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THE EARTH TODAY

The human species is a diverse species. The human species is multicultural, multiracial, multireligious, multilingual, multinational, and so forth. Yet, contemporary technology is compressing time and space. Technology in conjunction with urbanization is bringing humans from all walks of life closer and closer together. Humans are being brought closer together by such things as rapid transporation (such as trains, cars, and airplanes) and mass communications (such as the telephone, television, and Internet). There even are some who envision a future of human teleportation. Such a future would be revolutionary beyond anything humans have phantomed, that is, if teleporation were to become a reality one day. Teleportation would shatter all existing human notions about time and space. Over the ages, the diversity of the human species often has been a source of conflict and misunderstanding (albeit other intangible things such as greed, money, egotism, and power also have played historical roles in fostering human conflict).

Count Country Name Country ID ISO2 Code Capital City Profile Geoname Income Level Lending Type Longitude Latitude Region
1 Afghanistan AFG AF Kabul Profile Geoname Low income IDA 69.1761 34.5228 South Asia
2 Albania ALB AL Tirane Profile Geoname Lower middle income IBRD 19.8172 41.3317 Europe & Central Asia
3 Algeria DZA DZ Algiers Profile Geoname Upper middle income IBRD 3.05097 36.7397 Middle East & North Africa
4 American Samoa ASM AS Pago Pago Profile Geoname Upper middle income Not classified -170.691 -14.2846 East Asia & Pacific
5 Andorra AND AD Andorra la Vella Profile Geoname High income: nonOECD Not classified 1.5218 42.5075 Europe & Central Asia
6 Angola AGO AO Luanda Profile Geoname Upper middle income IDA 13.242 -8.81155 Sub-Saharan Africa
7 Antigua and Barbuda ATG AG Saint John's Profile Geoname Upper middle income IBRD -61.8456 17.1175 Latin America & Caribbean
8 Argentina ARG AR Buenos Aires Profile Geoname Upper middle income IBRD -58.4173 -34.6118 Latin America & Caribbean
9 Armenia ARM AM Yerevan Profile Geoname Lower middle income Blend 44.509 40.1596 Europe & Central Asia
10 Aruba ABW AW Oranjestad Profile Geoname High income: nonOECD Not classified -70.0167 12.5167 Latin America & Caribbean
11 Australia AUS AU Canberra Profile Geoname High income: OECD Not classified 149.129 -35.282 East Asia & Pacific
12 Austria AUT AT Vienna Profile Geoname High income: OECD Not classified 16.3798 48.2201 Europe & Central Asia
13 Azerbaijan AZE AZ Baku Profile Geoname Upper middle income IBRD 49.8932 40.3834 Europe & Central Asia
14 Bahamas, The BHS BS Nassau Profile Geoname High income: nonOECD Not classified -77.339 25.0661 Latin America & Caribbean
15 Bahrain BHR BH Manama Profile Geoname High income: nonOECD Not classified 50.5354 26.1921 Middle East & North Africa
16 Bangladesh BGD BD Dhaka Profile Geoname Low income IDA 90.4113 23.7055 South Asia
17 Barbados BRB BB Bridgetown Profile Geoname High income: nonOECD Not classified -59.6105 13.0935 Latin America & Caribbean
18 Belarus BLR BY Minsk Profile Geoname Upper middle income IBRD 27.5766 53.9678 Europe & Central Asia
19 Belgium BEL BE Brussels Profile Geoname High income: OECD Not classified 4.36761 50.8371 Europe & Central Asia
20 Belize BLZ BZ Belmopan Profile Geoname Lower middle income IBRD -88.7713 17.2534 Latin America & Caribbean
21 Benin BEN BJ Porto-Novo Profile Geoname Low income IDA 2.6323 6.4779 Sub-Saharan Africa
22 Bermuda BMU BM Hamilton Profile Geoname High income: nonOECD Not classified -64.706 32.3293 North America
23 Bhutan BTN BT Thimphu Profile Geoname Lower middle income IDA 89.6177 27.5768 South Asia
24 Bolivia BOL BO La Paz Profile Geoname Lower middle income Blend -66.1936 -13.9908 Latin America & Caribbean
25 Bosnia and Herzegovina BIH BA Sarajevo Profile Geoname Upper middle income Blend 18.4214 43.8607 Europe & Central Asia
26 Botswana BWA BW Gaborone Profile Geoname Upper middle income IBRD 25.9201 -24.6544 Sub-Saharan Africa
27 Brazil BRA BR Brasilia Profile Geoname Upper middle income IBRD -47.9292 -15.7801 Latin America & Caribbean
28 Brunei Darussalam BRN BN Bandar Seri Begawan Profile Geoname High income: nonOECD Not classified 114.946 4.94199 East Asia & Pacific
29 Bulgaria BGR BG Sofia Profile Geoname Upper middle income IBRD 23.3238 42.7105 Europe & Central Asia
30 Burkina Faso BFA BF Ouagadougou Profile Geoname Low income IDA -1.53395 12.3605 Sub-Saharan Africa
31 Burundi BDI BI Bujumbura Profile Geoname Low income IDA 29.3639 -3.3784 Sub-Saharan Africa
32 Cambodia KHM KH Phnom Penh Profile Geoname Low income IDA 104.874 11.5556 East Asia & Pacific
33 Cameroon CMR CM Yaounde Profile Geoname Lower middle income IDA 11.5174 3.8721 Sub-Saharan Africa
34 Canada CAN CA Ottawa Profile Geoname High income: OECD Not classified -75.6919 45.4215 North America
35 Cape Verde CPV CV Praia Profile Geoname Lower middle income Blend -23.5087 14.9218 Sub-Saharan Africa
36 Cayman Islands CYM KY George Town Profile Geoname High income: nonOECD Not classified -81.3857 19.3022 Latin America & Caribbean
37 Central African Republic CAF CF Bangui Profile Geoname Low income IDA 21.6407 5.63056 Sub-Saharan Africa
38 Chad TCD TD N'Djamena Profile Geoname Low income IDA 15.0445 12.1048 Sub-Saharan Africa
39 Channel Islands CHI JG   Profile Geoname High income: nonOECD Not classified & & Europe & Central Asia
40 Chile CHL CL Santiago Profile Geoname Upper middle income IBRD -70.6475 -33.475 Latin America & Caribbean
41 China CHN CN Beijing Profile Geoname Upper middle income IBRD 116.286 40.0495 East Asia & Pacific
42 Colombia COL CO Bogota Profile Geoname Upper middle income IBRD -74.082 4.60987 Latin America & Caribbean
43 Comoros COM KM Moroni Profile Geoname Low income IDA 43.2418 -11.6986 Sub-Saharan Africa
44 Congo, Dem. Rep. COD CD Kinshasa Profile Geoname Low income IDA 15.3222 -4.325 Sub-Saharan Africa
45 Congo, Rep. COG CG Brazzaville Profile Geoname Lower middle income IDA 15.2662 -4.2767 Sub-Saharan Africa
46 Costa Rica CRI CR San Jose Profile Geoname Upper middle income IBRD -84.0089 9.63701 Latin America & Caribbean
47 Cote d'Ivoire CIV CI Yamoussoukro Profile Geoname Lower middle income IDA -4.0305 5.332 Sub-Saharan Africa
48 Croatia HRV HR Zagreb Profile Geoname High income: nonOECD IBRD 15.9614 45.8069 Europe & Central Asia
49 Cuba CUB CU Havana Profile Geoname Upper middle income Not classified -82.3667 23.1333 Latin America & Caribbean
50 Curacao CUW CW Willemstad Profile Geoname High income: nonOECD Not classified & & Latin America & Caribbean
51 Cyprus CYP CY Nicosia Profile Geoname High income: nonOECD Not classified 33.3736 35.1676 Europe & Central Asia
52 Czech Republic CZE CZ Prague Profile Geoname High income: OECD Not classified 14.4205 50.0878 Europe & Central Asia
53 Denmark DNK DK Copenhagen Profile Geoname High income: OECD Not classified 12.5681 55.6763 Europe & Central Asia
54 Djibouti DJI DJ Djibouti Profile Geoname Lower middle income IDA 43.1425 11.5806 Middle East & North Africa
55 Dominica DMA DM Roseau Profile Geoname Upper middle income Blend -61.39 15.2976 Latin America & Caribbean
56 Dominican Republic DOM DO Santo Domingo Profile Geoname Upper middle income IBRD -69.8908 18.479 Latin America & Caribbean
57 Ecuador ECU EC Quito Profile Geoname Upper middle income IBRD -78.5243 -0.229498 Latin America & Caribbean
58 Egypt, Arab Rep. EGY EG Cairo Profile Geoname Lower middle income IBRD 31.2461 30.0982 Middle East & North Africa
59 El Salvador SLV SV San Salvador Profile Geoname Lower middle income IBRD -89.2073 13.7034 Latin America & Caribbean
60 Equatorial Guinea GNQ GQ Malabo Profile Geoname High income: nonOECD IBRD 8.7741 3.7523 Sub-Saharan Africa
61 Eritrea ERI ER Asmara Profile Geoname Low income IDA 38.9183 15.3315 Sub-Saharan Africa
62 Estonia EST EE Tallinn Profile Geoname High income: OECD Not classified 24.7586 59.4392 Europe & Central Asia
63 Ethiopia ETH ET Addis ababa Profile Geoname Low income IDA 38.7468 9.02274 Sub-Saharan Africa
64 Faeroe Islands FRO FO Torshavn Profile Geoname High income: nonOECD Not classified -6.91181 61.8926 Europe & Central Asia
65 Fiji FJI FJ Suva Profile Geoname Lower middle income IBRD 178.399 -18.1149 East Asia & Pacific
66 Finland FIN FI Helsinki Profile Geoname High income: OECD Not classified 24.9525 60.1608 Europe & Central Asia
67 France FRA FR Paris Profile Geoname High income: OECD Not classified 2.35097 48.8566 Europe & Central Asia
68 French Polynesia PYF PF Papeete Profile Geoname High income: nonOECD Not classified -149.57 -17.535 East Asia & Pacific
69 Gabon GAB GA Libreville Profile Geoname Upper middle income IBRD 9.45162 0.38832 Sub-Saharan Africa
70 Gambia, The GMB GM Banjul Profile Geoname Low income IDA -16.5885 13.4495 Sub-Saharan Africa
71 Georgia GEO GE Tbilisi Profile Geoname Lower middle income Blend 44.793 41.71 Europe & Central Asia
72 Germany DEU DE Berlin Profile Geoname High income: OECD Not classified 13.4115 52.5235 Europe & Central Asia
73 Ghana GHA GH Accra Profile Geoname Lower middle income IDA -0.20795 5.57045 Sub-Saharan Africa
74 Greece GRC GR Athens Profile Geoname High income: OECD Not classified 23.7166 37.9792 Europe & Central Asia
75 Greenland GRL GL Nuuk Profile Geoname High income: nonOECD Not classified -51.7214 64.1836 Europe & Central Asia
76 Grenada GRD GD Saint George's Profile Geoname Upper middle income Blend -61.7449 12.0653 Latin America & Caribbean
77 Guam GUM GU Agana Profile Geoname High income: nonOECD Not classified 144.794 13.4443 East Asia & Pacific
78 Guatemala GTM GT Guatemala City Profile Geoname Lower middle income IBRD -90.5328 14.6248 Latin America & Caribbean
79 Guinea GIN GN Conakry Profile Geoname Low income IDA -13.7 9.51667 Sub-Saharan Africa
80 Guinea-Bissau GNB GW Bissau Profile Geoname Low income IDA -15.1804 11.8037 Sub-Saharan Africa
81 Guyana GUY GY Georgetown Profile Geoname Lower middle income IDA -58.1548 6.80461 Latin America & Caribbean
82 Haiti HTI HT Port-au-Prince Profile Geoname Low income IDA -72.3288 18.5392 Latin America & Caribbean
83 Honduras HND HN Tegucigalpa Profile Geoname Lower middle income IDA -87.4667 15.1333 Latin America & Caribbean
84 Hong Kong SAR, China HKG HK   Profile Geoname High income: nonOECD Not classified 114.109 22.3964 East Asia & Pacific
85 Hungary HUN HU Budapest Profile Geoname High income: OECD Not classified 19.0408 47.4984 Europe & Central Asia
86 Iceland ISL IS Reykjavik Profile Geoname High income: OECD Not classified -21.8952 64.1353 Europe & Central Asia
87 India IND IN New Delhi Profile Geoname Lower middle income Blend 77.225 28.6353 South Asia
88 Indonesia IDN ID Jakarta Profile Geoname Lower middle income IBRD 106.83 -6.19752 East Asia & Pacific
89 Iran, Islamic Rep. IRN IR Tehran Profile Geoname Upper middle income IBRD 51.4447 35.6878 Middle East & North Africa
90 Iraq IRQ IQ Baghdad Profile Geoname Lower middle income IBRD 44.394 33.3302 Middle East & North Africa
91 Ireland IRL IE Dublin Profile Geoname High income: OECD Not classified -6.26749 53.3441 Europe & Central Asia
92 Isle of Man IMN IM Douglas Profile Geoname High income: nonOECD Not classified -4.47928 54.1509 Europe & Central Asia
93 Israel ISR IL   Profile Geoname High income: OECD Not classified 35.2035 31.7717 Middle East & North Africa
94 Italy ITA IT Rome Profile Geoname High income: OECD Not classified 12.4823 41.8955 Europe & Central Asia
95 Jamaica JAM JM Kingston Profile Geoname Upper middle income IBRD -76.792 17.9927 Latin America & Caribbean
96 Japan JPN JP Tokyo Profile Geoname High income: OECD Not classified 139.77 35.67 East Asia & Pacific
97 Jordan JOR JO Amman Profile Geoname Upper middle income IBRD 35.9263 31.9497 Middle East & North Africa
98 Kazakhstan KAZ KZ Astana Profile Geoname Upper middle income IBRD 71.4382 51.1879 Europe & Central Asia
99 Kenya KEN KE Nairobi Profile Geoname Low income IDA 36.8126 -1.27975 Sub-Saharan Africa
100 Kiribati KIR KI Tarawa Profile Geoname Lower middle income IDA 172.979 1.32905 East Asia & Pacific
101 Korea, Dem. Rep. PRK KP Pyongyang Profile Geoname Low income Not classified 125.754 39.0319 East Asia & Pacific
102 Korea, Rep. KOR KR Seoul Profile Geoname High income: OECD IBRD 126.957 37.5323 East Asia & Pacific
103 Kosovo KSV KV Pristina Profile Geoname Lower middle income IDA 20.926 42.565 Europe & Central Asia
104 Kuwait KWT KW Kuwait City Profile Geoname High income: nonOECD Not classified 47.9824 29.3721 Middle East & North Africa
105 Kyrgyz Republic KGZ KG Bishkek Profile Geoname Low income IDA 74.6057 42.8851 Europe & Central Asia
106 Lao PDR LAO LA Vientiane Profile Geoname Lower middle income IDA 102.177 18.5826 East Asia & Pacific
107 Latvia LVA LV Riga Profile Geoname Upper middle income Not classified 24.1048 56.9465 Europe & Central Asia
108 Lebanon LBN LB Beirut Profile Geoname Upper middle income IBRD 35.5134 33.8872 Middle East & North Africa
109 Lesotho LSO LS Maseru Profile Geoname Lower middle income IDA 27.7167 -29.5208 Sub-Saharan Africa
110 Liberia LBR LR Monrovia Profile Geoname Low income IDA -10.7957 6.30039 Sub-Saharan Africa
111 Libya LBY LY Tripoli Profile Geoname Upper middle income IBRD 13.1072 32.8578 Middle East & North Africa
112 Liechtenstein LIE LI Vaduz Profile Geoname High income: nonOECD Not classified 9.52148 47.1411 Europe & Central Asia
113 Lithuania LTU LT Vilnius Profile Geoname Upper middle income Not classified 25.2799 54.6896 Europe & Central Asia
114 Luxembourg LUX LU Luxembourg Profile Geoname High income: OECD Not classified 6.1296 49.61 Europe & Central Asia
115 Macao SAR, China MAC MO   Profile Geoname High income: nonOECD Not classified 113.55 22.1667 East Asia & Pacific
116 Macedonia, FYR MKD MK Skopje Profile Geoname Upper middle income IBRD 21.4361 42.0024 Europe & Central Asia
117 Madagascar MDG MG Antananarivo Profile Geoname Low income IDA 45.7167 -20.4667 Sub-Saharan Africa
118 Malawi MWI MW Lilongwe Profile Geoname Low income IDA 33.7703 -13.9899 Sub-Saharan Africa
119 Malaysia MYS MY Kuala Lumpur Profile Geoname Upper middle income IBRD 101.684 3.12433 East Asia & Pacific
120 Maldives MDV MV Male Profile Geoname Upper middle income IDA 73.5109 4.1742 South Asia
121 Mali MLI ML Bamako Profile Geoname Low income IDA -7.50034 13.5667 Sub-Saharan Africa
122 Malta MLT MT Valletta Profile Geoname High income: nonOECD Not classified 14.5189 35.9042 Middle East & North Africa
123 Marshall Islands MHL MH Majuro Profile Geoname Lower middle income IDA 171.135 7.11046 East Asia & Pacific
124 Mauritania MRT MR Nouakchott Profile Geoname Low income IDA -15.9824 18.2367 Sub-Saharan Africa
125 Mauritius MUS MU Port Louis Profile Geoname Upper middle income IBRD 57.4977 -20.1605 Sub-Saharan Africa
126 Mexico MEX MX Mexico City Profile Geoname Upper middle income IBRD -99.1276 19.427 Latin America & Caribbean
127 Micronesia, Fed. Sts. FSM FM Palikir Profile Geoname Lower middle income IDA 158.185 6.91771 East Asia & Pacific
128 Moldova MDA MD Chisinau Profile Geoname Lower middle income IDA 28.8497 47.0167 Europe & Central Asia
129 Monaco MCO MC Monaco Profile Geoname High income: nonOECD Not classified 7.41891 43.7325 Europe & Central Asia
130 Mongolia MNG MN Ulaanbaatar Profile Geoname Lower middle income Blend 106.937 47.9129 East Asia & Pacific
131 Montenegro MNE ME Podgorica Profile Geoname Upper middle income IBRD 19.2595 42.4602 Europe & Central Asia
132 Morocco MAR MA Rabat Profile Geoname Lower middle income IBRD -6.8704 33.9905 Middle East & North Africa
133 Mozambique MOZ MZ Maputo Profile Geoname Low income IDA 32.5713 -25.9664 Sub-Saharan Africa
134 Myanmar MMR MM Naypyidaw Profile Geoname Low income IDA 95.9562 21.914 East Asia & Pacific
135 Namibia NAM NA Windhoek Profile Geoname Upper middle income IBRD 17.0931 -22.5648 Sub-Saharan Africa
136 Nepal NPL NP Kathmandu Profile Geoname Low income IDA 85.3157 27.6939 South Asia
137 Netherlands NLD NL Amsterdam Profile Geoname High income: OECD Not classified 4.89095 52.3738 Europe & Central Asia
138 New Caledonia NCL NC Noum'ea Profile Geoname High income: nonOECD Not classified 166.464 -22.2677 East Asia & Pacific
139 New Zealand NZL NZ Wellington Profile Geoname High income: OECD Not classified 174.776 -41.2865 East Asia & Pacific
140 Nicaragua NIC NI Managua Profile Geoname Lower middle income IDA -86.2734 12.1475 Latin America & Caribbean
141 Niger NER NE Niamey Profile Geoname Low income IDA 2.1073 13.514 Sub-Saharan Africa
142 Nigeria NGA NG Abuja Profile Geoname Lower middle income IDA 7.48906 9.05804 Sub-Saharan Africa
143 Northern Mariana Islands MNP MP Saipan Profile Geoname High income: nonOECD Not classified 145.765 15.1935 East Asia & Pacific
144 Norway NOR NO Oslo Profile Geoname High income: OECD Not classified 10.7387 59.9138 Europe & Central Asia
145 Oman OMN OM Muscat Profile Geoname High income: nonOECD Not classified 58.5874 23.6105 Middle East & North Africa
146 Pakistan PAK PK Islamabad Profile Geoname Lower middle income Blend 72.8 30.5167 South Asia
147 Palau PLW PW Koror Profile Geoname Upper middle income IBRD 134.479 7.34194 East Asia & Pacific
148 Panama PAN PA Panama City Profile Geoname Upper middle income IBRD -79.5188 8.99427 Latin America & Caribbean
149 Papua New Guinea PNG PG Port Moresby Profile Geoname Lower middle income Blend 147.194 -9.47357 East Asia & Pacific
150 Paraguay PRY PY Asuncion Profile Geoname Lower middle income IBRD -57.6362 -25.3005 Latin America & Caribbean
151 Peru PER PE Lima Profile Geoname Upper middle income IBRD -77.0465 -12.0931 Latin America & Caribbean
152 Philippines PHL PH Manila Profile Geoname Lower middle income IBRD 121.035 14.5515 East Asia & Pacific
153 Poland POL PL Warsaw Profile Geoname High income: OECD IBRD 21.02 52.26 Europe & Central Asia
154 Portugal PRT PT Lisbon Profile Geoname High income: OECD Not classified -9.13552 38.7072 Europe & Central Asia
155 Puerto Rico PRI PR San Juan Profile Geoname High income: nonOECD Not classified -66 18.23 Latin America & Caribbean
156 Qatar QAT QA Doha Profile Geoname High income: nonOECD Not classified 51.5082 25.2948 Middle East & North Africa
157 Romania ROU RO Bucharest Profile Geoname Upper middle income IBRD 26.0979 44.4479 Europe & Central Asia
158 Russian Federation RUS RU Moscow Profile Geoname Upper middle income IBRD 37.6176 55.7558 Europe & Central Asia
159 Rwanda RWA RW Kigali Profile Geoname Low income IDA 30.0587 -1.95325 Sub-Saharan Africa
160 Samoa WSM WS Apia Profile Geoname Lower middle income IDA -171.752 -13.8314 East Asia & Pacific
161 San Marino SMR SM San Marino Profile Geoname High income: nonOECD Not classified 12.4486 43.9322 Europe & Central Asia
162 Sao Tome and Principe STP ST Sao Tome Profile Geoname Lower middle income IDA 6.6071 0.20618 Sub-Saharan Africa
163 Saudi Arabia SAU SA Riyadh Profile Geoname High income: nonOECD Not classified 46.6977 24.6748 Middle East & North Africa
164 Senegal SEN SN Dakar Profile Geoname Lower middle income IDA -17.4734 14.7247 Sub-Saharan Africa
165 Serbia SRB RS Belgrade Profile Geoname Upper middle income IBRD 20.4656 44.8024 Europe & Central Asia
166 Seychelles SYC SC Victoria Profile Geoname Upper middle income IBRD 55.4466 -4.6309 Sub-Saharan Africa
167 Sierra Leone SLE SL Freetown Profile Geoname Low income IDA -13.2134 8.4821 Sub-Saharan Africa
168 Singapore SGP SG Singapore Profile Geoname High income: nonOECD Not classified 103.85 1.28941 East Asia & Pacific
169 Sint Maarten (Dutch part) SXM SX Philipsburg Profile Geoname High income: nonOECD Not classified & & Latin America & Caribbean
170 Slovak Republic SVK SK Bratislava Profile Geoname High income: OECD Not classified 17.1073 48.1484 Europe & Central Asia
171 Slovenia SVN SI Ljubljana Profile Geoname High income: OECD Not classified 14.5044 46.0546 Europe & Central Asia
172 Solomon Islands SLB SB Honiara Profile Geoname Lower middle income IDA 159.949 -9.42676 East Asia & Pacific
173 Somalia SOM SO Mogadishu Profile Geoname Low income IDA 45.3254 2.07515 Sub-Saharan Africa
174 South Africa ZAF ZA Pretoria Profile Geoname Upper middle income IBRD 28.1871 -25.746 Sub-Saharan Africa
175 South Sudan SSD SS Juba Profile Geoname Lower middle income Not classified 31.6 4.85 Sub-Saharan Africa
176 Spain ESP ES Madrid Profile Geoname High income: OECD Not classified -3.70327 40.4167 Europe & Central Asia
177 Sri Lanka LKA LK Colombo Profile Geoname Lower middle income Blend 79.8528 6.92148 South Asia
178 St. Kitts and Nevis KNA KN Basseterre Profile Geoname High income: nonOECD Not classified -62.7309 17.3 Latin America & Caribbean
179 St. Lucia LCA LC Castries Profile Geoname Upper middle income Blend -60.9832 14 Latin America & Caribbean
180 St. Martin (French part) MAF MF Marigot Profile Geoname High income: nonOECD Not classified & & Latin America & Caribbean
181 St. Vincent and the Grenadines VCT VC Kingstown Profile Geoname Upper middle income Blend -61.2653 13.2035 Latin America & Caribbean
182 Sudan SDN SD Khartoum Profile Geoname Lower middle income IDA 32.5363 15.5932 Sub-Saharan Africa
183 Suriname SUR SR Paramaribo Profile Geoname Upper middle income IBRD -55.1679 5.8232 Latin America & Caribbean
184 Swaziland SWZ SZ Mbabane Profile Geoname Lower middle income IBRD 31.4659 -26.5225 Sub-Saharan Africa
185 Sweden SWE SE Stockholm Profile Geoname High income: OECD Not classified 18.0645 59.3327 Europe & Central Asia
186 Switzerland CHE CH Bern Profile Geoname High income: OECD Not classified 7.44821 46.948 Europe & Central Asia
187 Syrian Arab Republic SYR SY Damascus Profile Geoname Lower middle income IBRD 36.3119 33.5146 Middle East & North Africa
188 Tajikistan TJK TJ Dushanbe Profile Geoname Low income IDA 68.7864 38.5878 Europe & Central Asia
189 Tanzania TZA TZ Dodoma Profile Geoname Low income IDA 35.7382 -6.17486 Sub-Saharan Africa
190 Thailand THA TH Bangkok Profile Geoname Upper middle income IBRD 100.521 13.7308 East Asia & Pacific
191 Timor-Leste TLS TL Dili Profile Geoname Lower middle income IDA 125.567 -8.56667 East Asia & Pacific
192 Togo TGO TG Lome Profile Geoname Low income IDA 1.2255 6.1228 Sub-Saharan Africa
193 Tonga TON TO Nuku'alofa Profile Geoname Lower middle income IDA -175.216 -21.136 East Asia & Pacific
194 Trinidad and Tobago TTO TT Port-of-Spain Profile Geoname High income: nonOECD IBRD -61.4789 10.6596 Latin America & Caribbean
195 Tunisia TUN TN Tunis Profile Geoname Upper middle income IBRD 10.21 36.7899 Middle East & North Africa
196 Turkey TUR TR Ankara Profile Geoname Upper middle income IBRD 32.3606 39.7153 Europe & Central Asia
197 Turkmenistan TKM TM Ashgabat Profile Geoname Upper middle income IBRD 58.3794 37.9509 Europe & Central Asia
198 Turks and Caicos Islands TCA TC Grand Turk Profile Geoname High income: nonOECD Not classified -71.141389 21.4602778 Latin America & Caribbean
199 Tuvalu TUV TV Funafuti Profile Geoname Upper middle income IDA 179.089567 -8.6314877 East Asia & Pacific
200 Uganda UGA UG Kampala Profile Geoname Low income IDA 32.5729 0.314269 Sub-Saharan Africa
201 Ukraine UKR UA Kiev Profile Geoname Lower middle income IBRD 30.5038 50.4536 Europe & Central Asia
202 United Arab Emirates ARE AE Abu Dhabi Profile Geoname High income: nonOECD Not classified 54.3705 24.4764 Middle East & North Africa
203 United Kingdom GBR GB London Profile Geoname High income: OECD Not classified -0.126236 51.5002 Europe & Central Asia
204 United States USA US Washington D.C. Profile Geoname High income: OECD Not classified -77.032 38.8895 North America
205 Uruguay URY UY Montevideo Profile Geoname Upper middle income IBRD -56.0675 -34.8941 Latin America & Caribbean
206 Uzbekistan UZB UZ Tashkent Profile Geoname Lower middle income Blend 69.269 41.3052 Europe & Central Asia
207 Vanuatu VUT VU Port-Vila Profile Geoname Lower middle income IDA 168.321 -17.7404 East Asia & Pacific
208 Venezuela, RB VEN VE Caracas Profile Geoname Upper middle income IBRD -69.8371 9.08165 Latin America & Caribbean
209 Vietnam VNM VN Hanoi Profile Geoname Lower middle income Blend 105.825 21.0069 East Asia & Pacific
210 Virgin Islands (U.S.) VIR VI Charlotte Amalie Profile Geoname High income: nonOECD Not classified -64.8963 18.3358 Latin America & Caribbean
211 West Bank and Gaza PSE PS   Profile Geoname Lower middle income Not classified & & Middle East & North Africa
212 Yemen, Rep. YEM YE Sana'a Profile Geoname Lower middle income IDA 44.2075 15.352 Middle East & North Africa
213 Zambia ZMB ZM Lusaka Profile Geoname Lower middle income IDA 28.2937 -15.3982 Sub-Saharan Africa
214 Zimbabwe ZWE ZW Harare Profile Geoname Low income Blend 31.0672 -17.8312 Sub-Saharan Africa
215 WORLD       Profile Geoname         WORLD


Credit for Data in Table:
The World Bank - "Data Catalog | Data"

Amid this human diversity there also is a trend towards uniformity. For instance, humans have sought to foster a uniform system of measurement on Earth. Most would acknowledge that the metric system is the de facto international system of measurement. Humans have not yet found a way to speak as one, but there are some who contend that English slowly is becoming the de facto international language. Although the euro has gained in popularity at the dawn of the 21st century, generally speaking, many consider the USA dollar to be the de facto international currency. Despite advances towards higher degrees of human uniformity and understanding, many challenges remain. For instance, humans remain multilingual. Humans continue to transact business in many currencies with many valuations.



A QUEST FOR DATA UNIFORMITY

In computer parlance, one way in which this trend towards human uniformity manifests itself is through the use of standards. One of the hottest topics in the computer industry these days is referred to as data standardization. There is a movement to standardize all data on Earth. The goal is make all data easily convertible into useful information in a variety of formats simultaneously. The linchpin of this data standardization trend is known as SGML. Perhaps the most popular or recognizable offshoot of SGML is HTML. HTML is the principal language used to present websites over the World Wide Web (WWW).

After HTML, the next leap forward in data standardardization appears to be XML. Related to XML, and partly based on XML, another popular data standardization technology to emerge since the advent of HTML is known as RDF.

Through the use of data standards such as XML and RDF, the idea is to take one data source and make it consumable through multiple platforms and channels at once (that is, the one-to-many technique). To illustrate, take the publishing industry, for instance. The text of a book could be transmitted to publishers in the form of an XML file. Various publisers, in turn, would take that XML file and publish it in various native formats. For instance, one type of publisher would take that XML file and use it to publish a book in the paperback format. Another type of publisher would take that same xml file and use it publish a book in the eBook format to be used, say, on smartphones or eBook readers. The next publisher would take that same xml file and use it to publish a book in the audiobook format. Other types of publishers would take that same xml file and use it to publish a book, say, in the flipbook format or the XHTML (website) format. In much the same sense as money is the chief medium of exchange between the buyer and seller of a product, the idea behind XML is to make it the chief medium of exchange between producers and consumers of data. XML is a standard or uniform way for businesses, governments, organizations, and households to easily and quickly exchange information in a variety of ways.

Not only does XML excel at taking one data source and making it consumable through multiple platforms and channels at once but also XML excels at receiving data from disparate data sources and integrating these disparate sources of data into a single unified framework (that is, the many-to-one technique). An example of the many-to-one technique would be a travel website that receives data feeds (for example, hotel pricing and room availabilty data) from multiple sources and then integrates those different data feeds into a single database to offer users one-stop shopping comparisons (say, for hotel reservations). XML also excels as a many-to-many data dissemination technology.

The following videos and links provide some introductory insights into the emergence of HTML and XML:

XML Tutorial Introduction

XML Tutorial SGML, HTML and XML

XML Tutorial What You Need to Know About XML



Watch (An Introduction to XML: The Basics Part 1)






Watch (An Introduction to XML: XML and Web 2.0 Part 2)






Watch (An Introduction to XML Managing XML Data Part 3)




The following video and link provide addtional insights into RDF technology:

An Update on RDF Concepts and Some Ontologies



Watch (RDFa Basics)




It should be noted that the quest for data standardization is not without its share of growing pains. For instance, XML is not a standalone or all-in-one technology. XML is a series of technologies. In order for it to work efficiently and realize its full potential, XML must be augmented by ancillary technologies such as DTD, XSD, XSL, XQuery, XPath, XLink, XPointer, and so forth. Complete mastery of XML not only requires mastery of these ancillary technologies but also requires a minimum proficiency in at least one programming language such as Java or JavaScript. On the Water for All page of this website, I mentioned that the job market looks bright for those who choose to study some facet of making clean water available to all humans on Earth. Equally, the job market looks bright for those who choose to study XML and its ancillary technologies.



A QUEST FOR LINKED DATA

Web 1.0 was the original World Wide Web in all of its glory. Some view cloud computing as perhaps one of the most popular manifestations of Web 2.0. Some refer to the quest for linked data as the advent of Web 3.0. However, the quest for widespread linked data is more commonly referred to as the semantic web. Linked data derives its functionality from RDF and related technologies.

The following videos provide additional insights into the emerging semantic web:

Watch (Tim Berners-Lee: The Next Web of Open, Linked Data)






Watch (Intro to the Semantic Web)






Watch (The Semantic Web - An Overview)






Watch (What is Linked Data?)




The following links demonstrate some of the emerging ways to search the infantile semantic web:

Semantic Search:

Falcons |  Freebase |  OpenLink Virtuoso |  RKBExplorer |  sameAs |  Sindice |  Swoogle |  Watson



OPEN EARTH

Related to the quest for data standardization and linked data is another new trend in the computer industry. This additional trend is known as open data. The concept of open data is not new. Within the computer industry, the concept of open data can be traced to the advent of the World Wide Web. To repeat the snyposis provided on the Back Book Cover page of this website, following is a list of some milestone Internet-related dates in the computer industry.

The following videos offer insights into the emergence of the open data phenomenon:

Watch (#opendata from the Open Knowledge Foundation)





Watch [Linked Data (and the Web of Data)]






Watch (Web 3.0, by Kate Ray, NYU Journalism Graduate)



As of 2012, new technologies have emerged to support and boost the concept of open data. The idea of open data is not to propel humanity into a state of information overload. Instead, the idea of open data is to broaden human knowledge. The idea of open data is to make useful information available to all humans. The benefit of open data lies with its potential for improving the quality of life on Earth. The impact of open data potentially would be felt from the neighborhood level all the way up the chain to the global level.

The following links offer additional insights into and examples of open data in action:

visualizing.org | Data Visualizations, Challenges, Community

Open Data

Open Data Sites | Data.gov

Open Data Handbook

Welcome - the Data Hub

CKAN - The Open Source Data Portal Software

An excellent example of the potential for open data to enhance the quality of life of citizens can be found at the following link:

SeeClickFix

The chief motivating force behind the birth of SeeClickFix's website was to enable citizens to quickly document and report non-emergency quality-of-life types of issues to local government officials. These non-emergency issues included things such as graffiti, potholes in streets, inoperable vehicles abandoned on streets, inoperable traffic signal lights, inoperable street lamps, garbage and trash dumped in vacant lots, and so forth.

In the case of SeeClickFix, admittedly, local governments do not always have the resources to address all of these fix-it requests in a timely manner. Webites such as SeeClickFix, however, appear to be a good start in the right direction. It should be noted, moreover, that sometimes getting quality-of-life problems fixed is simply a matter of sending the appropriate officials a text message, email, or even placing a phone call:

U.S. Government Telephone and E-mail Directories | USA.gov

State Government | USA.gov

American Hometowns | Cities, Counties, and Towns | USA.gov

The U.S. Conference of Mayors: Meet the Mayors

US Government Directory | Federal, State & Local Government | GovEngine.com



TOWARDS A SMARTER PLANET EARTH

What is the point of this discussion about data standardization, linked data, open data, and the emerging semantic web? The point in presenting this sometimes abstract and technical information is to inform. The point is to show you the existence of a trend, path, or pattern. The pattern is this: Despite a diverse human species, the emergence of the semantic web signifies that humans increasingly are becoming as one. Humans are finding new ways to make connections, to share the world's knowledge, to solve problems, to improve the human condition, and to achieve a higher quality of life on Earth for all. The ultimate goal of this data openess is for the species Homo sapiens sapiens (human beings) to become wiser, survive, prosper, and thrive.

Watch (Imagine the Possibilities)




Watch (Making the Smarter Planet a Reality for Midsize Businesses)




Watch (GE Jumping Into Industrial Internet)




Watch (Intel | Future Technology | Vision)




Watch (Living Tomorrow: House of the Future)






TROUBLE IN PARADISE

Obviously, given the benefits of open data and the semantic web, there is a dark side that lurks just beneath the surface. Some possible adverse aspects of open data and the semantic web include the following:

Already a similar problem exists on the current World Wide Web. Unlike the good old days of, say, vinyl records, 8-track tapes, cassette tapes, and compact discs where you went to the music store and purchased these items, with the advent of digital content, not many people seem to be willing to compensate the creators and owners of digital content. Many humans seem to want to receive their digital content for free. This no-pay attitude by some appears to have become contagious and seems to apply to all kinds of digital products such as songs, motion pictures, software applications, eBooks, and so forth. Granted there is a lot of legitimate digital content available on the World Wide Web for free, but vast numbers of these digital products are not being offered for free and are for sale. There are many stakeholders whose livelihoods depend on these digital products making a profit. There are many businesses that depend on these digital products making a profit in order to stay in business. Far too many humans seem to be engaged in the practice of obtaining one copy of the digital product, making multiple unauthorized copies of the product, and then giving the copies to friends and acquaintances or selling the pirated or bootlegged copies to others at a steep discount. The rightful owners of these digital products do not get compensated whenever and wherever piracy occurs. The rightful owners of these digital products are deprived of a livelihood in the process. In other words, the digital age has turned many otherwise honest citizens into thieves. Most citizens would not imagine themselves walking into a clothing store and stealing articles of clothing off the shelves and racks. Yet, many of these same citizens think very little of obtaining an unauthorized or bootlegged copy of digital content, say, an eBook, mp3 song, software application, or mpg motion picture.

The following PaySwarm video offers another perspective on the problem of digital piracy. One shortcoming of the PaySwarm commercial strategy is this: Most owners of digital content do not generate lots of visitors on the World Wide Web. Most owners of digital content would be fortunate to receive 1,000 visits to their websites each year let alone 100,000 or 1,000,000 visits. Based on the assumption that the visitor would be willing to pay one cent per visit to the website to peruse, try, or purchase the digital content being offered for sale, then 1,000 visits would equate to $10 per year; 100,000 visits would equate to $1,000 per year; and 1,000,000 visits would equate to $10,000 per year in revenue for the owner of the digital content. Despite this perceived shortcoming, the PaySwarm business model represents a good start in the right direction. Of course, web-based business strategies such as PaySwarm would be one of several avenues for owners of digital content to make money from their content. The World Wide Web is but one channel for owners of digital content to make money. Other channels or commercial venues do exist.

Watch (Universal Payment for the Web)


Another interesting and novel approach is called Flattr. Much like the PaySwarm paradigm, the Flattr website allows supporters and creators of digital content, respectively, to make microdonations to and receive micropayments from the other. This website subscribes to Flattr. The catch is that you have to take the time to establish and fund a Flattr account for it to work as intended.

Watch (This is Flattr)


The approaches of World Wide Web giants such as YouTube, Vevo, and Myspace also are commendable. In an effort to help compensate owners of digital content, web giants such as YouTube, Vevo, and Myspace conveniently place a buy-it-now link or button next to the featured music video or song.

Related to the problem of digital piracy, in their study of human behavior and without reference to divine intervention, psychologists such as Sigmund Freud, B. F. Skinner, Albert Bandura, Gordon Allport, and Abraham Maslow have struggled with and sought to answer the question of why do humans behave the way that they do. Why do humans do certain things in the first place? For instance, they wanted to know the answers to questions such as the following ones:

In his hierarchy-of-needs model of human behavior, Abraham Maslow posited that, if the basic necessities of survival are not being met by a society (that is, the human need for food, clothing, and shelter), then members of that society might be tempted to engage in dishonest, immoral, and unethical practices in their quest to obtain the basic necessities of food, clothing, and shelter simply to stay alive and survive (that is, when opportunities and options for survival are few or scarce in a society). Based on the hierarchy-of-needs model of human behavior, it can be surmised that when the basic necessities of survival, in fact, are being met in a society, then it becomes a matter of free will whether humans choose to engage in dishonest, immoral, and unethical practices. When the basic necessities of survival are being met, then things such as greed, money, power, jealousy, envy, prestige, and lack of education most likely are the predominant forces driving human behavior and compelling some humans to engage in dishonest, immoral, and unethical practices. What is the moral here? If Abraham Maslow is to be believed, then the moral of this story seems to be this: Without recourse to prejudice, civil society diligently ought to try to find ways to offer all of its members meaniful opportunities for survival and prosperity in life. Meaniful opportunities for survival likely would dissuade or discourage citizens from choosing to travel down the dishonest, immoral, and unethical path in life. Perhaps the most critical opportunity that a society could confer upon its citizenry is the opportunity for all members to obtain a good education beginning in early childhood. For, as I mention on the Education for All page of this website, education plays two crucial roles in the human life cycle:

  1. Education provides students with the knowledge and skills that they require to become productive and self-supporting members of society regardless of the career niche they choose, that is, whether an academic, athletic, artistic, vocational, blue collar, or white collar niche.
  2. Education teaches students how to be responsible and law-abiding members of civil society. Responsible conduct entails leading principled and disciplined lives. It also entails showing the utmost respect for self, respect for others, respect for the property of others, respect for the rule of law, and respect for the sanctity of human life regardless of race, color, creed, ethnicity, gender, sexual orientation, religious belief, disability, national origin, socioeconomic birth status, political ideology, and so forth.
Click Here to View Another Perspective on Digital Piracy





Additional Links for Open Earth:
  1. XMLGenie! XML to HTML Conversion without Programming
  2. Firebug Lite: Firebug
  3. XPontus - Homepage
  4. Peter's XML Editor
  5. XMLQuire
  6. Firstobject's Free XML Editor for Windows
  7. XMLFox XSD Editor
  8. Exchanger XML Editor - XML Editor and XSLT Debugger
  9. XMLwriter XML Editor
  10. Text Editor | Hex Editor | UltraEdit
  11. EditiX XML Editor
  12. Butterfly XML Editor
  13. Rinzo XML Editor - Eclipse XML Editor
  14. XML Pro | Vervet Logic
  15. Liquid Technologies's XML Editor, Code Generator and Toolkit
  16. XMLBlueprint - XML Editor
  17. Altova XMLSpy
  18. XML Editor, XML Tools, and XQuery - Stylus Studio
  19. XMLmind
  20. oXygen XML Editor
  21. XMetaL Home Page
  22. XML editor - EduTech Wiki
  23. MSXML
  24. O'Reilly - www.XML.com: RUWF? The XML Syntax Checker
  25. XML Schema Checking Service
  26. W3C RDF Validation Service
  27. Vapour, a Linked Data validator
  28. Google Structured Data Testing Tool
  29. Friend of a Friend (FOAF)
  30. Free XML Tools and Software
  31. XML Tutorial (75 Videos)
  32. RssReader's Free RSS Reader Displays Any RSS and Atom News Feed
  33. RSS Builder
  34. ListGarden's RSS Feed Generator
  35. Feed Validator for Atom and RSS
  36. RSSPECT - Automatic and Free RSS Feeds for Everyone
  37. Industrial Internet: Pushing the Boundaries of Minds and Machines


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Intellectual Property Disclosures: All videos and songs (as well as many of the images) referenced or spotlighted throughout this website are the legal and intellectual properties of others. All content and opinions on this website (bruessard.com) are those of the author (Edward Bruessard) exclusively and do not necessarily reflect the opinions of the contributors, creators, owners, and distributors of these referenced videos, songs, and images. The author holds no legal interest or financial stake in any of these referenced videos, songs, and images. The contributors, creators, owners, and distributors of these referenced videos, songs, and images played no role at all regarding the appearance of said videos, songs, and images throughout this website; they had no clue that this website would be spotlighting their works..


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