Difference between revisions of "SOCR Cartography Project"
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==[[Available_SOCR_Development_Projects | SOCR Project]] - Development of the [[SOCR]] Cartography Applet/Interface== | ==[[Available_SOCR_Development_Projects | SOCR Project]] - Development of the [[SOCR]] Cartography Applet/Interface== | ||
| − | ===Project | + | ===Project goals=== |
[[Image:SOCR_CartographyChartIcon_USA.png|150px|thumbnail|right| SOCR Cartographic Charts]] | [[Image:SOCR_CartographyChartIcon_USA.png|150px|thumbnail|right| SOCR Cartographic Charts]] | ||
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Many of the [[SOCR_EduMaterials_ChartsActivities | SOCR Charts]] provide advanced tools for computational and graphical exploratory data analysis. Typical geo-political maps represent the world in a flat 2D Euclidean space where the North Pole looks huge and the equator appears small (Gastner and Newman, 2004). Data obtained for different geographic, political or regional locales may be used to morph the standard world atlases into cartographic maps that represent the areas, colors or glyphs of different regions according to the (multi-modality) data. Such maps are called '''data-driven-cartographic maps'''. | Many of the [[SOCR_EduMaterials_ChartsActivities | SOCR Charts]] provide advanced tools for computational and graphical exploratory data analysis. Typical geo-political maps represent the world in a flat 2D Euclidean space where the North Pole looks huge and the equator appears small (Gastner and Newman, 2004). Data obtained for different geographic, political or regional locales may be used to morph the standard world atlases into cartographic maps that represent the areas, colors or glyphs of different regions according to the (multi-modality) data. Such maps are called '''data-driven-cartographic maps'''. | ||
| − | ==Project | + | ==Project specifications== |
* Review the references below. | * Review the references below. | ||
* Develop the computational model for handling multi-modal data (e.g., [http://en.wikipedia.org/wiki/GDP GDP], [http://en.wikipedia.org/wiki/Population_size population size], [http://en.wikipedia.org/wiki/Income average income], [[SOCR_Data_Dinov_021808_ConsumerPriceIndex3Way | CPI]], etc.) The user should be able to map these data to specific cartographic features (e.g., region area, size, color, glyphs, etc.) | * Develop the computational model for handling multi-modal data (e.g., [http://en.wikipedia.org/wiki/GDP GDP], [http://en.wikipedia.org/wiki/Population_size population size], [http://en.wikipedia.org/wiki/Income average income], [[SOCR_Data_Dinov_021808_ConsumerPriceIndex3Way | CPI]], etc.) The user should be able to map these data to specific cartographic features (e.g., region area, size, color, glyphs, etc.) | ||
* Plan the extension of [[SOCR_EduMaterials_ChartsActivities | SOCR Charts]] and [[SOCR_MotionCharts | SOCR Motion Charts]] to design and implement this new infrastructure. | * Plan the extension of [[SOCR_EduMaterials_ChartsActivities | SOCR Charts]] and [[SOCR_MotionCharts | SOCR Motion Charts]] to design and implement this new infrastructure. | ||
* Test and validate the new '''SOCR Cartographic Charts''' with real data and deploy to [[SOCR]] production server. | * Test and validate the new '''SOCR Cartographic Charts''' with real data and deploy to [[SOCR]] production server. | ||
| + | |||
| + | ==Variable ''mapping''== | ||
| + | There should be several user-specifiable protocols for mapping multivariate data! We can use a drop-down list to select a predefined variable-mapping protocol, and these may allow plug-ins. One approach would be to allow multivariate data to be mapped into different map-sector (region) appearance characteristics – for instance you can use a mapping like this: | ||
| + | * variable1 = affects region warping (expansion or shrinkage) | ||
| + | * variable2 = affects region color | ||
| + | * variable3 = affects region shading | ||
| + | * variable4 = affects region pattern | ||
| + | * variable5 = affects region border-patters (thickness, color, appearance or line-style) | ||
| + | * etc. | ||
== See also== | == See also== | ||
Revision as of 13:24, 29 December 2009
Contents
SOCR Project - Development of the SOCR Cartography Applet/Interface
Project goals
To develop an agile and functional Java interface and an applet that integrates available SOCR resources (e.g., SOCR Charts) and provide the means to enter geo-political data and construct proportional cartography maps. In these maps, the sizes of different geographic regions, such as countries, provinces, continents, etc., appear proportional to the data provided by the user. The new SOCR Cartographic Charts will use the fundamental SOCR development principals and be accessible via the SOCR web-server. The image to the right illustrates an example of a cartographic map of the USA, where states are drawn approximately proportional to the square footage per capita.
Background
Many of the SOCR Charts provide advanced tools for computational and graphical exploratory data analysis. Typical geo-political maps represent the world in a flat 2D Euclidean space where the North Pole looks huge and the equator appears small (Gastner and Newman, 2004). Data obtained for different geographic, political or regional locales may be used to morph the standard world atlases into cartographic maps that represent the areas, colors or glyphs of different regions according to the (multi-modality) data. Such maps are called data-driven-cartographic maps.
Project specifications
- Review the references below.
- Develop the computational model for handling multi-modal data (e.g., GDP, population size, average income, CPI, etc.) The user should be able to map these data to specific cartographic features (e.g., region area, size, color, glyphs, etc.)
- Plan the extension of SOCR Charts and SOCR Motion Charts to design and implement this new infrastructure.
- Test and validate the new SOCR Cartographic Charts with real data and deploy to SOCR production server.
Variable mapping
There should be several user-specifiable protocols for mapping multivariate data! We can use a drop-down list to select a predefined variable-mapping protocol, and these may allow plug-ins. One approach would be to allow multivariate data to be mapped into different map-sector (region) appearance characteristics – for instance you can use a mapping like this:
- variable1 = affects region warping (expansion or shrinkage)
- variable2 = affects region color
- variable3 = affects region shading
- variable4 = affects region pattern
- variable5 = affects region border-patters (thickness, color, appearance or line-style)
- etc.
See also
- OpenMap
- ALOV
- BATIK
- Deegree
- GeoTools
- Advanced Normalization Tools (ANTs) can be used for the warping of one SVG/GIS map to fit in the user-specified sizes of each region.
- Constructing GIS Maps in Splus/R Manual (see page 10+)
References
- Example of a cartographic Applet.
- M. Gastner and M. Newman (2004). Diffusion-based method for producing density-equalizing maps. PNAS 2004 101:7499-7504; published online May 10, 2004, doi:10.1073/pnas.0400280101.
- Examples of data visualization.
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