Difference between revisions of "SOCR Cartography Project"
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− | ==[[SOCR]] | + | ==[[Available_SOCR_Development_Projects | SOCR Project]] - Development of the [[SOCR]] Cartography Applet/Interface== |
− | ===Project | + | ===Project goals=== |
− | [[Image: | + | [[Image:SOCR_Cartography_Fig2aaa.png|150px|thumbnail|right| SOCR Cartographic Charts]] |
To develop an agile and functional Java interface and an applet that integrates available [[SOCR]] resources (e.g., [[SOCR_EduMaterials_ChartsActivities | 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 [http://en.wikipedia.org/wiki/USA USA], where states are drawn approximately proportional to the square footage per capita. | To develop an agile and functional Java interface and an applet that integrates available [[SOCR]] resources (e.g., [[SOCR_EduMaterials_ChartsActivities | 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 [http://en.wikipedia.org/wiki/USA USA], where states are drawn approximately proportional to the square footage per capita. | ||
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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. | ||
+ | |||
+ | ==Use-cases== | ||
+ | * The first use-case is the user loads the geometry and the metadata files. The applet allows the user to specify a mapping between the variables (meta-data) and the Blob-locations (X,Y), the Blob-size, and the Blob-color, and then renders the blobs (discs with appropriate appearance) for each shape (simple closed curve) on the GIS map. | ||
+ | |||
+ | * The second use-case is the user again loads the geometry and the metadata files. The applet allows the user to specify a mapping between 1 variable in the meta-data, and a pair of 2D coordinates, (X,Y) locations, which are typically indicative of a longitude and latitude and should be inside or outside of each shape in the geometry file. Then the user wants to morph/transform the GIS map according to the variable values so that the areas of all regions in the GIS shape to be scaled proportionally to the variable of interest. Later we may include colors mapped to second variable. | ||
+ | |||
+ | ==SOCR Cartography Applet== | ||
+ | * [[Help_pages_for_SOCR_Cartography| SOCR Cartography Help page]] | ||
+ | * [http://socr.ucla.edu/htmls/SOCR_Cartograhy.html SOCR Cartography Java Applet] | ||
+ | |||
+ | == See also== | ||
+ | * [https://github.com/cambecc/earth Earth Wind and Ocean currents Map] | ||
+ | * [hint.fm/wind/ Interactive Windmap] | ||
+ | * [http://hosted.ap.org/specials/interactives/_national/stress_index/ Interactive Economic Stress Index Map] | ||
+ | * [http://rosuda.org/mondrian/ Mondrian Java-based GIS data-visualization system] | ||
+ | * [http://openmap.bbn.com/ OpenMap] | ||
+ | * [http://alov.org/ ALOV] | ||
+ | * [http://xml.apache.org/batik/ BATIK] | ||
+ | * [http://deegree.sourceforge.net/ Deegree] | ||
+ | * [http://www.geotools.org/ GeoTools] | ||
+ | * [http://sourceforge.net/projects/advants/ 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. | ||
+ | * [http://wiki.stat.ucla.edu/socr/uploads/b/b8/Cartography_Constructing_GIS_Maps_ATT.pdf Constructing GIS Maps in Splus/R Manual (see page 10+)] | ||
+ | * [http://scapetoad.choros.ch ScapeToad] | ||
+ | |||
+ | ==Data== | ||
+ | The applets should allow the user to specify 2 types of data: | ||
+ | : ''Geometry data'' - containing the shapes of the geography/GIS maps. These data are typically presented in [http://en.wikipedia.org/wiki/Shapefile Shape (*.shp) binary file format], see examples below. | ||
+ | : ''Meta-data'' - the auxiliary quantitative data in either [http://en.wikipedia.org/wiki/Shapefile#Shapefile_attribute_format_.28.dbf.29 DBF attribute file format], or in text/ASCII file format: | ||
+ | <center> | ||
+ | {| class="wikitable" | ||
+ | |- | ||
+ | ! Longitude(X)|| Latitude(Y) || Variable1 || ... || Variable_N | ||
+ | |- | ||
+ | | -120.23 || 32.45 || 11.23 || ... || 17 | ||
+ | |- | ||
+ | | ... || ... || ... || ... || ... | ||
+ | |- | ||
+ | | -121.23 || 31.45 || 17.31 || ... || 10 | ||
+ | |} | ||
+ | </center> | ||
+ | |||
+ | ===Examples of data=== | ||
+ | * [http://www.census.gov/geo/www/cob/bdy_files.html 2000 US Census data] and [http://www.census.gov/geo/www/cob/co2000.html#shp California Counties Shape Data] | ||
==References== | ==References== | ||
* [http://www-personal.umich.edu/~mejn/ Example of a cartographic Applet]. | * [http://www-personal.umich.edu/~mejn/ Example of a cartographic Applet]. | ||
* M. Gastner and [http://www-personal.umich.edu/~mejn/ M. Newman] (2004). [http://www.pnas.org/content/101/20/7499 Diffusion-based method for producing density-equalizing maps]. PNAS 2004 101:7499-7504; published online May 10, 2004, doi:10.1073/pnas.0400280101. | * M. Gastner and [http://www-personal.umich.edu/~mejn/ M. Newman] (2004). [http://www.pnas.org/content/101/20/7499 Diffusion-based method for producing density-equalizing maps]. PNAS 2004 101:7499-7504; published online May 10, 2004, doi:10.1073/pnas.0400280101. | ||
+ | * [http://www.webdesignerdepot.com/2009/06/50-great-examples-of-data-visualization/ Examples of data visualization]. | ||
<hr> | <hr> | ||
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*[[SOCR_ProposalSubmissionGuidelines]] | *[[SOCR_ProposalSubmissionGuidelines]] | ||
− | {{translate|pageName=http://wiki. | + | "{{translate|pageName=http://wiki.socr.umich.edu/index.php?title=SOCR_Cartography_Project}} |
Latest revision as of 15:23, 3 March 2020
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.
Use-cases
- The first use-case is the user loads the geometry and the metadata files. The applet allows the user to specify a mapping between the variables (meta-data) and the Blob-locations (X,Y), the Blob-size, and the Blob-color, and then renders the blobs (discs with appropriate appearance) for each shape (simple closed curve) on the GIS map.
- The second use-case is the user again loads the geometry and the metadata files. The applet allows the user to specify a mapping between 1 variable in the meta-data, and a pair of 2D coordinates, (X,Y) locations, which are typically indicative of a longitude and latitude and should be inside or outside of each shape in the geometry file. Then the user wants to morph/transform the GIS map according to the variable values so that the areas of all regions in the GIS shape to be scaled proportionally to the variable of interest. Later we may include colors mapped to second variable.
SOCR Cartography Applet
See also
- Earth Wind and Ocean currents Map
- [hint.fm/wind/ Interactive Windmap]
- Interactive Economic Stress Index Map
- Mondrian Java-based GIS data-visualization system
- 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+)
- ScapeToad
Data
The applets should allow the user to specify 2 types of data:
- Geometry data - containing the shapes of the geography/GIS maps. These data are typically presented in Shape (*.shp) binary file format, see examples below.
- Meta-data - the auxiliary quantitative data in either DBF attribute file format, or in text/ASCII file format:
Longitude(X) | Latitude(Y) | Variable1 | ... | Variable_N |
---|---|---|---|---|
-120.23 | 32.45 | 11.23 | ... | 17 |
... | ... | ... | ... | ... |
-121.23 | 31.45 | 17.31 | ... | 10 |
Examples of data
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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