The presented at FOSS4G SEOUL 2015. Create a infographic maps and can be shared on the web, we will introduce the Pinogio. Just a few clicks complex analysis function through Pinogio, it is possible to make a web map of high quality. Pinogio consists of a Geotools, GeoServer, OL3, including open source-based architecture. Do not store anymore geospatial data in local storage, create a beautiful maps from public cloud environment.

1. A Simple Way to Create a Web
Infographic Map:
For Public Data and Private Data
MangoSystem
Research Engineer | Hanjin Lee
@jinifor

3. Who

4. Are

5. We?!

9. How

10. to

11. Get

12. the

14.
Public

15. (Open)

16. Data?

17. 8
NS

18. Center

19. (National

20. Spatial

21. Information

22. Clearinghouse) https://nsic.go.kr

23. 9
Open

24. Data

25. Portal http://data.go.kr

26. 10
Seoul

27. Open

28. Data

29. Plaza http://data.seoul.go.kr

30. 11
Seoul

31. Open

32. Data

33. Plaza http://data.seoul.go.kr
Lat

39. |

45. Lon

46. United

47. States

48. of

49. America

50.
(http://www.data.gov/)
Australia

51.
(http://data.gov.au/)
United

52. Kingdom

53.
(http://data.gov.uk/)
Japan

54.
(http://data.go.jp/)

55. PINOGIO

56. Features?

57. 14
Open

58. Source

59. Stack
• PostgreSQL

60. /

61. PostGIS

62.
• GXT

63. Server

64. (GeoServer

65. WPS

66. Extension)

67.
• OpenLayers3

68. /

69. Leaflet

70. #GXT

71. 16
GXT

72. (Geoprocessing

73. Engine)
GXT

74.
Core
Grid

75. Coverage Custom
Vector

76. Features Spatial

77. Statistics
Geometry Statistics
GeoTools GeoAPI JTS JAI

78. 17
GXT

79. (Geoprocessing

80. Engine)
Category Function
GXT

81.
Modules
Geometry • Area,

82. Buffer,

83. Centroid,

84. Distance,

85. ManhattanDistance,

86. Union
Vector • Overlay,

87. Proximity,

88. Calculation,

89. Network
Raster
• Surface,

90. Interpolation,

91. Density,

92. Distance,

93. Reclassification,

94.
Conversion
Statistics • Classification,

95. Basic

96. Statistics,

97. Pearson,

98. Regression
Spatial

99.
Statistics
• Pattern(Moran’s

100. I,

101. G-Statistics,

102. Spatial

103. LQ,

104. Nearest

105. Neighbor)

106.
• Distribution(Mean

107. Center,

108. Central

109. Feature,

110. Standard

111.
Distance,

112. SDE)

113.
• Cluster(k-means)
Custom
• Extension

114. Data

115. Store

116.
• Web

117. KOPSS

118. algorithm

119. Support
GXT

120. Online

121. Documentation

122.
(http://gxt.mangosystem.com/)

123. 18
GXT

124. (Geoprocessing

125. Engine)
Category Function
GXT

126.
Modules
Geometry • Area,

127. Buffer,

128. Centroid,

129. Distance,

130. ManhattanDistance,

131. Union
Vector • Overlay,

132. Proximity,

133. Calculation,

134. Network
Raster
• Surface,

135. Interpolation,

136. Density,

137. Distance,

138. Reclassification,

139.
Conversion
Statistics • Classification,

140. Basic

141. Statistics,

142. Pearson,

143. Regression
Spatial

144.
Statistics
• Pattern(Moran’s

145. I,

146. G-Statistics,

147. Spatial

148. LQ,

149. Nearest

150. Neighbor)

151.
• Distribution(Mean

152. Center,

153. Central

154. Feature,

155. Standard

156.
Distance,

157. SDE)

158.
• Cluster(k-means)
Custom
• Extension

159. Data

160. Store

161.
• Web

162. KOPSS

163. algorithm

164. Support
GXT

165. Online

166. Documentation

167.
(http://gxt.mangosystem.com/)
'GXT

168. uDig

169. ToolBox'

170.
Free

171. for

172. Research

173. and

174. Education!!

175.
uDig

176. Plugin

177. Update

178. URL:

180.
http://www.mangosystem.com:8080/gxt_updates

182. Service

183. Category
19
MAPS

184.
LAYER

185.
DATA
JSON,

186. XML
JSP

187. /

188. Ajax
REST

189.
API

190. Service

191. Category
20
Zone

192.
Layer
Base

193.
Map
MAPS

194.
LAYER

195.
DATA

196. Mango

197. BaseMap
21
Mango

198. BaseMap

199.
(TMS)
Zone

200.
Layer
Base

201.
Map
MAPS

202.
LAYER

203.
DATA
Physical,

204. Gray,

205. Black…⋯

206. Zone(District)

207. Layer
22
Zone

208.
Layer
Base

209.
Map
MAPS

210.
LAYER

211.
DATA

212. Zone(District)

213. Layer
23
Zone

214.
Layer
Base

215.
Map
MAPS

216.
LAYER

217.
DATA
National

218. point

219. number
• 100km

220.
• 10km

221.
• 1km

222.
• 100m

223.
• 10m

224. 0
#DATA
1

225. • Support

226. Formats

227.
• Vector

228. Formats

229.
• Raster

230. Formats

231.
• Transform

232. support
#DATA
25
MAPS

233.
LAYER

234.
DATA

235. The

236. First

237. World

238. Map

239. of

240. Korea

241. +

242.
#LAYER

243. #LAYER
27
MAPS

244.
LAYER

245.
DATA

246. 28
Spatial

247. Statistics
=+
Population

248. Cartogram

250.
Sejong

251. Metropolitan

252. Autonomous

253. City,

254. South

255. Korea

256.
(http://www.sejong.go.kr/stat.do)

257. 29
Fishnet

258. /

259. Hexagon
Australian

260. Land

261. Tenure

262. 1993

263.
(source

264. :

265. http://data.gov.au/dataset)
Fishnet

266. Features
Hexagon

267. Features

268. 30
Map

269. Styling

270. Library

271. 31
COLOR

272. BREWER

273. 2.0 http://colorbrewer2.org

274. 32
pinoStyler.js
Spectrum

276.
Colorpicker
+
Color

277. Brewer

278. 2.0
+
++

279. 33
pinoStyler.js
UN-GGIM-AP

280. VGI

281. Portal

282.
product

283. by

284. National

285. Geographic

286. Information

287. Institute

288.
(http://www.ngii.go.kr)

292. Cloudy

293. day
Sunny

294. day
Rainy

295. day

296. S

297.
t

298.
a

299.
c

300.
k

302.
o

303.
f

304.
H

305.
a

306.
n

307.
d

308.
s
#MAPS

309. 39
MAPS

310. Template
…⋯…⋯

311. PreviewSettings

312. 41
MAPS

313. Contents

316. @jinifor
Thanks!
hjlee mangosystem.com