relates to securing the database. These security features generally revolve around assigning certain users restricted privileges related to performing specific tasks within the database. A data entry operator, for instance, would not be granted maintenance privileges on the database. Some databases also have tools for automatically backing up a copy of the database at pre-determined time intervals in the event of, say, a system failure such as a disk failure or a natural disaster such as a major earthquake. The objective of securing the database is to assure minimal data loss and rapid data recovery.

From a user's perspective, perhaps two of the most important features of any given database are its input and output capabilities. In terms of a database's input capabilities, for instance, how easy—or difficult—is it for users to interact with the database? How easy—or difficult—is it for users to add, delete, change, and search for records in the database?

In terms of a database's output capabilities, for instance, how easy—or difficult—is it to query the database and drill down to specific records? How simple is it to filter and sort the data? How simple—and comprehensive—is it to generate reports and charts summarizing various or specific aspects of the data in the database?

Three web-based database models will be illustrated on this page. Again, these three illustrations will be limited to a database's search functionality. The three illustrations will not contain the ability to add, delete, or change records in the database. Web-based databases, generally speaking, are not as sophisticated as internal databases maintained by a typical organization, but web-based databases gradually are catching up to their corporate counterparts.

THREE ILLUSTRATIONS OF DATABASES ON THE WEB

One of the earliest types of databases to be deployed on the World Wide Web was based on CGI and Perl technologies. Many CGI/Perl databases used flat, text-based files to store the data. Click the following link to see a demonstration of the older CGI/Perl database model:

Click here for Illustration 1: CGI/Perl Database

By far, to date as of 2016, the relational database model (or RDBMS for relational database management system) represents one of the most popular and mature database models to be deployed on the World Wide Web. A RDMS moves away from flat text files as data sources in favor of tables as data storage mechanisms. The thing that makes a database relational is its ability to link or relate various tables within the database to one another. For instance, a database might contain one table for customers, another table for products, another table for orders, another table for employees, and another table for vendors. Through relational techniques, the user can join these various tables together in one-to-one relationships, one-to-many relationships, many-to-many relationships, union relationships, and so forth. These join techniques enable manipulation of the database data in all kinds of unique ways.

Some of the more popular relational databases in the marketplace today include Microsoft SQL Server, MySQL, PostgreSQL, IBM DB2, Oracle 12c, and SAP ASE. Click the following link to view a demonstration of the PHP/MySQL relational database model:

Click here for Illustration 2: PHP/MySQL Database

As illustrated, a chief benefit of using relational databases is the fact that they present users with easy-to-use graphical user interfaces (GUIs) on the front-end. GUIs are used to manipulate the database and attain a desired output. The underlying SQL commands are hidden from the user on the back-end. In other words, with a properly designed front-end GUI, the user does not need to be versed in SQL to easily navigate and manipulate the database. Most office suites such as Microsoft Office, Libre Office, Calligra Suite, and so forth, usually would contain a database application.

Data grids have emerged as an alternate way to present tabular data in a sophisticated, database-like manner on the World Wide Web. Some observers refer to data grids as enhanced, next-generation, or glorified HTML tables. One attribute of data grids to set them apart from regular HMTL tables is this: Much like standard databases, data grids have the capacity to add, delete, and change records in the table instantly on the fly. Data grids also retain the customary sorting, filtering, and querying functions of a database. Click the following link to see a demonstration of the data grid database model:

Click here for Illustration 3: Data Grid

For those who are interested in delving deeper into the data grid database model, some examples include the following ones:

A more recent World Wide Web development related to databases has been the advent of so-called NoSQL (Not Only SQL) databases. The NoSQL database model typically has been deployed by social networking types of organizations (such as Facebook and Twitter). That is to say, NoSQL databases are best suited for organization with millions of users and tons of user data to maintain, track, and link. One thing that makes not only SQL types of databases unique from relational databases is the manner in which data is stored. Instead of using tables to store and manipulate data as is the case with relational databases, NoSQL databases, in large part, mimic the JSON (JavaScript Object Notation) data storage paradigm.

There are numerous NoSQL databases in the marketplace. The NoSQL database model is not illustrated on this page. The main reason why a NoSQL database is not illustrated here is this: NoSQL databases generally are used where there is a need to store vast volumes of data, not small datasets. Moreover, in terms of World Wide Web deployments, the NoSQL database model has not yet gained a level of maturation and ease-of-use on par with relational databases, both their input and output features. The reader can click this PouchDB demonstration link to see how a Document-style NoSQL database is implemented on the World Wide Web.

For those who are interested in delving deeper into the NoSQL database model, some online or cloud-based examples include the following ones:

Watch (TECH TALKS: NoSQL vs SQL databases Tutorial - Differences and advantages of NoSQL versus SQ)


Watch (What is NoSQL Database? )


Watch (An Introduction To NoSQL Databases)


It should be noted that it probably would require attaining a college degree in computer science to become proficient at mastering these different database technologies. The database illustrations on this page can best be categorized as novice-level illustrations. There are numerous much more sophisticated database renditions deployed on the World Wide Web than the ones illustrated on this page.

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WIKIPEDIA MEETS THE SEMANTIC WEB

Speaking of databases and the Information Web, it should be noted that Wikepdia.org represents perhaps the largest online encyclopedia on Earth. Even more remarkably, Wikipedia is crowd-sourced and is made available free of charge for the world public to use. The stated mission of Wikipedia is "containing the sum of all human knowledge on Earth."

Wikipedia is mentioned here because it also has been transposed into a database-like format. That is to say, the transposed version of Wikipedia.org is maintained by DBpedia.org, and it is stored in the RDF (Resource Description Framework) format.

Based on its website, the stated mission of DBpedia is to allow users "to extract structured information from Wikipedia and make this information available on the Web. DBpedia allows you to ask sophisticated queries against Wikipedia, and to link the different data sets on the Web to Wikipedia data. We hope that this work will make it easier for the huge amount of information in Wikipedia to be used in some new interesting ways. Furthermore, it might inspire new mechanisms for navigating, linking, and improving the encyclopedia itself." DBpedia's (RDF) semantic web data storage format is more closely aligned with the NoSQL-based database model than it is to, say, the SQL-based relational database model.

As of 2016, not many GUIs exist to easily navigate and extract data from DBdepia. The GUI deployed by DBdepia is called DBpedia SPARQL (Structured Protocol and RDF Query Language), which does resemble the SQL programming language commonly used in the relational database world. The only problem with DBpedia SPARQL is this: It is not too user friendly. To successfully exploit the SPARQL interface to its maximum potential, the user is required to be versed in the SQL programming language, RDF, and DBpedia's unique vocabulary or its way of organizing and representing Wikipedia's data.

On the one hand, with the Google, Bing, and Yahoo! search engines, the user is accustomed to typing keywords into the search engine's search box to easily extract relevant information from the World Wide Web. You ask a question of Google, Bing, and Yahoo!, and you instantly receive an answer to your question in almost lightening speed. DBpedia SPARQL, on the other hand, looks strange and un-usable. With DBpedia SPARQL, first you have to figure out how to ask a question, and then you have hope that you receive a decent answer. Using DBpedia SPARQL today (as of 2016) is like a throwback to the days of command-line Microsoft DOS during the early 1980's. As of 2016, command-line DOS had morphed into a much more eloquent and user-friendly GUI known as the Windows 10 desktop. Will DBpedia be making a similar morph? For those who are interested in probing deeper into SPARQL, the following video series provides a good introduction:

Click here for Noureddin Sadawi's Simple SPARQL Tutorials

The chief benefit of a data repository such as DBpedia is this: It allows users to extract specific pieces of data from various Wikipedia pages and re-assemble this data into a wholly new view of the data. Steady progress is being made to provide users with easy-to-use GUIs for navigating and extracting information directly from Wikipedia or indirectly from Wikipedia through processes such as DBpedia. These efforts include the following ones:

Watch (Demo Sparklis ~ Explore SPARQL Endpoints...Answer Complex Questions)


The Exalead search engine serves as another resource for directly querying Wikipedia. Exalead has incorporated into its search engine an area devoted exclusively to a search of Wikipedia's content as illustrated below:

Click here to visit Exalead's Wikipedia search page

Google, too, has introduced a widget to easily search for information directly from Wikipedia, which is consistent with Google's stated mission of "organizing the world's information and making this information universally accessible and useful to all human beings." The Google Wikipedia widget is illustrated below:

Search Google's Knowledge Graph. Type some relevant text into the Search box below to find applicable Wikipedia matches.



















It is further worth mentioning that, in addition to Wikipedia, another popular data resource on the Web is found at Wolfram|Alpha.com. The stated mission of Wolfram|Alpha is "making all human knowledge computable and accessible to every human being from a single source." The Wolfram|Alpha search widget is illustrated below:

Click here to visit Wolfram|Alpha's search page
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A TALE OF TWO WARS

If you clicked any of the three database illustration links above, you noticed that the data itself was reproduced from the United Nations High Commissioner for Refugees's (UNHCR) 2015 Global Trends data. As I have mentioned elsewhere (namely, on bruessard.com), science can be used for good, and it equally can be used for bad. Similarly, the World Wide Web can be used for good, and it equally can be used for bad. As evidenced by the three databases illustrations above, this page used databases to shine a little more light on the contemporary global refugee/displaced persons crisis, in particular, and the human condition, in general.

The table below summarizes UNHCR's 2015 Global Trends data. The table below indicates that, for the year 2015, more displaced persons originated in the countries of Syria and Colombia than any of the other 197 countries surveyed. A key difference between Syria and Colombia was this: Most of Syria's displaced residents fled the country to escape the turmoil and civil war in Syria. Most of Colombia's displaced residents were displaced to other areas within the country to escape the turmoil and civil war in Colombia.

Summary: Global Trends 2015

Index Country (Year 2015) Refugees (including refugee-like situations) Asylum-seekers (pending cases) Returned refugees Internally displaced persons (IDPs) Returned IDPs Stateless persons Others of concern Total population in upheaval
  Afghanistan - Fleeing from (2,666,213) (258,866) (61,376) (1,174,306) (123,653) 0 (150,369) (4,434,783)
  Afghanistan - Received Into 257,553 79 0 1,174,306 123,653 0 150,317 1,705,908
1 Afghanistan's Net change (2,408,660) (258,787) (61,376) 0 0 0 (52) (2,728,875)
  Albania - Fleeing from (10,404) (42,140) 0 0 0 0 0 (52,544)
  Albania - Received Into 79 825 0 0 0 7,442 0 8,346
2 Albania's Net change (10,325) (41,315) 0 0 0 7,442 0 (44,198)
  Algeria - Fleeing from (3,450) (7,593) 0 0 0 0 (12) (11,055)
  Algeria - Received Into 94,161 6,570 859 0 0 0 0 101,590
3 Algeria's Net change 90,711 (1,023) 859 0 0 0 (12) 90,535
  Angola - Fleeing from (11,830) (3,242) (4,639) 0 0 0 (34,965) (54,676)
  Angola - Received Into 15,537 30,131 0 0 0 0 0 45,668
4 Angola's Net change 3,707 26,889 (4,639) 0 0 0 (34,965) (9,008)
  Antigua and Barbuda - Fleeing from (51) (7) 0 0 0 0 0 (58)
  Antigua and Barbuda - Received Into 15 0 0 0 0 0 0 15
5 Antigua and Barbuda's Net change (36) (7) 0 0 0 0 0 (43)
  Argentina - Fleeing from (181) (156) 0 0 0 0 0 (337)
  Argentina - Received Into 3,142 1,022 9 0 0 0 0 4,173
6 Argentina's Net change 2,961 866 9 0 0 0 0 3,836
  Armenia - Fleeing from (11,175) (8,486) 0 0 0 0 (14) (19,675)
  Armenia - Received Into 19,309 54 0 0 0 311 0 19,674
7 Armenia's Net change 8,134 (8,432) 0 0 0 311 (14) (1)
  Australia - Fleeing from (11) 0 0 0 0 0 0 (11)
  Australia - Received Into 36,827 20,535 0 0 0 0 0 57,362
8 Australia's Net change 36,816 20,535 0 0 0 0 0 57,351
  Austria - Received Into 72,158 80,020 143 0 0 828 0 153,149
9 Austria's Net change 72,158 80,020 143 0 0 828 0 153,149
  Azerbaijan - Fleeing from (9,699) (5,208) 0 (618,220) 0 0 0 (633,127)
  Azerbaijan - Received Into 1,269 211 64 618,220 0 3,585 0 623,349
10 Azerbaijan's Net change (8,430) (4,997) 64 0 0 3,585 0 (9,778)
  Bahamas - Fleeing from (211) (75) 0 0 0 0 0 (286)
  Bahamas - Received Into 7 10 0 0 0 0 86 103
11 Bahamas's Net change (204) (65) 0 0 0 0 86 (183)
  Bahrain - Fleeing from (407) (75) 0 0 0 0 0 (482)
  Bahrain - Received Into 246 103 11 0 0 0 0 360
12 Bahrain's Net change (161) 28 11 0 0 0 0 (122)
  Bangladesh - Fleeing from (12,135) (30,756) 0 0 0 0 (16) (42,907)
  Bangladesh - Received Into 231,954 0 0 0 0 0 0 231,954
13 Bangladesh's Net change 219,819 (30,756) 0 0 0 0 (16) 189,047
  Barbados - Fleeing from (95) (24) 0 0 0 0 0 (119)
14 Barbados's Net change (95) (24) 0 0 0 0 0 (119)
  Belarus - Fleeing from (4,101) (1,451) 0 0 0 0 0 (5,552)
  Belarus - Received Into 1,800 258 5 0 0 5,635 0 7,698
15 Belarus's Net change (2,301) (1,193) 5 0 0 5,635 0 2,146
  Belgium - Fleeing from (61) (27) 0 0 0 0 0 (88)
  Belgium - Received Into 35,267 35,949 29 0 0 5,776 0 77,021
16 Belgium's Net change 35,206 35,922 29 0 0 5,776 0 76,933
  Belize - Fleeing from (48) (91) 0 0 0 0 (57) (196)
  Belize - Received Into 34 716 0 0 0 0 57 807
17 Belize's Net change (14) 625 0 0 0 0 0 611
  Benin - Fleeing from (395) (1,132) 0 0 0 0 (6) (1,533)
  Benin - Received Into 521 166 6 0 0 0 0 693
18 Benin's Net change 126 (966) 6 0 0 0 (6) (840)
  Bhutan - Fleeing from (17,699) (211) 0 0 0 0 0 (17,910)
19 Bhutan's Net change (17,699) (211) 0 0 0 0 0 (17,910)
  Bolivia (Plurinational State of) - Fleeing from (550) (337) 0 0 0 0 0 (887)
  Bolivia (Plurinational State of) - Received into 752 0 0 0 0 0 0 752
20 Bolivia (Plurinational State of)'s Net change 202 (337) 0 0 0 0 0 (135)
  Bosnia and Herzegovina - Fleeing from (18,753) (6,996) (11) (98,324) 0 0 (52,437) (176,521)
  Bosnia and Herzegovina - Received into 6,789 10 68 98,324 0 58 52,437 157,686
21 Bosnia and Herzegovina's Net change (11,964) (6,986) 57 0 0 58 0 (18,835)
  Botswana - Fleeing from (301) (62) 0 0 0 0 0 (363)
  Botswana - Received Into 2,122 133 52 0 0 0 0 2,307
22 Botswana's Net change 1,821 71 52 0 0 0 0 1,944
  Brazil - Fleeing from (873) (2,132) 0 0 0 0 0 (3,005)
  Brazil - Received Into 8,643 20,718 0 0 0 0 6,264 35,625
23 Brazil's Net change 7,770 18,586 0 0 0 0 6,264 32,620
  Brunei Darussalam - Received Into 0 0 0 0 0 20,524 0 20,524
24 Brunei Darussalam's Net change 0 0 0 0 0 20,524 0 20,524
  Bulgaria - Fleeing from (1,259) (179) 0 0 0 0 0 (1,438)
  Bulgaria - Received Into 16,513 9,463 11 0 0 67 0 26,054
25 Bulgaria's Net change 15,254 9,284 11 0 0 67 0 24,616
  Burkina Faso - Fleeing from (2,112) (2,665) 0 0 0 0 0 (4,777)
  Burkina Faso - Received Into 34,012 136 1,674 0 0 0 0 35,822
26 Burkina Faso's Net change 31,900 (2,529) 1,674 0 0 0 0 31,045
  Burundi - Fleeing from (292,725) (26,864) (11) (25,000) (1,144) 0 (164,015) (509,759)
  Burundi - Received Into 53,356 2,920 42 25,000 1,144 1,302 639 84,403
27 Burundi's Net change (239,369) (23,944) 31 0 0 1,302 (163,376) (425,356)
  Cabo Verde - Fleeing from (17) (90) 0 0 0 0 0 (107)
  Cabo Verde - Received Into 0 0 0 0 0 115 0 115
28 Cabo Verde's Net change (17) (90) 0 0 0 115 0 8
  Cambodia - Fleeing from (12,791) (357) 0 0 0 0 0 (13,148)
  Cambodia - Received Into 69 14 0 0 0 0 197 280
29 Cambodia's Net change (12,722) (343) 0 0 0 0 197 (12,868)
  Cameroon - Fleeing from (10,535) (7,359) 0 (92,657) (18,636) 0 (5) (129,192)
  Cameroon - Received Into 342,950 5,342 11,250 92,657 18,636 0 9 470,844
30 Cameroon's Net change 332,415 (2,017) 11,250 0 0 0 4 341,652
  Canada - Fleeing from (73) (329) 0 0 0 0 (6) (408)
  Canada - Received Into 135,865 19,542 24 0 0 0 0 155,431
31 Canada's Net change 135,792 19,213 24 0 0 0 (6) 155,023
  Cayman Islands - Fleeing from (6) 0 0 0 0 0 0 (6)
  Cayman Islands - Received Into 5 0 0 0 0 0 0 5
32 Cayman Islands's Net change (1) 0 0 0 0 0 0 (1)
  Central African Rep. - Fleeing from (471,073) (10,626) (21,632) (216,392) (258,276) 0 (20,792) (998,791)
  Central African Rep. - Received into 7,322 332 811 216,392 258,276 0 0 483,133
33 Central African Rep.'s Net change (463,751) (10,294) (20,821) 0 0 0 (20,792) (515,658)
  Chad - Fleeing from (14,896) (3,261) (38) (51,999) 0 0 (30,000) (100,194)
  Chad - Received Into 369,523 2,880 49,221 51,999 0 0 50,000 523,623
34 Chad's Net change 354,627 (381) 49,183 0 0 0 20,000 423,429
  Chile - Fleeing from (554) (130) 0 0 0 0 0 (684)
  Chile - Received Into 1,825 1,025 0 0 0 0 0 2,850
35 Chile's Net change 1,271 895 0 0 0 0 0 2,166
  China - Fleeing from (212,880) (57,680) 0 0 0 0 0 (270,560)
  China - Received Into 301,039 650 0 0 0 0 0 301,689
36 China's Net change 88,159 (57,030) 0 0 0 0 0 31,129
  China, Hong Kong SAR - Fleeing from (28) (75) 0 0 0 0 0 (103)
  China, Hong Kong SAR - Received into 104 2,239 0 0 0 0 0 2,343
37 China, Hong Kong SAR's Net change 76 2,164 0 0 0 0 0 2,240
  China, Macao SAR - Fleeing from 0 (20) 0 0 0 0 0 (20)
38 China, Macao SAR's Net change 0 (20) 0 0 0 0 0 (20)
  Colombia - Fleeing from (340,190) (6,865) (1,789) (6,939,067) 0 0 0 (7,287,911)
  Colombia - Received Into 187 102 0 6,939,067 0 12 0 6,939,368
39 Colombia's Net change (340,003) (6,763) (1,789) 0 0 12 0 (348,543)
  Comoros - Fleeing from (553) (216) 0 0 0 0 0 (769)
40 Comoros's Net change (553) (216) 0 0 0 0 0 (769)
  Congo - Fleeing from (14,707) (4,063) 0 0 0 0 (88) (18,858)
  Congo - Received Into 44,937 4,330 274 0 0 0 2,838 52,379
41 Congo's Net change 30,230 267 274 0 0 0 2,750 33,521
  Costa Rica - Fleeing from (369) (208) 0 0 0 0 0 (577)
  Costa Rica - Received Into 3,588 3,224 0 0 0 1,806 0 8,618
42 Costa Rica's Net change 3,219 3,016 0 0 0 1,806 0 8,041
  Cote d'Ivoire - Fleeing from (71,037) (13,729) (12,215) (308,272) (399) 0 (44) (405,696)
  Cote d'Ivoire - Received Into 1,952 624 63 308,272 399 700,000 44 1,011,354
43 Cote d'Ivoire's Net change (69,085) (13,105) (12,152) 0 0 700,000 0 605,658
  Croatia - Fleeing from (33,437) (67) (111) 0 0 0 (14,070) (47,685)
  Croatia - Received Into 473 5 20 0 0 2,873 14,070 17,441
44 Croatia's Net change (32,964) (62) (91) 0 0 2,873 0 (30,244)
  Cuba - Fleeing from (6,826) (2,315) 0 0 0 0 (75) (9,216)
  Cuba - Received Into 295 23 0 0 0 0 0 318
45 Cuba's Net change (6,531) (2,292) 0 0 0 0 (75) (8,898)
  Cyprus - Received Into 7,022 2,200 0 0 0 0 6,000 15,222
46 Cyprus's Net change 7,022 2,200 0 0 0 0 6,000 15,222
  Czech Rep. - Fleeing from (1,280) (113) 0 0 0 0 0 (1,393)
  Czech Rep. - Received Into 3,580 604 0 0 0 1,502 0 5,686
47 Czech Rep.'s Net change 2,300 491 0 0 0 1,502 0 4,293
  Dem. People's Rep. of Korea - Fleeing from (1,089) (213) 0 0 0 0 0 (1,302)
  Dem. People's Rep. of Korea - Received into 0 0 16 0 0 0 0 16
48 Dem. People's Rep. of Korea's Net change (1,089) (213) 16 0 0 0 0 (1,286)
  Dem. Rep. of the Congo - Fleeing from (541,465) (76,385) (8,530) (1,555,112) (736,837) 0 (9,923) (2,928,252)
  Dem. Rep. of the Congo - Received into 383,085 968 10,822 1,555,112 736,837 0 14,474 2,701,298
49 Dem. Rep. of the Congo's Net change (158,380) (75,417) 2,292 0 0 0 4,551 (226,954)
  Denmark - Fleeing from (6) (7) 0 0 0 0 0 (13)
  Denmark - Received Into 27,267 2,892 9 0 0 6,580 0 36,748
50 Denmark's Net change 27,261 2,885 9 0 0 6,580 0 36,735
  Djibouti - Fleeing from (1,049) (534) 0 0 0 0 0 (1,583)
  Djibouti - Received Into 19,359 2,634 0 0 0 0 0 21,993
51 Djibouti's Net change 18,310 2,100 0 0 0 0 0 20,410
  Dominica - Fleeing from (35) (78) 0 0 0 0 0 (113)
52 Dominica's Net change (35) (78) 0 0 0 0 0 (113)
  Dominican Rep. - Fleeing from (357) (1,699) 0 0 0 0 0 (2,056)
  Dominican Rep. - Received Into 605 740 0 0 0 133,770 0 135,115
53 Dominican Rep.'s Net change 248 (959) 0 0 0 133,770 0 133,059
  Ecuador - Fleeing from (981) (10,391) 0 0 0 0 0 (11,372)
  Ecuador - Received Into 121,451 11,583 10 0 0 0 0 133,044
54 Ecuador's Net change 120,470 1,192 10 0 0 0 0 121,672
  Egypt - Fleeing from (17,879) (12,136) 0 0 0 0 (78) (30,093)
  Egypt - Received Into 212,462 38,125 87 0 0 22 0 250,696
55 Egypt's Net change 194,583 25,989 87 0 0 22 (78) 220,603
  El Salvador - Fleeing from (14,758) (31,444) 0 0 0 0 (10,100) (56,302)
  El Salvador - Received Into 36 0 0 0 0 0 10,100 10,136
56 El Salvador's Net change (14,722) (31,444) 0 0 0 0 0 (46,166)
  Equatorial Guinea - Fleeing from (160) (69) 0 0 0 0 0 (229)
57 Equatorial Guinea's Net change (160) (69) 0 0 0 0 0 (229)
  Eritrea - Fleeing from (411,301) (63,390) 0 0 0 0 (235) (474,926)
  Eritrea - Received Into 2,549 0 33 0 0 0 6 2,588
58 Eritrea's Net change (408,752) (63,390) 33 0 0 0 (229) (472,338)
  Estonia - Fleeing from (310) (35) 0 0 0 0 0 (345)
  Estonia - Received Into 133 58 0 0 0 85,301 0 85,492
59 Estonia's Net change (177) 23 0 0 0 85,301 0 85,147
  Ethiopia - Fleeing from (85,749) (77,874) 0 0 0 0 (221) (163,844)
  Ethiopia - Received Into 736,071 2,111 0 0 0 0 934 739,116
60 Ethiopia's Net change 650,322 (75,763) 0 0 0 0 713 575,272
  Fiji - Fleeing from (877) (424) 0 0 0 0 0 (1,301)
  Fiji - Received Into 7 6 0 0 0 0 0 13
61 Fiji's Net change (870) (418) 0 0 0 0 0 (1,288)
  Finland - Fleeing from (5) 0 0 0 0 0 0 (5)
  Finland - Received Into 12,622 24,292 20 0 0 2,427 0 39,361
62 Finland's Net change 12,617 24,292 20 0 0 2,427 0 39,356
  France - Fleeing from (80) (57) 0 0 0 0 0 (137)
  France - Received Into 273,092 63,005 107 0 0 1,326 0 337,530
63 France's Net change 273,012 62,948 107 0 0 1,326 0 337,393
  Gabon - Fleeing from (159) (214) 0 0 0 0 0 (373)
  Gabon - Received Into 919 1,917 31 0 0 0 0 2,867
64 Gabon's Net change 760 1,703 31 0 0 0 0 2,494
  Gambia - Fleeing from (8,453) (12,781) 0 0 0 0 0 (21,234)
  Gambia - Received Into 7,851 0 0 0 0 0 0 7,851
65 Gambia's Net change (602) (12,781) 0 0 0 0 0 (13,383)
  Georgia - Fleeing from (6,455) (9,273) 0 (268,416) 0 0 0 (284,144)
  Georgia - Received Into 1,963 688 0 268,416 0 627 0 271,694
66 Georgia's Net change (4,492) (8,585) 0 0 0 627 0 (12,450)
  Germany - Fleeing from (153) (81) 0 0 0 0 0 (234)
  Germany - Received Into 316,058 420,569 175 0 0 12,569 0 749,371
67 Germany's Net change 315,905 420,488 175 0 0 12,569 0 749,137
  Ghana - Fleeing from (22,932) (10,917) 0 0 0 0 0 (33,849)
  Ghana - Received Into 17,394 1,840 42 0 0 0 0 19,276
68 Ghana's Net change (5,538) (9,077) 42 0 0 0 0 (14,573)
  Greece - Fleeing from (106) (56) 0 0 0 0 0 (162)
  Greece - Received Into 30,187 26,101 448 0 0 198 0 56,934
69 Greece's Net change 30,081 26,045 448 0 0 198 0 56,772
  Grenada - Fleeing from (270) (51) 0 0 0 0 0 (321)
70 Grenada's Net change (270) (51) 0 0 0 0 0 (321)
  Guadeloupe - Fleeing from 0 (23) 0 0 0 0 0 (23)
71 Guadeloupe's Net change 0 (23) 0 0 0 0 0 (23)
  Guatemala - Fleeing from (10,264) (26,930) 0 0 0 0 (3,500) (40,694)
  Guatemala - Received Into 222 113 0 0 0 0 3,500 3,835
72 Guatemala's Net change (10,042) (26,817) 0 0 0 0 0 (36,859)
  Guinea - Fleeing from (16,977) (17,834) 0 0 0 0 0 (34,811)
  Guinea - Received Into 8,825 194 0 0 0 0 0 9,019
73 Guinea's Net change (8,152) (17,640) 0 0 0 0 0 (25,792)
  Guinea-Bissau - Fleeing from (1,452) (1,910) 0 0 0 0 0 (3,362)
  Guinea-Bissau - Received Into 8,680 110 0 0 0 0 0 8,790
74 Guinea-Bissau's Net change 7,228 (1,800) 0 0 0 0 0 5,428
  Guyana - Fleeing from (508) (223) 0 0 0 0 0 (731)
  Guyana - Received Into 7 0 0 0 0 0 0 7
75 Guyana's Net change (501) (223) 0 0 0 0 0 (724)
  Haiti - Fleeing from (34,752) (9,241) 0 0 0 0 (6,264) (50,257)
  Haiti - Received Into 0 0 0 0 0 977 0 977
76 Haiti's Net change (34,752) (9,241) 0 0 0 977 (6,264) (49,280)
  Honduras - Fleeing from (6,830) (19,421) 0 (174,000) 0 0 (5,100) (205,351)
  Honduras - Received Into 23 5 0 174,000 0 0 5,100 179,128
77 Honduras's Net change (6,807) (19,416) 0 0 0 0 0 (26,223)
  Hungary - Fleeing from (1,427) (699) 0 0 0 0 0 (2,126)
  Hungary - Received Into 4,333 36,641 0 0 0 132 0 41,106
78 Hungary's Net change 2,906 35,942 0 0 0 132 0 38,980
  Iceland - Received Into 125 129 0 0 0 131 0 385
79 Iceland's Net change 125 129 0 0 0 131 0 385
  India - Fleeing from (9,832) (24,927) 0 0 0 0 (378) (35,137)
  India - Received Into 201,364 6,452 957 0 0 0 0 208,773
80 India's Net change 191,532 (18,475) 957 0 0 0 (378) 173,636
  Indonesia - Fleeing from (13,942) (2,623) 0 0 0 0 0 (16,565)
  Indonesia - Received Into 5,954 7,554 626 0 0 0 0 14,134
81 Indonesia's Net change (7,988) 4,931 626 0 0 0 0 (2,431)
  Iran (Islamic Rep. of) - Fleeing from (84,899) (57,035) (5) 0 0 0 (8) (141,947)
  Iran (Islamic Rep. of) - Received into 979,435 42 4,152 0 0 0 0 983,629
82 Iran (Islamic Rep. of)'s Net change 894,536 (56,993) 4,147 0 0 0 (8) 841,682
  Iraq - Fleeing from (264,064) (237,123) (5,909) (4,403,287) (1,747) 0 (3,598) (4,915,728)
  Iraq - Received Into 277,697 7,389 200 4,403,287 1,747 50,000 27 4,740,347
83 Iraq's Net change 13,633 (229,734) (5,709) 0 0 50,000 (3,571) (175,381)
  Ireland - Fleeing from 0 (36) 0 0 0 0 0 (36)
  Ireland - Received Into 6,063 4,983 0 0 0 99 0 11,145
84 Ireland's Net change 6,063 4,947 0 0 0 99 0 11,109
  Israel - Fleeing from (782) (366) 0 0 0 0 0 (1,148)
  Israel - Received Into 38,463 6,554 0 0 0 15 0 45,032
85 Israel's Net change 37,681 6,188 0 0 0 15 0 43,884
  Italy - Fleeing from (64) (138) 0 0 0 0 0 (202)
  Italy - Received Into 117,986 60,105 232 0 0 747 0 179,070
86 Italy's Net change 117,922 59,967 232 0 0 747 0 178,868
  Jamaica - Fleeing from (1,850) (818) 0 0 0 0 0 (2,668)
  Jamaica - Received Into 8 0 0 0 0 0 0 8
87 Jamaica's Net change (1,842) (818) 0 0 0 0 0 (2,660)
  Japan - Fleeing from (140) (58) 0 0 0 0 0 (198)
  Japan - Received Into 2,464 13,792 5 0 0 603 0 16,864
88 Japan's Net change 2,324 13,734 5 0 0 603 0 16,666
  Jordan - Fleeing from (1,802) (1,808) 0 0 0 0 (92) (3,702)
  Jordan - Received Into 664,095 24,899 286 0 0 0 0 689,280
89 Jordan's Net change 662,293 23,091 286 0 0 0 (92) 685,578
  Kazakhstan - Fleeing from (2,243) (1,538) 0 0 0 0 0 (3,781)
  Kazakhstan - Received Into 701 89 5 0 0 7,909 0 8,704
90 Kazakhstan's Net change (1,542) (1,449) 5 0 0 7,909 0 4,923
  Kenya - Fleeing from (7,877) (3,263) (1,231) 0 0 0 (12) (12,383)
  Kenya - Received Into 553,892 39,950 5,846 0 0 20,000 0 619,688
91 Kenya's Net change 546,015 36,687 4,615 0 0 20,000 (12) 607,305
  Kuwait - Fleeing from (1,071) (426) 0 0 0 0 0 (1,497)
  Kuwait - Received Into 731 883 29 0 0 93,000 0 94,643
92 Kuwait's Net change (340) 457 29 0 0 93,000 0 93,146
  Kyrgyzstan - Fleeing from (2,473) (2,258) 0 0 0 0 0 (4,731)
  Kyrgyzstan - Received Into 349 145 12 0 0 9,118 0 9,624
93 Kyrgyzstan's Net change (2,124) (2,113) 12 0 0 9,118 0 4,893
  Lao People's Dem. Rep. - Fleeing from (7,354) (151) 0 0 0 0 0 (7,505)
92 Lao People's Dem. Rep.'s Net change (7,354) (151) 0 0 0 0 0 (7,505)
  Latvia - Fleeing from (187) (80) 0 0 0 0 0 (267)
  Latvia - Received Into 188 162 0 0 0 252,195 0 252,545
93 Latvia's Net change 1 82 0 0 0 252,195 0 252,278
  Lebanon - Fleeing from (4,333) (5,950) 0 0 0 0 0 (10,283)
  Lebanon - Received Into 1,070,844 12,108 51 0 0 0 5,208 1,088,211
94 Lebanon's Net change 1,066,511 6,158 51 0 0 0 5,208 1,077,928
  Lesotho - Fleeing from (11) (1,086) 0 0 0 0 0 (1,097)
  Lesotho - Received Into 26 0 0 0 0 0 0 26
95 Lesotho's Net change 15 (1,086) 0 0 0 0 0 (1,071)
  Liberia - Fleeing from (9,929) (2,383) (51) 0 0 0 (8) (12,371)
  Liberia - Received Into 36,490 6 12,059 0 0 0 1,479 50,034
96 Liberia's Net change 26,561 (2,377) 12,008 0 0 0 1,471 37,663
  Libya - Fleeing from (6,042) (6,027) 0 (434,869) 0 0 (5) (446,943)
  Libya - Received Into 9,295 27,458 172 434,869 0 0 0 471,794
97 Libya's Net change 3,253 21,431 172 0 0 0 (5) 24,851
  Liechtenstein - Received Into 141 67 0 0 0 0 0 208
98 Liechtenstein's Net change 141 67 0 0 0 0 0 208
  Lithuania - Fleeing from (138) (59) 0 0 0 0 0 (197)
  Lithuania - Received Into 1,064 75 0 0 0 3,466 0 4,605
99 Lithuania's Net change 926 16 0 0 0 3,466 0 4,408
  Luxembourg - Received Into 1,276 2,343 0 0 0 82 0 3,701
100 Luxembourg's Net change 1,276 2,343 0 0 0 82 0 3,701
  Madagascar - Fleeing from (265) (158) 0 0 0 0 (5) (428)
  Madagascar - Received Into 6 5 0 0 0 0 0 11
101 Madagascar's Net change (259) (153) 0 0 0 0 (5) (417)
  Malawi - Fleeing from (404) (5,674) 0 0 0 0 0 (6,078)
  Malawi - Received Into 9,013 14,463 0 0 0 0 0 23,476
102 Malawi's Net change 8,609 8,789 0 0 0 0 0 17,398
  Malaysia - Fleeing from (425) (2,803) 0 0 0 0 0 (3,228)
  Malaysia - Received Into 94,111 60,375 61 0 0 11,689 80,000 246,236
103 Malaysia's Net change 93,686 57,572 61 0 0 11,689 80,000 243,008
  Maldives - Fleeing from (34) (18) 0 0 0 0 0 (52)
104 Maldives's Net change (34) (18) 0 0 0 0 0 (52)
  Mali - Fleeing from (154,170) (9,851) (4,088) (61,920) (53,551) 0 (26) (283,606)
  Mali - Received Into 15,908 336 0 61,920 53,551 0 0 131,715
105 Mali's Net change (138,262) (9,515) (4,088) 0 0 0 (26) (151,891)
  Malta - Received Into 7,033 561 5 0 0 0 0 7,599
106 Malta's Net change 7,033 561 5 0 0 0 0 7,599
  Marshall Islands - Fleeing from 0 (6) 0 0 0 0 0 (6)
107 Marshall Islands's Net change 0 (6) 0 0 0 0 0 (6)
  Mauritania - Fleeing from (34,631) (7,460) 0 0 0 0 0 (42,091)
  Mauritania - Received Into 77,380 478 499 0 0 0 0 78,357
108 Mauritania's Net change 42,749 (6,982) 499 0 0 0 0 36,266
  Mauritius - Fleeing from (91) (198) 0 0 0 0 0 (289)
109 Mauritius's Net change (91) (198) 0 0 0 0 0 (289)
  Mexico - Fleeing from (11,305) (46,231) 0 0 0 0 0 (57,536)
  Mexico - Received Into 2,874 1,304 0 0 0 13 0 4,191
110 Mexico's Net change (8,431) (44,927) 0 0 0 13 0 (53,345)
  Micronesia (Federated States of) - Fleeing from 0 (6) 0 0 0 0 0 (6)
  Micronesia (Federated States of) - Received into 0 11 0 0 0 0 0 11
111 Micronesia (Federated States of)'s Net change 0 5 0 0 0 0 0 5
  Monaco - Received Into 32 0 0 0 0 0 0 32
112 Monaco's Net change 32 0 0 0 0 0 0 32
  Mongolia - Fleeing from (2,188) (3,513) 0 0 0 0 0 (5,701)
  Mongolia - Received Into 6 0 0 0 0 0 6
113 Mongolia's Net change (2,182) (3,513) 0 0 0 0 0 (5,695)
  Montenegro - Fleeing from (641) (3,003) 0 0 0 0 0 (3,644)
  Montenegro - Received Into 1,762 18 156 0 0 3,262 10,822 16,020
114 Montenegro's Net change 1,121 (2,985) 156 0 0 3,262 10,822 12,376
  Morocco - Fleeing from (1,732) (5,562) 0 0 0 0 (11) (7,305)
  Morocco - Received Into 3,884 1,524 10 0 0 0 0 5,418
115 Morocco's Net change 2,152 (4,038) 10 0 0 0 (11) (1,887)
  Mozambique - Fleeing from (40) (2,190) 0 0 0 0 0 (2,230)
  Mozambique - Received Into 5,609 14,814 0 0 0 0 0 20,423
116 Mozambique's Net change 5,569 12,624 0 0 0 0 0 18,193
  Myanmar - Fleeing from (451,789) (60,617) 0 (451,089) (25,265) 0 (443) (989,203)
  Myanmar - Received Into 0 0 0 451,089 25,265 938,000 0 1,414,354
117 Myanmar's Net change (451,789) (60,617) 0 0 0 938,000 (443) 425,151
  Namibia - Fleeing from (1,456) (60) (21) 0 0 0 (36) (1,573)
  Namibia - Received Into 1,725 1,087 0 0 0 0 1,703 4,515
118 Namibia's Net change 269 1,027 (21) 0 0 0 1,667 2,942
  Nauru - Received Into 488 269 0 0 0 0 0 757
119 Nauru's Net change 488 269 0 0 0 0 0 757
  Nepal - Fleeing from (8,838) (8,941) 0 0 0 0 0 (17,779)
  Nepal - Received Into 32,659 15 0 0 0 0 384 33,058
120 Nepal's Net change 23,821 (8,926) 0 0 0 0 384 15,279
  Netherlands - Fleeing from (64) (50) 0 0 0 0 0 (114)
  Netherlands - Received Into 88,493 27,980 5 0 0 1,951 0 118,429
121 Netherlands's Net change 88,429 27,930 5 0 0 1,951 0 118,315
  New Zealand - Fleeing from (16) (9) 0 0 0 0 0 (25)
  New Zealand - Received Into 1,273 99 119 0 0 0 0 1,491
122 New Zealand's Net change 1,257 90 119 0 0 0 0 1,466
  Nicaragua - Fleeing from (1,464) (1,224) 0 0 0 0 0 (2,688)
  Nicaragua - Received Into 325 126 0 0 0 0 0 451
123 Nicaragua's Net change (1,139) (1,098) 0 0 0 0 0 (2,237)
  Niger - Fleeing from (1,363) (748) 0 (137,337) 0 0 (70,000) (209,448)
  Niger - Received Into 124,712 103 1,107 137,337 0 0 70,000 333,259
124 Niger's Net change 123,349 (645) 1,107 0 0 0 0 123,811
  Nigeria - Fleeing from (167,942) (51,821) 0 (2,172,532) 0 0 (9) (2,392,304)
  Nigeria - Received Into 1,372 375 0 2,172,532 0 0 0 2,174,279
125 Nigeria's Net change (166,570) (51,446) 0 0 0 0 (9) (218,025)
  Niue - Fleeing from (18) (18) 0 0 0 0 0 (36)
126 Niue's Net change (18) (18) 0 0 0 0 0 (36)
  Norway - Received Into 50,317 25,236 146 0 0 2,561 0 78,260
127 Norway's Net change 50,317 25,236 146 0 0 2,561 0 78,260
  Oman - Fleeing from (21) (6) 0 0 0 0 0 (27)
  Oman - Received Into 244 185 22 0 0 0 0 451
128 Oman's Net change 223 179 22 0 0 0 0 424
  Pakistan - Fleeing from (297,787) (64,041) 0 (1,146,108) (676,638) 0 0 (2,184,574)
  Pakistan - Received Into 1,561,152 6,440 58,211 1,146,108 676,638 0 0 3,448,549
129 Pakistan's Net change 1,263,365 (57,601) 58,211 0 0 0 0 1,263,975
  Palestinian - Fleeing from (97,923) (4,294) (12) 0 0 0 (2,420) (104,649)
130 Palestinian's Net change (97,923) (4,294) (12) 0 0 0 (2,420) (104,649)
  Panama - Fleeing from (62) (52) 0 0 0 0 0 (114)
  Panama - Received Into 17,264 2,904 0 0 0 0 0 20,168
131 Panama's Net change 17,202 2,852 0 0 0 0 0 20,054
  Papua New Guinea - Fleeing from (335) (198) 0 0 0 0 0 (533)
  Papua New Guinea - Received Into 9,503 423 0 0 0 0 0 9,926
132 Papua New Guinea's Net change 9,168 225 0 0 0 0 0 9,393
  Paraguay - Fleeing from (83) (67) 0 0 0 0 0 (150)
  Paraguay - Received Into 167 27 5 0 0 0 0 199
133 Paraguay's Net change 84 (40) 5 0 0 0 0 49
  Peru - Fleeing from (3,581) (1,527) 0 0 0 0 0 (5,108)
  Peru - Received Into 1,429 340 0 0 0 0 0 1,769
134 Peru's Net change (2,152) (1,187) 0 0 0 0 0 (3,339)
  Philippines - Fleeing from (578) (1,865) 0 (63,174) (254,848) 0 (80,057) (400,522)
  Philippines - Received Into 239 165 0 63,174 254,848 7,138 68 325,632
135 Philippines's Net change (339) (1,700) 0 0 0 7,138 (79,989) (74,890)
  Poland - Fleeing from (1,273) (392) 0 0 0 0 0 (1,665)
  Poland - Received Into 14,012 3,266 0 0 0 10,825 0 28,103
136 Poland's Net change 12,739 2,874 0 0 0 10,825 0 26,438
  Portugal - Fleeing from (18) (54) 0 0 0 0 0 (72)
  Portugal - Received Into 634 586 0 0 0 14 0 1,234
137 Portugal's Net change 616 532 0 0 0 14 0 1,162
  Qatar - Fleeing from (16) (7) 0 0 0 0 0 (23)
  Qatar - Received Into 117 116 12 0 0 1,200 0 1,445
138 Qatar's Net change 101 109 12 0 0 1,200 0 1,422
  Rep. of Korea - Fleeing from (346) (248) 0 0 0 0 0 (594)
  Rep. of Korea - Received Into 1,425 5,386 0 0 0 197 0 7,008
139 Rep. of Korea's Net change 1,079 5,138 0 0 0 197 0 6,414
  Rep. of Moldova - Fleeing from (2,264) (3,402) 0 0 0 0 0 (5,666)
  Rep. of Moldova - Received Into 404 87 0 0 0 5,014 0 5,505
140 Rep. of Moldova's Net change (1,860) (3,315) 0 0 0 5,014 0 (161)
  Romania - Fleeing from (1,726) (1,349) 0 0 0 0 0 (3,075)
  Romania - Received Into 2,546 383 25 0 0 240 0 3,194
141 Romania's Net change 820 (966) 25 0 0 240 0 119
  Russian Federation - Fleeing from (67,028) (27,472) 0 0 0 0 0 (94,500)
  Russian Federation - Received Into 314,472 2,025 0 0 0 101,813 0 418,310
142 Russian Federation's Net change 247,444 (25,447) 0 0 0 101,813 0 323,810
  Rwanda - Fleeing from (286,322) (10,927) (5,050) 0 0 0 (5,801) (308,100)
  Rwanda - Received Into 144,724 406 11 0 0 0 960 146,101
143 Rwanda's Net change (141,598) (10,521) (5,039) 0 0 0 (4,841) (161,999)
  Saint Kitts and Nevis - Fleeing from (20) (5) 0 0 0 0 0 (25)
144 Saint Kitts and Nevis's Net change (20) (5) 0 0 0 0 0 (25)
  Saint Lucia - Fleeing from (1,011) (49) 0 0 0 0 0 (1,060)
145 Saint Lucia's Net change (1,011) (49) 0 0 0 0 0 (1,060)
  Saint Vincent and the Grenadines - Fleeing from (1,823) (41) 0 0 0 0 0 (1,864)
146 Saint Vincent and the Grenadines's Net change (1,823) (41) 0 0 0 0 0 (1,864)
  Samoa - Fleeing from 0 (11) 0 0 0 0 0 (11)
147 Samoa's Net change 0 (11) 0 0 0 0 0 (11)
  Sao Tome and Principe - Fleeing from (19) (10) 0 0 0 0 0 (29)
148 Sao Tome and Principe's Net change (19) (10) 0 0 0 0 0 (29)
  Saudi Arabia - Fleeing from (666) (548) 0 0 0 0 (10) (1,224)
  Saudi Arabia - Received Into 117 23 64 0 0 70,000 0 70,204
149 Saudi Arabia's Net change (549) (525) 64 0 0 70,000 (10) 68,980
  Senegal - Fleeing from (21,242) (14,272) 0 0 0 0 0 (35,514)
  Senegal - Received Into 14,383 3,086 0 0 0 0 0 17,469
150 Senegal's Net change (6,859) (11,186) 0 0 0 0 0 (18,045)
  Serbia and Kosovo - Fleeing from (38,613) (53,278) (328) (220,002) (545) 0 0 (312,766)
  Serbia and Kosovo - Received Into 35,321 93 51 220,002 545 2,700 0 258,712
151 Serbia and Kosovo's Net change (3,292) (53,185) (277) 0 0 2,700 0 (54,054)
  Seychelles - Fleeing from (9) (11) 0 0 0 0 0 (20)
152 Seychelles's Net change (9) (11) 0 0 0 0 0 (20)
  Sierra Leone - Fleeing from (4,846) (3,465) 0 0 0 0 (1,479) (9,790)
  Sierra Leone - Received Into 760 7 0 0 0 0 0 767
153 Sierra Leone's Net change (4,086) (3,458) 0 0 0 0 (1,479) (9,023)
  Singapore - Fleeing from (50) (41) 0 0 0 0 0 (91)
154 Singapore's Net change (50) (41) 0 0 0 0 0 (91)
  Sint Maarten (Dutch part) - Received into 0 5 0 0 0 0 0 5
155 Sint Maarten (Dutch part)'s Net change 0 5 0 0 0 0 0 5
  Slovakia - Fleeing from (320) (542) 0 0 0 0 0 (862)
  Slovakia - Received Into 796 173 0 0 0 1,523 83 2,575
156 Slovakia's Net change 476 (369) 0 0 0 1,523 83 1,713
  Slovenia - Fleeing from (21) (10) 0 0 0 0 0 (31)
  Slovenia - Received Into 269 77 0 0 0 0 0 346
157 Slovenia's Net change 248 67 0 0 0 0 0 315
  Solomon Islands - Fleeing from (71) (37) 0 0 0 0 0 (108)
158 Solomon Islands's Net change (71) (37) 0 0 0 0 0 (108)
  Somalia - Fleeing from (1,123,010) (56,744) (32,343) (1,133,000) (5,000) 0 (823) (2,350,920)
  Somalia - Received Into 8,071 10,105 0 1,133,000 5,000 0 86 1,156,262
159 Somalia's Net change (1,114,939) (46,639) (32,343) 0 0 0 (737) (1,194,658)
  South Africa - Fleeing from (422) (860) 0 0 0 0 (5) (1,287)
  South Africa - Received Into 121,573 1,095,991 9 0 0 0 0 1,217,573
160 South Africa's Net change 121,151 1,095,131 9 0 0 0 (5) 1,216,286
  South Sudan - Fleeing from (778,661) (4,215) (159) (1,790,427) 0 0 (30) (2,573,492)
  South Sudan - Received Into 263,012 835 2,017 1,790,427 0 0 0 2,056,291
161 South Sudan's Net change (515,649) (3,380) 1,858 0 0 0 (30) (517,201)
  Spain - Fleeing from (50) (76) 0 0 0 0 0 (126)
  Spain - Received Into 5,737 11,013 0 0 0 440 0 17,190
162 Spain's Net change 5,687 10,937 0 0 0 440 0 17,064
  Sri Lanka - Fleeing from (121,399) (14,837) (849) (44,934) (8,112) 0 (17) (190,148)
  Sri Lanka - Received Into 776 598 0 44,934 8,112 0 0 54,420
163 Sri Lanka's Net change (120,623) (14,239) (849) 0 0 0 (17) (135,728)
  Stateless - Fleeing from (37,410) (18,584) 0 0 0 (3,687,716) 0 (3,743,710)
164 Stateless's Net change (37,410) (18,584) 0 0 0 (3,687,716) 0 (3,743,710)
  Sudan - Fleeing from (628,718) (45,058) (39,491) (3,218,234) (152,663) 0 (15) (4,084,179)
  Sudan - Received Into 309,627 12,576 6 3,218,234 152,663 0 3,355 3,696,461
165 Sudan's Net change (319,091) (32,482) (39,485) 0 0 0 3,340 (387,718)
  Suriname - Fleeing from (19) (40) 0 0 0 0 0 (59)
166 Suriname's Net change (19) (40) 0 0 0 0 0 (59)
  Swaziland - Fleeing from (213) (155) (7) 0 0 0 0 (375)
  Swaziland - Received Into 674 263 0 0 0 0 0 937
167 Swaziland's Net change 461 108 (7) 0 0 0 0 562
  Sweden - Fleeing from (8) 0 0 0 0 0 0 (8)
  Sweden - Received Into 169,461 156,991 0 0 0 31,062 0 357,514
168 Sweden's Net change 169,453 156,991 0 0 0 31,062 0 357,506
  Switzerland - Fleeing from (11) 0 0 0 0 0 0 (11)
  Switzerland - Received Into 73,261 32,641 42 0 0 69 0 106,013
169 Switzerland's Net change 73,250 32,641 42 0 0 69 0 106,002
  Syrian Arab Rep. - Fleeing from (4,872,548) (245,791) (188) (6,563,462) 0 0 (8,247) (11,690,236)
  Syrian Arab Rep. - Received Into 21,102 5,217 938 6,563,462 0 160,000 3,554 6,754,273
170 Syrian Arab Rep.'s Net change (4,851,446) (240,574) 750 0 0 160,000 (4,693) (4,935,963)
  Tajikistan - Fleeing from (765) (1,453) 0 0 0 0 0 (2,218)
  Tajikistan - Received Into 1,963 287 102 0 0 19,469 52 21,873
171 Tajikistan's Net change 1,198 (1,166) 102 0 0 19,469 52 19,655
  Thailand - Fleeing from (210) (829) 0 0 0 0 0 (1,039)
  Thailand - Received Into 108,237 8,231 17 0 0 443,862 438 560,785
172 Thailand's Net change 108,027 7,402 17 0 0 443,862 438 559,746
  The former Yugoslav Republic of Macedonia - Fleeing from (1,744) (14,607) 0 0 0 0 0 (16,351)
  The former Yugoslav Republic of Macedonia - Received into 697 5 172 0 0 667 0 1,541
173 The former Yugoslav Republic of Macedonia's Net change (1,047) (14,602) 172 0 0 667 0 (14,810)
  Tibetan - Fleeing from (15,069) 0 0 0 0 0 (6) (15,075)
174 Tibetan's Net change (15,069) 0 0 0 0 0 (6) (15,075)
  Timor-Leste - Fleeing from (14) 0 0 0 0 0 0 (14)
  Timor-Leste - Received Into 0 0 0 0 0 0 5 5
175 Timor-Leste's Net change (14) 0 0 0 0 0 5 (9)
  Togo - Fleeing from (8,739) (2,095) (6) 0 0 0 0 (10,840)
  Togo - Received Into 21,939 740 94 0 0 0 0 22,773
176 Togo's Net change 13,200 (1,355) 88 0 0 0 0 11,933
  Tonga - Fleeing from (22) (62) 0 0 0 0 0 (84)
177 Tonga's Net change (22) (62) 0 0 0 0 0 (84)
  Trinidad and Tobago - Fleeing from (369) (191) 0 0 0 0 0 (560)
  Trinidad and Tobago - Received Into 101 71 0 0 0 0 0 172
178 Trinidad and Tobago's Net change (268) (120) 0 0 0 0 0 (388)
  Tunisia - Fleeing from (1,544) (2,307) 0 0 0 0 (7) (3,858)
  Tunisia - Received Into 649 75 0 0 0 0 0 724
179 Tunisia's Net change (895) (2,232) 0 0 0 0 (7) (3,134)
  Turkey - Fleeing from (59,526) (12,063) 0 0 0 0 (12) (71,601)
  Turkey - Received Into 2,541,308 212,366 0 0 0 780 0 2,754,454
180 Turkey's Net change 2,481,782 200,303 0 0 0 780 (12) 2,682,853
  Turkmenistan - Fleeing from (421) (1,205) 0 0 0 0 0 (1,626)
  Turkmenistan - Received Into 25 0 7 0 0 7,125 0 7,157
181 Turkmenistan's Net change (396) (1,205) 7 0 0 7,125 0 5,531
  Turks and Caicos Islands - Fleeing from (14) 0 0 0 0 0 0 (14)
182 Turks and Caicos Islands's Net change (14) 0 0 0 0 0 0 (14)
  Uganda - Fleeing from (6,256) (6,429) (1,191) 0 0 0 (180,000) (193,876)
  Uganda - Received Into 477,167 35,758 6,847 0 0 0 180,000 699,772
183 Uganda's Net change 470,911 29,329 5,656 0 0 0 0 505,896
  Ukraine - Fleeing from (321,266) (22,524) 0 (1,600,000) 0 0 (5) (1,943,795)
  Ukraine - Received Into 3,226 6,446 10 1,600,000 0 35,228 0 1,644,910
184 Ukraine's Net change (318,040) (16,078) 10 0 0 35,228 (5) (298,885)
  United Arab Emirates - Fleeing from (91) (83) 0 0 0 0 0 (174)
  United Arab Emirates - Received into 658 417 169 0 0 0 0 1,244
185 United Arab Emirates's Net change 567 334 169 0 0 0 0 1,070
  United Kingdom - Fleeing from (128) (109) 0 0 0 0 0 (237)
  United Kingdom - Received Into 122,996 45,773 388 0 0 41 0 169,198
186 United Kingdom's Net change 122,868 45,664 388 0 0 41 0 168,961
  United Rep. of Tanzania - Fleeing from (6,181) (1,577) 0 0 0 0 (10) (7,768)
  United Rep. of Tanzania - Received into 211,845 2,150 5 0 0 0 168,625 382,625
187 United Rep. of Tanzania's Net change 205,664 573 5 0 0 0 168,615 374,857
  United States of America - Fleeing from (4,814) (217) 0 0 0 0 (10) (5,041)
  United States of America - Received into 273,113 286,146 0 0 0 0 0 559,259
188 United States of America's Net change 268,299 285,929 0 0 0 0 (10) 554,218
  Uruguay - Fleeing from (79) (52) 0 0 0 0 0 (131)
  Uruguay - Received Into 267 44 0 0 0 0 0 311
189 Uruguay's Net change 188 (8) 0 0 0 0 0 180
  Uzbekistan - Fleeing from (4,166) (2,655) 0 0 0 0 0 (6,821)
  Uzbekistan - Received Into 106 0 0 0 0 86,703 0 86,809
190 Uzbekistan's Net change (4,060) (2,655) 0 0 0 86,703 0 79,988
  Various/Unknown - Fleeing from (120,143) (1,035,150) 0 0 0 0 (14,244) (1,169,537)
191 Various/Unknown's Net change (120,143) (1,035,150) 0 0 0 0 (14,244) (1,169,537)
  Venezuela (Bolivarian Republic of) - Fleeing from (7,437) (15,062) 0 0 0 0 0 (22,499)
  Venezuela (Bolivarian Republic of) - Received into 173,705 182 1,765 0 0 0 0 175,652
192 Venezuela (Bolivarian Republic of)'s Net change 166,268 (14,880) 1,765 0 0 0 0 153,153
  Viet Nam - Fleeing from (313,132) (4,330) 0 0 0 0 (265) (317,727)
  Viet Nam - Received Into 0 0 0 0 0 11,000 0 11,000
193 Viet Nam's Net change (313,132) (4,330) 0 0 0 11,000 (265) (306,727)
  Western Sahara - Fleeing from (116,536) (1,428) 0 0 0 0 0 (117,964)
194 Western Sahara's Net change (116,536) (1,428) 0 0 0 0 0 (117,964)
  Yemen - Fleeing from (15,846) (10,048) 0 (2,532,032) 0 0 (12) (2,557,938)
  Yemen - Received Into 267,158 9,847 26,728 2,532,032 0 0 16 2,835,781
195 Yemen's Net change 251,312 (201) 26,728 0 0 0 4 277,843
  Zambia - Fleeing from (329) (308) 0 0 0 0 0 (637)
  Zambia - Received Into 26,429 2,383 419 0 0 0 23,321 52,552
196 Zambia's Net change 26,100 2,075 419 0 0 0 23,321 51,915
  Zimbabwe - Fleeing from (21,307) (57,385) (31) 0 0 0 (135) (78,858)
  Zimbabwe - Received Into 6,933 257 0 0 0 300,000 3,375 310,565
197 Zimbabwe's Net change (14,374) (57,128) (31) 0 0 300,000 3,240 231,707
Data Sources for Table:
United Nations High Commissioner for Refugees | Persons of Concern
United Nations High Commissioner for Refugees | Global Trends 2015

A key similarity between Syria's and Colombia's displaced residents was this. The residents of each country mainly were displaced by internal fighting or civil war. War itself is the age-old human story of one or more groups violently pitted against another group due to some dispute or another, which was not resolved diplomatically and congenially. Human conflict is natural and normal. Human conflict that results in humans murdering one another or otherwise doing great bodily harm to one another is not normal. Humans who torture and kill one another represent some of the most extreme and barbaric ways to resolve conflicts.

Some summary statistics to be gleaned from the above table include the following ones:

From a high-level, global perspective, for the year 2015, the refugee/displaced persons crisis can be summarized as follows:

When the above summary statistics are added together, they come to a grand total of 63,904,309 forcibly displaced persons worldwide in 2015. Click the following link to see some additional summary statistics:

Global Trends 2015

Moving beyond the statistics about refugees and displaced persons, the following videos are presented here to put a human face on these refugees and displaced persons.



Watch (What does it mean to be a refugee? - Benedetta Berti and Evelien Borgman)


Watch (UNHCR Global Trends Data 2015)


Watch (The human tragedy of African migration)


Watch (Colombia's fragile peace, explained)


Watch (Faces of displacement in Colombia)


Watch (Syria: What's Behind the Conflict)


Watch (Syria's War: Through the eyes of the people)


Watch (Number of Syrian refugees rises above 2 million)


Watch (Destination Europe: Syria's war refugees)


Watch (The cost of Syria's War - BBC News)

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THE HUMAN CONDITION

It seems like a natural human phenomenon to react adversely or negatively towards a culture, way of thinking, religious philosophy, race, gender, political philosophy, and so forth, that is markedly different from one's own reality. Some wars have their origins in this seemingly natural human phenomenon—notwithstanding genuine lifestyle differences within communities of residents and even differences in social discipline between communities of residents, which potentially can lead to community-level conflict.

There seems to be a human tolerance threshold for accepting those who are perceived as being different. The tolerance threshold seems to center on a majority-minority equation or the us-versus-them dynamic. That is to say, those who are perceived as different generally are accepted by the majority population as long as the so-called different ones remain the minority population. If those who are perceived as different stand poised to become the majority population and perhaps to take control of the major levers of power and access to resources, then tensions, upheavals, and conflicts tend to arise. For some, the tipping point might be anything greater than, say, a 20% minority population. For others, the tipping point might be, say, anything greater than a 40% minority population. When the threshold is breached, conflicts usually begin to ensue. But, is this seemingly natural human phenomenon of being less receptive to those who are perceived as being different a primitive psychological instinct? For, it is true that people tend not to be too receptive to what they perceive as radical or dramatic changes in the societal status quo. People tend to respond negatively to what they perceive as abrupt and disruptive changes to the societal status quo.

The following photo places the contemporary Western European immigration problem into perspective. The photo is representative of the classic invasion-succession thesis of neighborhood change. The invasion-succession thesis posits that when migrants or immigrants from dramatically different social or racial backgrounds move into the community (or country), conflict with the native population is inevitable as the immigrant population grows in size. As the immigrant population grows in size, the native population will tend to respond by enacting stricter national immigration policies and/or taking extraordinary steps to stem the flow of immigration. Succession begins to occur when members of the native population tend to retreat or flee from the immigrants and move into exclusive enclaves. As the natives flee to their own exclusive enclaves, the invasion-succession thesis posits that the old neighborhood begins to take on characteristics of the immigrants (say, for instance, Chinatown or Koreatown) who have succeeded in displacing the natives. Conflicts between natives and immigrants tend to arise not only at the national (policy) level but also particularly at the city and neighborhood physical levels. In the photo below, the yellow flowers can be viewed as representing the native and racially homogeneous Western European population. The red flowers can be viewed as representing, say, immigrants from Syria who fled the civil war (in search of stability). The white flowers can be viewed as, say, immigrants from Africa who fled poverty and political upheaval (in search of prosperity). The purple flowers can be viewed as other miscellaneous immigrants, say, from Eastern Asia, the Caribbean, or Latin America.

Wildflowers Wildflowers in the mountain meadow. NPS Photo / Credit: Walker Hall

For various reasons, humans, too, appear to be territorial creatures. Are humans capable of surmounting this primitive psychological instinct? Are humans resigned to accept the present-day state of human affairs "as is" because "That's The Way of the World" (Earth, Wind & Fire)? The larger questions become these: Do humans possess the capacity to overcome their territorial propensities and instincts? Are humans all across Earth capable of peacefully getting along with one another despite their differences? I think that the answer is, "Yes, they are very capable of overcoming their territorial instincts and getting along." I submit that life on Earth should not be about one group of humans wielding power over and dominating another group of humans. Instead, each individual should be able to pursue and attain his or her niche in society without recourse to prejudice and discrimination—notwithstanding the ongoing competition to secure a reasonably generous slice of the world's scarce resource pie. I realize that there are those in society who actively subscribe to the superiority-inferiority syndrome and, usually, they do so for all of the wrong reasons like advocating, promoting, and spreading feelings of hatred, ridicule, and scorn rather than feelings of courtesy, respect, and tolerance.

Much like certain civilizations have reigned supreme on Earth for large slices of time throughout the course of human history, I also realize that there are some in society—perhaps a vocal minority but also possibly a silent majority—who very strongly adhere to the notion that whites have emerged to reign as the most intelligent, superior, and supreme race on Earth. As a result, they vociferously are opposed to notions of racial mixing or any inter-racial breeding. To do so, they feel only will lead to an adverse and irreversible contamination, dilution, and destruction of an otherwise pure and superior white gene pool. Of course, in a free and open society such as the United States, some citizens are going to date whomever they wish despite what others in society might think of them.

The larger point, however, is this: Change is inevitable—hopefully, for the betterment of humanity instead of the extinction of humanity. People change and societies change. Nothing on Earth remains the same forever. No society, people, corporation, or civilization is invincible. No category of people holds a monopoly on excellence and wisdom. Recall the rise and fall of the dinosaurs or the rise and fall of empires. Even today as of 2016, many think that the USA has emerged as the most dominant nation on Earth. But, even in a dominant USA, I think it is a misplaced fear to think that a surging minority population bodes ill for the USA's future global dominance. Instead, I submit to you that the propagation of and a preoccupation with guns, gunplay, violence, hatred, and substance abuse are the more likely factors to lead to the USA's downfall as a global superpower. For instance, in my opinion, each time another state adopts legislation making it legal for citizens to recreationally use marijuana, then it represents a further erosion of the USA's social fabric. For, to me, legalizing the recreational use of marijuana, in effect, enables more citizens to become drug users and drug abusers. It leads citizens to opt for an altered state of consciousness in their daily lives—and, ultimately, a debilitating state of consciousness.

Based on Earth's history, it stands to reason that others countries, in time, inevitably will catch up to and surpass the USA in global stature albeit nobody truly knows how many years into the future it will be before that day arrives. So long as the USA remains true to its fundamental principles such as liberty (of speech, press, assembly, religion, movement, privacy from government intrusion into the home, etc.); justice (e.g., innocent until proven guilty with the right to representation by an attorney in criminal cases, speedy trials, beyond a reasonable doubt trials by jury, reasonable bails, etc.); equality of opportunity for all (e.g., in education, employment, housing, access to public facilities); equality of treatment, tolerance, and inclusiveness for all (regardless of race, religion, class, gender, ethnicity, age, sexual orientation, disability, political persuasion, etc.); and so on, then the USA will continue to be one of world's most admired countries—albeit admittedly the 200-plus-year USA journey, thus far, has been an imperfect one and remains a work in progress.

The key is to success in life appears to reside in the ability to successfully adapt to change. One's race per se should not be important in contemporary society with its division and specialization of labor. The thing that should matter the most in contemporary society is getting a good education and finding a niche in the broader civil society. The thing that should matter the most in contemporary society is becoming a productive and self-supporting member of civil society. The thing that should matter the most in contemporary society is treating your fellow humans with courtesy and respect without recourse to prejudice and discrimination. The thing that should matter the most in contemporary society is being a responsible and law-abiding member of civil society. For, as was so eloquently stated by Dr. Martin Luther King, Jr., if humans must resort to judging one another, then they should be judged by the contents of their characters rather than the colors of their skins. The operative phrase is "live and let live (in peace)" not "dog-eats-dog (in conflict)."

I faithfully submit to you that all humans are equally human. I continue to maintain that humans are one species stuck together here on lonely and delicate planet Earth by the force of gravity as they drift through the vast ocean of space that is known as the Universe. The Universe is expanding, and Earth is moving along with the expanding Universe. Just as the Earth continuously revolves on its axis as it simultaneously orbits the Sun, everything and everyone on Earth are tagging along for the ride as Earth, also, flies through time and space. Why not make Earth's journey through an expanding Universe a most wondrous ride for all human beings to experience each day?

Watch (Stevie Wonder, Saturn)


Watch (Maze featuring Frankie Beverly, In Time)


Watch (Stevie Wonder, Visions)


Watch (Our Solar System - Size Of Planets and Stars to Scale)

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BREAKING THE CYCLE OF EARTH'S NEVER-ENDING WARS

Unfortunately, in much the same sense as some of the most extreme followers of Islam appear to find themselves stuck in a 7th century time warp in their strict and literal interpretations of ancient Islamic writings and in much the same sense that some street gang members find themselves trapped in a seemingly never-ending cycle of violence and hatred, there remain some contemporary world leaders who appear to find themselves stuck or trapped in some sort of Cold War time warp. While most of the world seem ready to move beyond the Cold War for the betterment of humanity, this group of world leaders seems more interested in fermenting and spreading war, destruction, killing, dominance, and divisiveness across Earth. Don't these world leaders have better things to do with their time other than sitting around ego-tripping, power-tripping, and stirring up a bunch of mess?

The larger question is this: If humans do not get their collective acts together, will all of their non-stop bickering and warring ultimately lead to human extinction and the end of the world? Calmer heads have to prevail during these tense, provocative, dangerous, and challenging times (of nuclear weapons, of high science like genetic engineering, and of high technology like nanobots and self-driving vehicles) in a global economy. Progress is a good thing, but humans have got to transition into a new kind of Earth with an over-abundance of caution. Perhaps planned progress represents a better way for humans to proceed into the future instead of ad hoc progress.

The time has come for these old-guard world leaders to let it go or step aside before it is too late for humankind. The time has come for these world leaders to abandon their geopolitical machinations and nuclear ambitions so emblematic of an anachronistic past of world domination proclivities. Now is the time for these world leaders to break the cycle of the scourge of war on Earth. The time has come for a newer, higher, and deeper dimension of human living to take hold and flourish on Earth. Now is the time for humans to experience revolutionary progress and revolutionary improvements in the daily quality of life on Earth for all, which I often refer to as a state of Heaven on Earth for the living to enjoy each day in the extant age of Homo sapiens sapiens.

Watch (George Benson, This Masquerade)


Watch (Stevie Wonder, Pastime Paradise)


Watch (Earth: A Brief History)


I particularly am disheartened and disenchanted as I ponder how, on the one hand, over a billion humans are walking around Earth each day who must survive off as little as $2 a day (if that much), malnourished, in poor health, and who do not have access to clean drinking water or decent shelter. While, on the other hand, USA politicians seem fixated and fascinated with incessantly bickering over email scandals and sex scandals or engaging in name-calling, finger-pointing, and stalemate instead of pursuing progress. I am asking myself, "Really? Seriously? Nothing more important for USA politicians to do except obsess, squabble, and snipe over email scandals and sex scandals? Where are their priorities?" Do you think the world's have-nots give a hoot about some emails? No, the world's have-nots do not have the luxury of sitting around bickering over emails. The world's have-nots can only think about surviving. Yet, all humans should give a hoot about the world's stockpiles of nuclear, chemical, biological, and radiological weapons for the whole of life on Earth lies in the balance in the face of these extinction-inducing weapons of mass destruction.

To be sure, distracted USA politicians remind me of the case of Barry Bonds. While I agree that the integrity of professional sports must be upheld and doping in professional sports must not be tolerated, it was bewildering to me how much energy and money the government devoted to prosecuting Barry Bonds for his alleged doping transgression while the drug lords went about their business of smuggling tons of illicit drugs into the country and smuggling tons of money and weapons outside the country. Wouldn't the government's money and time have been better spent disrupting the drug trade instead of being distracted with prosecuting Barry Bonds? These tons of smuggled illicit drugs are destroying thousands of lives each day. People are dying from substance overdoses. Even as Barry Bonds was being prosecuted by the government for his alleged flaunting with doping, the government allowed drug mills to legally prescribe dozens of pills to customers leading to even more substance use, abuse, and trade—with much more profound adverse consequences to citizens than the case of Barry Bonds.

Now is the time to surmount the USA-style politics of tarnishing, banishing, and vanquishing one's political rival(s) at all costs for the mere sake of wielding power. Instead, the focus of politicians should be that of advancing new ideas to find the best ways to elevate the daily quality of life for all humans on Earth. Now is the time for politicians to abandon the political silliness and turn their attention to the more serious matter of transforming Earth into some sort of paradise. Why not? There is nothing to lose and everything to gain by transforming Earth into some type of paradise for the living to enjoy each day. To be sure, when I speak of World War 3, it is not a hot war. World War 3 is not even a cold war. World War 3 is an individualized inner struggle to discard an old way of thinking and to embrace a new mentality of perpetual peace on Earth and goodwill between humans.

Watch (Herbie Hancock, Sunlight)


Watch (Ramsey Lewis featuring Earth, Wind & Fire, Sun Goddess)


Watch [Michael Jackson, Heal The World (January 31, 1993 Pasadena, California - SuperBowl XXVII Half-Time Show)]

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