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Python Geospatial Development - Second Edition by Erik Westra

capital controls, database schema, Firefox, Golden Gate Park, Google Earth, Mercator projection, natural language processing, openstreetmap, Silicon Valley, web application

Index A AddGeometryColumn() function / Using SpatiaLite AddPoint() / Task – save the country bounding boxes into a shapefile add_dash() method / Dashed and dotted lines admin interface, Django applicationabout / The structure of a Django application admin system, Django applicationabout / Playing with the admin system adding / Playing with the admin system database, resynchronizing / Playing with the admin system database objects, adding / Playing with the admin system admin URLs, adding / Playing with the admin system working with / Playing with the admin system affine transformation, DEMabout / Task – analyze height data using a digital elevation map also rules / "Also" rules angular distanceabout / Distance / Using angular distances angular distances / Task – identify parks in or near urban areas Application Programming Interfaces (APIs)about / Recent developments application reviewabout / Application review and improvements usablity / Usability quality / Quality performance / Performance problem, searching / Finding the problem performance, improving / Improving performance tiled shorelines, calculating / Calculating the tiled shorelines tiled shorelines, using / Using tiled shorelines performance improvement, analyzing / Analyzing the performance improvement aspect ratio / Calculating the map's dimensions AsText() function / Using SpatiaLite attributesabout / Geospatial development authentication system, Django applicationabout / The structure of a Django application azimuthal projectionabout / Azimuthal projections B band.ReadRaster() method / Task – analyze height data using a digital elevation map Band Interleaved by Line (BIL) formatabout / GIS data formats Band Interleaved by Pixel (BIP) formatabout / GIS data formats Band Sequential (BSQ) formatabout / GIS data formats base layerabout / Tile rendering base mapsetting up / Setting up the base map best practices, geospatial databasesabout / Recommended best practices spatial references, monitoring / Using the database to keep track of spatial references appropriate spatial reference, using / Using the appropriate spatial reference for your data databases, using supporting geographies / Option 1 – using a database that supports geographies features, transforming / Option 2 – transforming features as required features, transforming outset / Option 3 – transforming features from the outset unprojected coordinates, using / When to use unprojected coordinates on-the-fly transformations, avoiding within query / Avoiding on-the-fly transformations within a query spatial indexes, using / Using spatial indexes appropriately limits, spatial query optimizer / Knowing the limits of your database's query optimizer Bingabout / Creating a geospatial mash-up bounding / The OpenStreetMap API C calc_search_radius() function / Implementing the find feature view changesets / The OpenStreetMap API civic locationabout / Location colorsusing / Using colors common spatially-enabled databasesabout / Commercial Spatially-enabled databases Oracle / Oracle MS SQL Server / MS SQL Server conditions, rules / Rules, filters, and styles conic projectionabout / Conic projections coordinatesabout / Geospatial development coordinate systemabout / Coordinate systems projected coordinate systems / Coordinate systems unprojected coordinate systems / Coordinate systems coordinate transformation / Task – change projections to combine shapefiles using geographic and UTM coordinates Core Based Statistical Areas (CBSAs) / Task – identify parks in or near urban areas country bounding boxes, geospatial datacalculating / Task – calculate the bounding box for each country in the world saving, into shapefile / Task – save the country bounding boxes into a shapefile coverage formatabout / GIS data formats CreateSpatialIndex() function / Using SpatiaLite crosses() method / Design cursor.execute() methodabout / MySQL cylindrical projectionsabout / Cylindrical projections D dash segments / Dashed and dotted lines datadownloading / Downloading the data World Borders Dataset / World Borders Dataset, World Borders Dataset GSHHS / GSHHS, GSHHS GNIS / GNIS GEOnet Names Server / GEOnet Names Server importing / Importing the data places’ name data / US place name data worldwide places’ name data / Worldwide place name data data modelsdefining / Defining the data models shapefile, importing / Shapefile attribute / Attribute feature / Feature AttributeValue object / AttributeValue models.py file / The models.py file data sourcesetting up / Setting up the data source Datasource object / Design datasourcesshapefile / Shapefile PostGIS / PostGIS Gdal / Gdal Org / Ogr SQLite / SQLite OSM / OSM MemoryDatasource / MemoryDatasource datumabout / Datums, Changing datums and projections reference points / Datums NAD 27 / Datums NAD 83 / Datums WGS 84 / Datums changing / Task – change datums to allow older and newer TIGER data to be combined decimal degrees / Analyzing geospatial data defaultHandlerOptions dictionary / Intercepting mouse clicks design, MapnikLayers / Design Styles / Design Symbolizers / Design Destroy() method / Task – save the country bounding boxes into a shapefile, Saving the features into the shapefile digital elevation maps (DEM) / Sources of geospatial data in raster formatabout / Task – analyze height data using a digital elevation map used, for analyzing height data / Task – analyze height data using a digital elevation map affine transformation / Task – analyze height data using a digital elevation map Digital Elevation Model (DEM) formatabout / GIS data formats Digital Raster Graphic (DRG) formatabout / GIS data formats DISTALbasic workflow / About DISTAL database, designing / Designing and building the database database, building / Designing and building the database DISTAL applicationimplementing / Implementing the DISTAL application, The "select country" script about / Implementing the DISTAL application shared database module / The shared "database" module select country script / The "select country" script select area script / The "select area" script show result script / The "show results" script DISTAL databasedesigning / Designing and building the database distanceabout / Distance angular distance / Distance linear distance / Distance traveling distance / Distance distance featuresidentifying, manually / Calculating distances manually angular distance, using / Using angular distances projected coordinates, using / Using projected coordinates hybrid approach / A hybrid approach result, displaying / Displaying the results Django administrationworking with / Playing with the admin system Django applicationdownloading / Prerequisites structure / The structure of a Django application authentication system / The structure of a Django application admin interface / The structure of a Django application markup application / The structure of a Django application messages framework / The structure of a Django application sessions system / The structure of a Django application sitemaps framework / The structure of a Django application syndication system / The structure of a Django application settings file / The structure of a Django application model / The structure of a Django application, Models view / The structure of a Django application, Views templates / The structure of a Django application, Templates URL dispatching / URL dispatching data-entry forms / Templates DSG (Feature Designation Code) field / Worldwide place name data E edit_feature() function / Editing features edit_shapefile() function / Intercepting mouse clicks edit_shapeFile() view function / Intercepting mouse clicks else rules / "Else" rules envelope / Task – calculate the bounding box for each country in the world ESRI format / Obtaining and using GLOBE data European Petroleum Survey Group (EPSG) / Using the database to keep track of spatial references EveryBlockURL / Mapnik example map, Mapnikcreating / Creating an example map expandRect() function / Calculating the tiled shorelines export_data() function / Exporting shapefiles, Saving the attributes into the shapefile export_shapefile() view function / Exporting shapefiles F FC (Feature Classification) field / Worldwide place name data Feature Classification (FC) / Obtaining and using GEOnet Names Server data Feature Designation Code (DSG) / Obtaining and using GEOnet Names Server data feature layerabout / Tile rendering featuresediting / Editing features adding / Adding features deleting / Deleting features fields / Task – calculate the bounding box for each country in the world filterabout / Introducing Mapnik Filter() constructor / Filters filters, Mapnikabout / Filters scale denominators / Scale denominators find feature viewimplementing / Implementing the find feature view findPoints() function / Working with GIS data manually find_feature() function / Implementing the find feature view find_feature_url parameter / Intercepting mouse clicks find_places_within() function / A hybrid approach fixtureabout / Setting up the base map form.as_table template function / Editing features formsabout / The "import shapefile" view function FWTools installerURL / Working with GIS data manually G gamma correction / Gamma correction GDALabout / Recent developments / Obtaining and using GLOBE data, Drawing raster images GDAL, for Mac OS X / Working with GIS data manually GDAL/OGRabout / GDAL/OGR documentation / Documentation availability / Availability Gdal data sourceabout / Gdal gdaldem utility / Obtaining and using NED data GDAL designabout / GDAL design dataset / GDAL design raster band / GDAL design raster size / GDAL design georeferencing transform / GDAL design affine transformation / GDAL design Ground Control Points (GCPs) / GDAL design coordinate system / GDAL design metadata / GDAL design band raster size / GDAL design band metadata / GDAL design color table / GDAL design raster data / GDAL design drivers / GDAL design GDAL example codeabout / GDAL example code GDAL Python librarydownloading / Working with GIS data manually Generalized Search Tree (GiST)about / Spatial indexes generateMap() functionabout / The MapGenerator interface / Rendering the map Generic Mapping Tools (GMT)URL / Data format about / Data format geocode / Analyzing geospatial data geocoder / Advanced PostGIS features Geodabout / Geod fwd() method / Geod inv() method / Geod npts() method / Geod geodetic locationabout / Location GeoDjango / Prerequisites Geographical Information System (GIS) vendors / Geospatial development geographies / Using PostGIS Geography Markup Language (GML) format / GIS data formats GeoJSON format / GIS data formats Geolocationabout / Recent developments geometries / Using PostGIS geometry / Task – calculate the bounding box for each country in the world GeometryCollection class / Design geometry typesPoint / Implementing the find feature view LineString / Implementing the find feature view Polygon / Implementing the find feature view MultiPoint / Implementing the find feature view MultiLineString / Implementing the find feature view MultiPolygon / Implementing the find feature view GeometryCollection / Implementing the find feature view geometry unitsconverting / Converting and standardizing units of geometry and distance standardizing / Converting and standardizing units of geometry and distance Thai-Myanmar border lenght, calculating / Task – calculate the length of the Thai-Myanmar border Shoshone latitude, calculating / Task – find a point 132.7 kilometers west of Soshone, California Shoshone longitude, calculating / Task – find a point 132.7 kilometers west of Soshone, California GEOnet Names Serverabout / GEOnet Names Server screenshot / GEOnet Names Server data format / Data format obtaining / Obtaining and using GEOnet Names Server data using / Obtaining and using GEOnet Names Server data / Designing and building the database, GEOnet Names Server GeoRSSabout / Recent developments geospatialabout / Geospatial development geospatial calculationsperforming / Performing geospatial calculations parks, identifying in or near urban areas / Task – identify parks in or near urban areas geospatial dataabout / Geospatial development coordinates / Geospatial development attributes / Geospatial development analyzing / Analyzing geospatial data, Analyzing and manipulating geospatial data visualizing / Visualizing geospatial data, Visualizing geospatial data GDAL / GDAL/OGR OGR / GDAL/OGR GDAL design / GDAL design GDAL example code / GDAL example code OGR design / OGR design OGR example code / OGR example code manipulating / Analyzing and manipulating geospatial data sources / Sources of other types of geospatial data pre-requisites / Pre-requisites reading / Reading and writing geospatial data writing / Reading and writing geospatial data country bounding boxes, calculating / Task – calculate the bounding box for each country in the world country bounding boxes, saving into shapefile / Task – save the country bounding boxes into a shapefile height data, analyzing with DEM / Task – analyze height data using a digital elevation map representing / Representing and storing geospatial data storing / Representing and storing geospatial data Thailand and Myanmar border, calculating / Task – define the border between Thailand and Myanmar geometries, saving into text file / Task – save geometries into a text file geospatial databasesbest practices / Recommended best practices geospatial databases, Python usedprerequisites / Prerequisites MySQL, working with / Working with MySQL PostGIS, working with / Working with PostGIS SpatiaLite, working with / Working with SpatiaLite comparing / Comparing the databases geospatial developmentabout / Geospatial development overview / Recent developments geospatial development applicationsgeospatial data, analyzing / Analyzing geospatial data geospatial data, visualizing / Visualizing geospatial data geospatial mash-up, creating / Creating a geospatial mash-up geospatial mash-upcreating / Creating a geospatial mash-up GeoTIFF files / Obtaining and using NED data getattr() function / Editing features GetNoDataValue() method / Task – analyze height data using a digital elevation map get_country_datasource() function / Displaying the results get_datasource() function / Setting up the data source get_map_form() function / Editing features get_map_widget() / Editing features get_ogr_feature_attribute() function / Saving the attributes into the shapefile get_shoreline_datasource() function / Using tiled shorelines GISspatially-enabled databases / Spatially-enabled databases spatial indexes / Spatial indexes open source spatially-enabled databases / Open source spatially-enabled databases common spatially-enabled databases / Commercial Spatially-enabled databases GIS conceptsabout / Core GIS concepts location / Location distance / Distance units / Units projection / Projections coordinate system / Coordinate systems datums / Datums shapes / Shapes GIS dataworking manually / Working with GIS data manually GIS data formatabout / GIS data formats raster format data / GIS data formats vector format data / GIS data formats micro-formats / GIS data formats Global Land Cover Facility / Obtaining Landsat imagery Global Positioning System (GPS)about / Recent developments GLOBEabout / Global Land One-kilometer Base Elevation (GLOBE) data format / Data format data, obtaining / Obtaining and using GLOBE data GLOBE DEM dataabout / Global Land One-kilometer Base Elevation (GLOBE) GMLabout / Recent developments GNISabout / Geographic Names Information System (GNIS) screenshot / Geographic Names Information System (GNIS) data format / Data format obtaining / Obtaining and using GNIS Data using / Obtaining and using GNIS Data / GNIS GNIS Database / Designing and building the database Google Earthabout / Recent developments Google Mapsabout / Recent developments Google Maps APIabout / Creating a geospatial mash-up great circle distance calculation / Working with GIS data manually GSHHSabout / Global, self-consistent, hierarchical, high-resolution shoreline database (GSHHS) screenshot / Global, self-consistent, hierarchical, high-resolution shoreline database (GSHHS) data format / Data format obtaining / Obtaining the GSHHS database / GSHHS H handleResponse() callback function / Intercepting mouse clicks Haversine formulaURL / Working with GIS data manually height data, geospatial dataanalyzing, DEM used / Task – analyze height data using a digital elevation map HTML Forms / The "select country" script I import shapefile view function / The "import shapefile" view function import_data() function / Importing shapefiles, Extracting the uploaded shapefile imposmURL / Working with OpenStreetMap data J jurisdictional locationsabout / Location K KMLabout / Recent developments L labelsdrawing / Drawing labels Landsatabout / Landsat data format / Data format Landsat imageryobtaining / Obtaining Landsat imagery Layer objectsabout / Introducing Mapnik layersabout / Maps and layers Layers, Mapnikabout / Design libspatialite / Installing SpatiaLite libspatialite extensionloading / Accessing SpatiaLite from Python line-drawing optionsline color / Line color line width / Line width opacity / Opacity line caps / Line caps line joins / Line joins dashed and dotted lines / Dashed and dotted lines linear distanceabout / Distance linear ringabout / Shapes LinearRing class / Design linear rings / Task – save the country bounding boxes into a shapefile LinePatternSymbolizerabout / LinePatternSymbolizer linesdrawing, onto map / Drawing lines linestringabout / Shapes LineString class / Design LineSymbolizerabout / Introducing Mapnik, LineSymbolizer using / LineSymbolizer LinuxSpatiaLite, installing / Installing SpatiaLite list shapefiles viewimplementing / Implementing the "list shapefiles" view list_countries() function / The "select country" script list_shapefiles() view function / Implementing the "list shapefiles" view locationsabout / Location measuring / Location LULC datafiles / Task – change projections to combine shapefiles using geographic and UTM coordinates M Mac OS XSpatiaLite, installing / Installing SpatiaLite Map Definition Fileabout / Introducing Mapnik map definition fileabout / Map definition files MapGeneratorabout / MapGenerator revisited interface / The MapGenerator interface main map layer, creating / Creating the main map layer points, displaying on map / Displaying points on the map map, rendering / Rendering the map mapGenerator.generateMap() function / Rendering the map image mapGenerator.py moduleabout / The MapGenerator interface Mapnikabout / Creating a geospatial mash-up, Mapnik, Introducing Mapnik features / Mapnik, Introducing Mapnik design / Design example code / Example code documentation / Documentation availability / Availability URL / Availability, Introducing Mapnik map, generating / Introducing Mapnik Polygons layer / Introducing Mapnik example map, creating / Creating an example map Python documentation / Mapnik in depth data sources / Data sources rules / Rules, filters, and styles styles / Rules, filters, and styles filters / Rules, filters, and styles symbolizers / Symbolizers maps / Maps and layers layers / Maps and layers map rendering / Map rendering mapnik.Layer classmethods / Layer attributes and methods mapnik.Map classattributes / Map attributes and methods methods / Map attributes and methods mapnik.Shapefile() function / Shapefile mapnik.SQLite() function / SQLite Mapnik Datasource objectsetting up / Data sources Mapnik WikiURL / Documentation map renderingabout / Map rendering mapsabout / Maps and layers MapServerabout / Creating a geospatial mash-up markup application, Django applicationabout / The structure of a Django application MBRContains() function / MySQL MemoryDatasourceabout / MemoryDatasource meridiansabout / Location messages framework, Django applicationabout / The structure of a Django application micro-formatsWell-known Text (WKT) / GIS data formats Well-known Binary (WKB) / GIS data formats GeoJSON / GIS data formats Geography Markup Language (GML) / GIS data formats minimum bounding rectangleabout / Spatial indexes / MySQL models, Djangoabout / Models models.py fileediting / The models.py file mouse clicks, ShapeEditor applicationintercepting / Intercepting mouse clicks MS SQL Serverabout / MS SQL Server MS WindowsSpatiaLite, installing / Installing SpatiaLite MultiLineString class / Design MultiPoint class / Design MultiPolygon class / Design MySQLabout / MySQL downloading / MySQL acessing, from Python programs / MySQL disadvantages / MySQL MySQL-Python driver / MySQLabout / MySQL MySQLdbURL / MySQL MySQL query optimizerabout / MySQL N NAD 27about / Datums NAD 83about / Datums National Map Viewer / Obtaining and using NED data Natural Earth, raster-format dataabout / Natural Earth raster maps / Natural Earth data format / Data format obtaining / Obtaining and using Natural Earth raster data using / Obtaining and using Natural Earth raster data Natural Earth, vector-format dataURL / Natural Earth about / Natural Earth cultural map data / Natural Earth physical map data / Natural Earth data format / Data format data, obtaining / Obtaining and using Natural Earth vector data data, using / Obtaining and using Natural Earth vector data nature of map projectionsabout / The nature of map projections NEDabout / National Elevation Dataset (NED) data format / Data format data, obtaining / Obtaining and using NED data data, using / Obtaining and using NED data no data value / Task – analyze height data using a digital elevation map NT (Name Type) field / Worldwide place name data O OGRabout / Recent developments Ogr data sourceabout / Ogr OGR designabout / OGR design data source / OGR design layers / OGR design spatial reference / OGR design feature / OGR design attributes / OGR design geometry / OGR design OGR example codeabout / OGR example code OGR Shapefiledefining / Defining the OGR shapefile onClick() function / Intercepting mouse clicks Open Geospatial ConsortiumURL / Recent developments about / Recent developments Openlayersabout / Creating a geospatial mash-up OpenLayersused, for displaying map / Using OpenLayers to display the map OpenLayers.Control.Click class / Intercepting mouse clicks OpenLayers.Request.GET function / Intercepting mouse clicks open source spatially-enabled databasesabout / Open source spatially-enabled databases MySQL / MySQL PostGIS / PostGIS SpatiaLite / SpatiaLite OpenStreetMapURL / Mapnik, OpenStreetMap about / OpenStreetMap screenshot / OpenStreetMap data format / Data format geospatial data, obtaining / Obtaining and using OpenStreetMap data geospatial data, using / Obtaining and using OpenStreetMap data data, working with / Working with OpenStreetMap data OpenStreetMap API / The OpenStreetMap API OpenStreetMap geocoderabout / Recent developments Oracleabout / Oracle Oracle Locatorabout / Oracle Oracle Spatialabout / Oracle orthorectification / Data format os.path.join() function / Shapefile osm2pgsql tool / Working with OpenStreetMap data OsmApi / The OpenStreetMap API OSM data sourceabout / OSM overlay / Visualizing geospatial data P painters algorithmabout / Introducing Mapnik parallelsabout / Location parametersabout / URL dispatching Planet.osmabout / Planet.osm mirror site / Mirror sites and extracts extracts / Mirror sites and extracts pointabout / Shapes Point class / Design pointsdrawing / Drawing points PointSymbolizerabout / PointSymbolizer polygonabout / Shapes polygon-drawing optionsfill color / Fill color attribute / Opacity gamma correction / Gamma correction polygon.contains(point) method / MySQL Polygon class / Design PolygonPatternSymbolizerabout / PolygonPatternSymbolizer polygonsdrawing / Drawing polygons PolygonSymbolizerabout / Introducing Mapnik, PolygonSymbolizer polylinesabout / Shapes PostGIS / Analyzing geospatial dataabout / Recent developments, PostGIS installing / Installing and configuring PostGIS downloading / Installing and configuring PostGIS configuring / Installing and configuring PostGIS using / Using PostGIS documentation / Documentation features / Advanced PostGIS features PostGIS databasesetting up, for ShapeEditor application / Setting up the database PostGIS datasourceabout / PostGIS PostGIS manualURL / Documentation PostGIS query optimizerabout / PostGIS PostgreSQL database / PostGIS PostgreSQL manualURL / Documentation prime meridianabout / Location Projabout / Proj PROJ.4about / Recent developments, Availability projected coordinate systemabout / Coordinate systems projectionabout / Geospatial development, Projections, Changing datums and projections cylindrical projections / Cylindrical projections conic projection / Conic projections azimuthal projection / Azimuthal projections nature of map projections / The nature of map projections dealing with / Dealing with projections pyproj / pyproj design / Design example code / Example code documentation / Documentation availability / Availability changing / Task – change projections to combine shapefiles using geographic and UTM coordinates Proj Python library / Analyzing geospatial data Psycopginstalling / Installing and configuring PostGIS Psycopg database / PostGIS Psycopg documentationURL / Documentation pyproj libraryabout / Design Proj / Proj Geod / Geod for MS Windows / Availability for Linux / Availability for Macintosh / Availability pysqliteinstalling / Installing pysqlite URL / Installing pysqlite PythonURL / Python about / Python features / Python Python Database APIabout / MySQL Python Database Programming Wiki pageURL / MySQL Python Package Indexabout / Python URL / Python geospatial development / Geospatial development Python Standard Librariesabout / Python Q qualityplace name issues / Place name issues Lat/Long coordinate problems / Lat/Long coordinate problems query optimization processMySQL / MySQL PostGIS / PostGIS SpatiaLite / SpatiaLite R R-Tree data structuresabout / Spatial indexes R-Tree indexesabout / Spatial indexes raster format dataabout / GIS data formats Digital Raster Graphic (DRG) / GIS data formats Digital Elevation Model (DEM) / GIS data formats BIL / GIS data formats BIP / GIS data formats BSQ / GIS data formats raster imagesdrawing / Drawing raster images raster mapsabout / Natural Earth Cross-Blended Hypsometric Tints / Natural Earth Natural Earth 1 / Natural Earth Natural Earth 2 / Natural Earth Ocean Bottom dataset / Natural Earth Shaded Relief imagery / Natural Earth RasterSymbolizerabout / Drawing raster images uses / Drawing raster images ReadRaster() method / Task – analyze height data using a digital elevation map reference pointsabout / Coordinate systems roadsdrawing / Drawing roads and other complex linear features root() functionabout / Implementing Tile Map Server ruleabout / Introducing Mapnik rules, Mapnikconditions / Rules, filters, and styles symbolizers / Rules, filters, and styles else rules / "Else" rules also rules / "Also" rules S scale denominators / Scale denominators select area scriptabout / The "select area" script bounding box, calculating / Calculating the bounding box map’s dimension, calculating / Calculating the map's dimensions data source, setting up / Setting up the data source map image, rendering / Rendering the map image select country script / The "select country" script select_feature.html template / Adding features service() functionabout / Implementing Tile Map Server sessions system, Django applicationabout / The structure of a Django application setattr() function / Editing features SetField() method / Saving the attributes into the shapefile setField() method / Task – save the country bounding boxes into a shapefile set_ogr_feature_attribute() function / Saving the attributes into the shapefile shaded relief imagery / Sources of geospatial data in raster format ShapeEditor applicationworkflow / About ShapeEditor, Selecting a feature to edit web interface / About ShapeEditor shapefile, importing / About ShapeEditor, Importing a shapefile, Importing shapefiles features / About ShapeEditor designing / Designing ShapeEditor feature, selecting / Selecting a feature feature, editing / Editing a feature shapefile, exporting / Exporting a shapefile, Exporting shapefiles prerequisites / Prerequisites database, setting up / Setting up the database setting up / Setting up the ShapeEditor project defining / Defining the ShapeEditor's applications shared application, creating / Creating the shared application data models, defining / Defining the data models admin system / Playing with the admin system list shapefiles view, implementing / Implementing the "list shapefiles" view feature, selecting for edit / Selecting a feature to edit Tile Map Server, implementing / Implementing Tile Map Server mouse clicks, intercepting / Intercepting mouse clicks features, editing / Editing features features, adding / Adding features features, deleting / Deleting features shapefiles, deleting / Deleting shapefiles using / Using ShapeEditor enhancements / Further improvements and enhancements shapefile datasourceabout / Shapefile Shapefile formatabout / GIS data formats Shapefile objectadding, to database / Add the Shapefile object to the database shapefilesimporting / Importing shapefiles contents, importing / Importing the shapefile's contents opening / Open the shapefile attributes, defining / Define the shapefile's attributes features, storing / Store the shapefile's features attributes, storing / Store the shapefile's attributes cleaning up / Cleaning up deleting / Deleting shapefiles shapefiles, exportingabout / Exporting shapefiles OGR Shapefile, defining / Defining the OGR shapefile features, saving into shapefile / Saving the features into the shapefile attributes, saving into shapefile / Saving the attributes into the shapefile shapefile, compressing / Compressing the shapefile temporary files, deleting / Deleting temporary files ZIP archive, returning to user / Returning the ZIP archive to the user Shapelyabout / Shapely design / Design Point class / Design LineString class / Design LinearRing class / Design Polygon class / Design MultiPoint class / Design MultiLineString class / Design MultiPolygon class / Design GeometryCollection class / Design example code / Example code documentation / Documentation availability / Availability shapesabout / Shapes point / Shapes linestring / Shapes polygon / Shapes shared.utils module / Implementing the find feature view shared database module / The shared "database" module ShieldSymbolizerabout / ShieldSymbolizer showResults.py script / Using tiled shorelines show result scriptabout / The "show results" script clicked-on point, identifying / Identifying the clicked-on point distance features, identifying / Identifying features by distance simple features formatabout / GIS data formats sitemaps framework, Django applicationabout / The structure of a Django application source code format, Linuxabout / MySQL source code format, Mac OS X about / MySQL sources, geospatial dataabout / Sources of other types of geospatial data GEOnet Names Server / GEOnet Names Server GNIS / Geographic Names Information System (GNIS) selecting / Choosing your geospatial data source sources, raster-format geospatial dataabout / Sources of geospatial data in raster format Landsat / Landsat Natural Earth / Natural Earth GLOBE / Global Land One-kilometer Base Elevation (GLOBE) National Elevation Dataset (NED) / National Elevation Dataset (NED) sources, vector-format geospatial dataOpenStreetMap / OpenStreetMap TIGER / TIGER Natural Earth / Natural Earth GSHHS / Global, self-consistent, hierarchical, high-resolution shoreline database (GSHHS) World Borders Dataset / World Borders Dataset spatial datatypes / Spatially-enabled databases spatial functions / Spatially-enabled databases spatial indexesabout / Spatial indexes R-Tree indexes / Spatial indexes SpatiaLiteabout / SpatiaLite installing / Installing SpatiaLite installing, on Mac OS X / Installing SpatiaLite installing, on MS Windows / Installing SpatiaLite installing, on Linux / Installing SpatiaLite pysqlite, installing / Installing pysqlite accessing, from Python / Accessing SpatiaLite from Python documentation / Documentation URL / Documentation online documentation / Documentation using / Using SpatiaLite capabilities / SpatiaLite capabilities SpatiaLite query optimizerabout / SpatiaLite spatial joins / Spatially-enabled databases spatially-enabled databasesabout / Spatially-enabled databases functioning / Spatially-enabled databases spatial queries / Spatially-enabled databases spatial query functions / Implementing the find feature view spatial reference / Design, Task – save the country bounding boxes into a shapefile, Representing and storing geospatial data, Using the database to keep track of spatial references Spatial Reference Identifier (SRID) / Using the database to keep track of spatial references SQLite data sourceabout / SQLite Styles, Mapnikabout / Design, Introducing Mapnik ST_AsText() function / Using PostGIS ST_CONTAINS() function / A hybrid approach ST_DWITHIN() function / A hybrid approach ST_GeomFromText() function / Using PostGIS subselect queryabout / PostGIS using / PostGIS Symbolizers, Mapnikabout / Design, Introducing Mapnik PolygonSymbolizer / Introducing Mapnik LineSymbolizer / Introducing Mapnik TextSymbolizer / Introducing Mapnik lines, drawing / Drawing lines polygons, drawing / Drawing polygons labels, drawing / Drawing labels points, drawing / Drawing points syndication system, Django applicationabout / The structure of a Django application T template, Djangoabout / Templates terminology, TMS protocolTile Map Server / Implementing Tile Map Server Tile Map Service / Implementing Tile Map Server Tile Map / Implementing Tile Map Server Tile Set / Implementing Tile Map Server Tile / Implementing Tile Map Server TextSymbolizerabout / Introducing Mapnik, TextSymbolizer text, selecting for display / Specifying the text to be displayed font, selecting / Selecting a suitable font semi-transparent text, drawing / Drawing semi-transparent text text placement, controlling / Controlling text placement labels, repeating / Repeating labels text overlap, controlling / Controlling text overlap text, drawing on dark background / Drawing text on a dark background position, adjusting of text / Adjusting the position of the text labels, splitting across multiple lines / Splitting labels across multiple lines character spacing, controlling / Controlling character and line spacing line spacing, controlling / Controlling character and line spacing capitalization, controlling / Controlling capitalization advanced text placement and formatting / Advanced text placement and formatting TIGERabout / TIGER data format / Data format data, obtaining / Obtaining and using TIGER data data, using / Obtaining and using TIGER data TIGER/Line formatabout / GIS data formats Tileabout / Implementing Tile Map Server Tile Mapabout / Implementing Tile Map Server tileMap() function / Implementing Tile Map Serverabout / Implementing Tile Map Server Tile Map Servercompleting / Completing the Tile Map Server Tile Map Server (TMS) / Selecting a feature Tile Map Serviceabout / Implementing Tile Map Server tilePolys array / Calculating the tiled shorelines tile renderingabout / Tile rendering query parameters, parsing / Parsing the query parameters map, setting up / Setting up the map base layer, defining / Defining the base layer feature layer, defining / Defining the feature layer map tile, rendering / Rendering the map tile Tile Setabout / Implementing Tile Map Server TMS protocolimplementing / Implementing Tile Map Server about / Implementing Tile Map Server terminology / Implementing Tile Map Server error handling / Implementing Tile Map Server base map, setting up / Setting up the base map tile, rendering / Tile rendering map, displaying with OpenLayers / Using OpenLayers to display the map traveling distanceabout / Distance triggersabout / SpatiaLite U unitsabout / Units Universal Transverse Mercator (UTM) coordinate systemabout / Coordinate systems Universal Transverse Mercator (UTM) projection / Task – change projections to combine shapefiles using geographic and UTM coordinates unprojected coordinatesabout / Geospatial development unprojected coordinate systemabout / Coordinate systems unwrap_geos_geometry() function / Saving the features into the shapefile uploaded shapefileextracting / Extracting the uploaded shapefile URLConfabout / URL dispatching URL dispatching, Djangoabout / URL dispatching usability / Usability US Census BureauURL / Working with GIS data manually utils.calc_geometry_field() / Editing features utils.get_map_form() / Editing features utils.get_ogr_feature_attribute() function / Saving the attributes into the shapefile V vector-format geospatial dataabout / Sources of geospatial data in vector format sources / Sources of geospatial data in vector format vector format dataabout / GIS data formats shapefile / GIS data formats simple features / GIS data formats TIGER/Line / GIS data formats coverage / GIS data formats view, Djangoabout / Views Virtual Datasource (VRT) formatabout / Ogr W WCSabout / Recent developments WebGIS websiteURL / Task – change projections to combine shapefiles using geographic and UTM coordinates Well-known Binary (WKB) format / GIS data formats, Representing and storing geospatial data Well-known Text (WKT) format / GIS data formats, Representing and storing geospatial data WFSabout / Recent developments WGS 84about / Datums WMSabout / Recent developments World Borders Datasetabout / World Borders Dataset data format / Data format obtaining / Obtaining World Borders Dataset downloading / Task – calculate the bounding box for each country in the world / World Borders Dataset, World Borders Dataset World Data Bank II / Global, self-consistent, hierarchical, high-resolution shoreline database (GSHHS) world reference system (WRS) / Obtaining Landsat imagery World Vector Shoreline / Global, self-consistent, hierarchical, high-resolution shoreline database (GSHHS) X XCodeabout / Availability installing / Availability

.> <member type="way" ref="22930719" role=""/> <member type="way" ref="23963573" role=""/> <member type="way" ref="28562757" role=""/> <member type="way" ref="23963609" role=""/> <member type="way" ref="47475844" role=""/> <tag k="name" v="State Highway 30A"/> <tag k="ref" v="30A"/> <tag k="route" v="road"/> <tag k="type" v="route"/> </relation> </osm> Obtaining and using OpenStreetMap data You can obtain geospatial data from OpenStreetMap in one of following three ways: You can use the OpenStreetMap API to download a subset of the data you are interested in. You can download the entire OpenStreetMap database, called Planet.osm, and process it locally. Note that this is a multi-gigabyte download. You can make use of one of the mirror sites that provide OpenStreetMap data nicely packaged into smaller chunks and converted into other data formats. For example, you can download the data for North America on a state-by-state basis, in one of several available formats, including shapefiles. Let's take a closer look at each of these three options. The OpenStreetMap API Using the OpenStreetMap API (http://wiki.openstreetmap.org/wiki/API), you can download selected data from the OpenStreetMap database in one of following three ways: You can specify a bounding box defining the minimum and maximum longitude and latitude values, as shown in the following screenshot: The API will return all of the elements (nodes, ways, and relations), which are completely or partially inside the specified bounding box.

OSM The OSM data source allows you to include OpenStreetMap data onto a map. The OpenStreetMap data is stored in .osm format, which is an XML format containing the underlying nodes, ways and relations used by OpenStreetMap. The OpenStreetMap data format, and options for downloading .osm files, can be found at: http://wiki.openstreetmap.org/wiki/.osm If you have downloaded a .osm file and want to access it locally, you can set up your data source like this: datasource = mapnik.OSM(file="myData.osm") If you wish to use an OpenStreetMap API call to retrieve the OSM data on the fly, you can do this by supplying a URL to read the data from, along with a bounding box to identify which set of data you want to download. For example: osmURL = "http://api.openstreetmap.org/api/0.6/map" bounds = "176.193,-38.172,176.276,-38.108" datasource = mapnik.OSM(url=osmURL, bbox=bounds) The bounding box is a string containing the left, bottom, right, and top coordinates for the desired bounding box, respectively.


PostGIS in Action, 2nd Edition by Regina O. Obe, Leo S. Hsu

call centre, crowdsourcing, database schema, Debian, domain-specific language, en.wikipedia.org, Firefox, Google Earth, job automation, McMansion, megacity, Mercator projection, Network effects, openstreetmap, planetary scale, profit maximization, Ruby on Rails, Skype, South of Market, San Francisco, traveling salesman, web application

This first set of maps will just give you a feel for what each looks like. In subsequent sections, we’ll add PostGIS layers and PostGIS queries that output JSON. OpenStreetMap tiles: publicly available tiles versus building your own For the base layers, we’ll use OpenStreetMap public tile servers for the exercises that follow. Because OpenStreetMap public tile servers run on donations, you may be cut off if you make a lot of calls to them. The tile usage policy is detailed at http:// wiki.openstreetmap.org/wiki/Tile_usage_policy. If you have heavy traffic, you should build your own tiles, or use tiles from a commercial service, such as MapQuest OSM tiles (http://wiki.openstreetmap.org/wiki/ Mapquest#MapQuest-hosted_map_tiles), CloudMade (http://cloudmade.com), or Mapbox (http://mapbox.com), which also provide storage and tools for building custom tiles.

GPX data is also always in the WGS 84 lon/lat spatial reference system, which has a PostGIS SRID/EPSG number of 4326. Ogr2ogr is smart enough to know this, so it puts in the correct SRID for you. For more details about command-line switches specific to the OGR GPX driver, visit www.gdal.org/ogr/drv_gpx.html. OpenStreetMap is full of user-contributed GPX files uploaded by users worldwide. You can find these at www.openstreetmap.org/traces. We randomly selected one from Australia titled “A bike trip around Narangba” by going to www.openstreetmap.org/ traces/tag/australia and downloading the file www.openstreetmap.org/user/Ash %20Kyd/traces/468761. You can find out more about the data you’re about to load by using ogrinfo. Listing 4.2 Displaying info about GPX file using ogrinfo ogrinfo 468761.gpx Command INFO: Open of '468761.gpx' using driver 'GPX' successful. 1: waypoints (Point) 2: routes (Line String) 3: tracks (Multi Line String) 4: route_points (Point) 5: track_points (Point) Output Next, you can load this up into a staging schema with the simple ogr2ogr command shown in the next listing.

By selecting a region, the BBOX filters should be filled in. For example, if you picked the Arc de Triomphe area, the min longitude/latitude and max longitude/latitude will be filled in the bounding box coordinates. Something like 2.28568,48.87957,2.30371,48.8676 will appear in the coordinate text boxes. Select OpenStreetMap XML Data as the export format. We called ours arctriump.osm. Licensed to tracy moore <nordick.an@gmail.com> www.it-ebooks.info Importing OpenStreetMap data with osm2pgsql 101 You can also use one of the REST APIs provided by OpenStreetMap to achieve the same results. The following listing demonstrates carving out a similar section using a wget call. Note that the bbox argument corresponds to the minimum longitude/latitude and maximum longitude/latitude of the area you’re interested in. Listing 4.8 Download a bounding box area covering the Arc de Triomphe wget --progress=dot:mega -O "arc.osm" ➥"http://www.overpass-api.de/api/xapi?


pages: 39 words: 4,665

Data Source Handbook by Pete Warden

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en.wikipedia.org, Menlo Park, openstreetmap, phenotype, social graph

There are no rate limits, but you do have to get an API key and use OAuth to authenticate your calls: http://api.simplegeo.com/1.0/context/37.778381,-122.389388.json { "query":{ "latitude":37.778381, "longitude":-122.389388 }, "timestamp":1291766899.794, "weather": { "temperature": "65F", "conditions": "light haze" }, { "demographics": { "metro_score": 9 }, "features":[ { "handle":"SG_4H2GqJDZrc0ZAjKGR8qM4D_37.778406_-122.389506", "license":"http://creativecommons.org/licenses/by-sa/2.0/", "attribution":"(c) OpenStreetMap (http://openstreetmap.org/) and contributors CC-BY-SA (http://creativecommons.org/licenses/by-sa/2.0/)", "classifiers":[ { "type":"Entertainment", "category":"Arena", "subcategory":"Stadium" } ], "bounds":[ -122.39115, 37.777233, -122.387775, 37.779731 ], "abbr":null, "name":"AT&T Park", "href":"http://api.simplegeo.com/ 1.0/features/SG_4H2GqJDZrc0ZAjKGR8qM4D_37.778406_-122.389506.json" }, ... Locations | 17 Yahoo!

<parameters applicable-location="point1"> <temperature type="maximum" units="Fahrenheit" time-layout="k-p24h-n8-1"> <name>Daily Maximum Temperature</name> <value>38</value> <value>33</value> <value>41</value> <value>41</value> <value>35</value> <value>32</value> <value>30</value> <value>35</value> </temperature> <temperature type="minimum" units="Fahrenheit" time-layout="k-p24h-n7-2"> <name>Daily Minimum Temperature</name> <value>22</value> <value>28</value> <value>34</value> <value>22</value> <value>24</value> <value>17</value> Locations | 23 <value>20</value> </temperature> </parameters> </data> </dwml> OpenStreetMap The volunteers at OpenStreetMap have created a somewhat-chaotic but comprehensive set of geographic information, and you can download everything they’ve gathered as a single massive file. One unique strength is the coverage of areas in the developing world that are absent from commercial databases, and since it’s so easy to change, even US locations are often more up-to-date with recent changes than more traditional maps.

ISBN: 978-1-449-30314-3 [LSI] 1295970672 Table of Contents Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii Data Source Handbook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Websites WHOIS Blekko bit.ly Compete Delicious BackType PagePeeker People by Email WebFinger Flickr Gravatar Amazon AIM FriendFeed Google Social Graph MySpace Github Rapleaf Jigsaw People by Name WhitePages LinkedIn GenderFromName People by Account Klout Qwerly Search Terms BOSS 1 1 2 3 3 4 5 5 5 6 6 6 7 7 8 8 9 10 10 11 11 11 11 11 12 12 12 12 13 v Blekko Bing Google Custom Search Wikipedia Google Suggest Wolfram Alpha Locations SimpleGeo Yahoo! Google Geocoding API CityGrid Geocoder.us Geodict GeoNames US Census Zillow Neighborhoods Natural Earth US National Weather Service OpenStreetMap MaxMind Companies CrunchBase ZoomInfo Hoover’s Yahoo! Finance IP Addresses MaxMind Infochimps Books, Films, Music, and Products Amazon Google Shopping Google Book Search Netflix Yahoo! Music Musicbrainz The Movie DB Freebase vi | Table of Contents 13 14 14 15 15 16 16 17 18 18 19 19 19 20 20 21 22 23 24 24 24 24 25 25 26 26 26 27 27 27 27 28 28 29 29 29 30 Preface A lot of new sources of free, public data have emerged over the last few years, and this guide covers some of the most useful.


pages: 316 words: 90,165

You Are Here: From the Compass to GPS, the History and Future of How We Find Ourselves by Hiawatha Bray

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A Declaration of the Independence of Cyberspace, Albert Einstein, Big bang: deregulation of the City of London, bitcoin, British Empire, call centre, crowdsourcing, Dava Sobel, digital map, don't be evil, Edmond Halley, Edward Snowden, Firefox, game design, Google Earth, Hedy Lamarr / George Antheil, Isaac Newton, job automation, John Harrison: Longitude, John Snow's cholera map, license plate recognition, lone genius, openstreetmap, polynesian navigation, popular electronics, RAND corporation, RFID, Ronald Reagan, Silicon Valley, Steve Jobs, Steven Levy, trade route, turn-by-turn navigation, uranium enrichment, urban planning, V2 rocket, Zipcar

By contrast, all OSM maps are published under a broad copyright. Any individual or business can copy, modify, or reuse OpenStreetMap’s products to their heart’s content. They are merely required to post a notice giving credit to OpenStreetMap and its contributors. Few seem to mind Google’s profiteering, as long as it results in better maps. The success of OpenStreetMap has provided healthy competition, as well as fodder for good-natured disputation. Which model produces better maps—Google’s lavishly funded commercial operation or OpenStreetMap’s legions of untrained part-time amateurs? With its ample finances and direct access to the latest, sharpest satellite imagery, Google’s got an overall edge in quality that OpenStreetMap will not soon match. Yet for one of its most valuable features, Google Maps relies on the kindness of strangers.

Roberto Rocha, “A Map-Making Democracy,” Montreal Gazette, December 20, 2007. 18. Michael Cross, “OS Maps Finally Available to Not-for-Profit Organisations,” Guardian, December 13, 2007. 19. Jonathan Brown, “No. 1 in the Charts Since 1747; Now Its Maps Are Available on the Web,” Independent, April 2, 2010. 20. Carl Franzen, “OpenStreetMap Reaches 1 Million Users, Will Rival Google Maps in 2 Years,” Talking Points Memo, January 12, 2013, http://idealab.talkingpointsmemo.com/2013/01/openstreetmap-reaches-1-million-users-will-rival-google-maps-in-2-years.php. 21. Rocha, “A Map-Making Democracy.” 22. “MapQuest to Launch Open-Source Mapping in Europe,” Wireless News, July 20, 2010. 23. Rob D. Young, “Google Maps API to Charge for High-Volume Usage,” Search Engine Watch, November 2, 2011, http://searchenginewatch.com/article/2122151/Google-Maps-API-to-Charge-for-High-Volume-Usage. 24.

He created the software tools he would need, purchased a GPS unit—at the time GPS devices cost hundreds of dollars and were “larger than a brick”—attached it to a laptop, packed the setup into a backpack, and started pedaling his bike through the streets of central London. Bit by bit, his map of the area began to come together. Coast did more than pedal his bike; he also peddled his idea to anybody who would listen. He called it OpenStreetMap, a campaign to create a new kind of map, drawn by volunteers and available to everybody at no charge. Furthermore, OSM would not stop at creating a new map of the United Kingdom; Coast decided to cover the entire planet. That meant finding help, and a lot of it. Even though the participants would not earn a dime for their efforts, Coast believed they would step forward. “I think I was young and naive,” he said.16 Coast set up an Internet mailing list for mapping enthusiasts; he created a wiki, a do-it-yourself database of expert knowledge on do-it-yourself geography.

The Data Revolution: Big Data, Open Data, Data Infrastructures and Their Consequences by Rob Kitchin

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Bayesian statistics, business intelligence, business process, cellular automata, Celtic Tiger, cloud computing, collateralized debt obligation, conceptual framework, congestion charging, corporate governance, correlation does not imply causation, crowdsourcing, discrete time, George Gilder, Google Earth, Infrastructure as a Service, Internet Archive, Internet of things, invisible hand, knowledge economy, late capitalism, lifelogging, linked data, Masdar, means of production, Nate Silver, natural language processing, openstreetmap, pattern recognition, platform as a service, recommendation engine, RFID, semantic web, sentiment analysis, slashdot, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, smart grid, smart meter, software as a service, statistical model, supply-chain management, the scientific method, The Signal and the Noise by Nate Silver, transaction costs

The example Carr highlights is Wikipedia, which although popular and extensive, has grown in a haphazard way that matches the selective interests of participants, and has incomplete, sometimes poorly written, trivial and highly contested articles which undermine its authority and usability. Carr contends that ‘if Wikipedia weren’t free, it is unlikely its readers would be so forgiving of its failings’ (2007: 4). OpenStreetMap can suffer from a lack of coverage in some areas where there are few volunteers. There are also concerns as to the sustainability of volunteered crowdsourced labour, with Carr (2007) arguing that the connections that bind a virtual crowd together are often superficial, lacking depth and obligatory commitment, are liable to dispersion, and are reliant on a small core group to keep the project going and provide the bulk of the labour. In contrast, others have noted with respect to OpenStreetMap, that the quality of data produced matches that of professional companies, and that the coverage is diverse (Haklay 2010; Mooney et al. 2011). What this discussion highlights is that just because a dataset is huge in volume, it is not necessarily random, representative, clean, has fidelity, or is trustworthy.

., who the email was sent to or received from, the time/date, subject, attachments). Even if the e-mail is downloaded locally and deleted it is still retained on the server, with most institutions and companies keeping such data for a number of years. Like other forms of data, spatial data has grown enormously in recent years, from real-time remote sensing and radar imagery, to large crowdsourced projects such as OpenStreetMap, to digital spatial trails created by GPS receivers being embedded in devices. The first two seek to be spatially exhaustive, capturing the terrain of the entire planet, mapping the infrastructure of whole countries and providing a creative commons licensed mapping dataset. The third provides the ability to track and trace movement across space over time; to construct individual time–space trails that can be aggregated to provide time–space models of behaviour across whole cities and regions.

As a consequence, vast quantities of data are routinely generated concerning interactions across ICT networks Volunteered data In contrast to surveillance that is either directed at people or things by individuals and agencies, or are captured automatically as an inherent feature of a device or system, much big data are actively volunteered by people. In such cases, individuals generate and input data and labour either to avail themselves of a service (such as social media) or to take part in a collective project (such OpenStreetMap or Wikipedia). Such labour has been called prosumption as the modes of production and consumption have been partially collapsed onto one another, with individuals assuming a role in the production of the service or product they are consuming (Ritzer and Jurgenson 2010). For example, the content of a social media site is simultaneously produced and consumed by individual users inputting comments, uploading photos and videos, and engaging in discussion and the exchange of sentiment (‘liking’ or ‘disliking’ something).


pages: 367 words: 99,765

Maphead: Charting the Wide, Weird World of Geography Wonks by Ken Jennings

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Asperger Syndrome, augmented reality, Bartolomé de las Casas, Berlin Wall, British Empire, clean water, David Brooks, digital map, don't be evil, dumpster diving, Eratosthenes, game design, Google Earth, helicopter parent, hive mind, index card, John Harrison: Longitude, John Snow's cholera map, Mercator projection, Mercator projection distort size, especially Greenland and Africa, Mikhail Gorbachev, New Journalism, openstreetmap, place-making, Ronald Reagan, Saturday Night Live, Skype, Stewart Brand, Tacoma Narrows Bridge, traveling salesman, urban planning

Rescue workers didn’t know where to start; even the ones with GPS receivers quickly discovered that there were no good digital maps of Haiti. Google, to its credit, gave the United Nations full access to the usually proprietary data in its collaborative Map Maker tool, but the real hero of the hour was the OpenStreetMap project, an open-source alternative to Map Maker. OpenStreetMap is essentially the Wikipedia of maps: anyone can use it, anyone can change it in real time, and its data is free and uncopyrighted in perpetuity. When the earthquake struck, late Tuesday afternoon, Haiti was a white void in OpenStreetMap. Within hours, thousands of amateur mappers were collaborating all over the world, adding roads and buildings from aerial imagery to the database, until every back alley and footpath in Port-au-Prince had been charted. Relief workers updated the maps with traffic revisions, triage centers, and refugee centers, and just days later, the volunteer-drawn map was the United Nations’ go-to source of transportation information.

Relief workers updated the maps with traffic revisions, triage centers, and refugee centers, and just days later, the volunteer-drawn map was the United Nations’ go-to source of transportation information. “Many thanks to all crisis mappers for great contributions,” posted UNICEF emergency officer Jihad Abdalla. “You made my life much easier, since I’m a one-man show here . . . million thanks.” Port-au-Prince, as it looked in OpenStreetMap when the earthquake hit and the way it looked a week later After reading about the lives saved in Haiti by OpenStreetMap, I used it to look at my own neighborhood and found that the cul-de-sac we live on was also missing from the map. After hesitating a moment—is it really okay to draw on a map?—I added and labeled my street by hand, Wikipedia-style. It was a surprising rush to add something new, however trivial, to the world’s sum of geographical knowledge.* For a brief moment, I was Captain Cook charting the New Zealand coastline, a veritable Stanley of the suburbs.

Also available in Australia from McArthur Maps, 208 Queens Parade, North Fitzroy, 3068, Australia; phone: 0011 614 3155 5908; e-mail: stuartmcarthur@hotmail.com. Further credits: Images on page 66 courtesy of NASA; map on page 81 courtesy of Altea Gallery (www.alteagallery.com); map on page 118 © Dragonsteel Entertainment, LLC; photograph on page 118 © Mayang Murni Adnin; photograph on page 171 by Jim Payne; images on page 230 © OpenStreetMap and contributors, CC-BY-SA For my parents. And for the kid with the map. CONTENTS Chapter 1: ECCENTRICITY Chapter 2: BEARING Chapter 3: FAULT Chapter 4: BENCHMARKS Chapter 5: ELEVATION Chapter 6: LEGEND Chapter 7: RECKONING Chapter 8: MEANDER Chapter 9: TRANSIT Chapter 10: OVEREDGE Chapter 11: FRONTIER Chapter 12: RELIEF Notes Index MAPHEAD Chapter 1 ECCENTRICITY n.: the deformation of an elliptical map projection My wound is geography.


pages: 25 words: 5,789

Data for the Public Good by Alex Howard

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23andMe, Atul Gawande, Cass Sunstein, cloud computing, crowdsourcing, Hernando de Soto, Internet of things, lifelogging, Network effects, openstreetmap, Silicon Valley, slashdot, social software, social web, web application

Structured social data and geospatial mapping suggest one direction where these tools are evolving in the field. A web application from ESRI deployed during historic floods in Australia demonstrated how crowdsourced social intelligence provided by Ushahidi can enable emergency social data to be integrated into crisis response in a meaningful way. The Australian flooding web app includes the ability to toggle layers from OpenStreetMap, satellite imagery, and topography, and then filter by time or report type. By adding structured social data, the web app provides geospatial information system (GIS) operators with valuable situational awareness that goes beyond standard reporting, including the locations of property damage, roads affected, hazards, evacuations and power outages. Long before the floods or the Red Cross joined Twitter, however, Brian Humphrey of the Los Angeles Fire Department (LAFD) was already online, listening.

After the devastating 2010 earthquake in Haiti, the evolution of volunteers working collaboratively online also offered a glimpse into the potential of citizen-generated data. Crisis Commons has acted as a sort of “geeks without borders.” Around the world, developers, GIS engineers, online media professionals and volunteers collaborated on information technology projects to support disaster relief for post-earthquake Haiti, mapping streets on OpenStreetMap and collecting crisis data on Ushahidi. Healthcare What happens when patients find out how good their doctors really are? That was the question that Harvard Medical School professor Dr. Atul Gawande asked in the New Yorker, nearly a decade ago. The narrative he told in that essay makes the history of quality improvement in medicine compelling, connecting it to the creation of a data registry at the Cystic Fibrosis Foundation in the 1950s.


pages: 497 words: 144,283

Connectography: Mapping the Future of Global Civilization by Parag Khanna

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1919 Motor Transport Corps convoy, 2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 3D printing, 9 dash line, additive manufacturing, Admiral Zheng, affirmative action, agricultural Revolution, Airbnb, Albert Einstein, amateurs talk tactics, professionals talk logistics, Amazon Mechanical Turk, Asian financial crisis, asset allocation, autonomous vehicles, banking crisis, Basel III, Berlin Wall, bitcoin, Black Swan, blockchain, borderless world, Boycotts of Israel, Branko Milanovic, BRICs, British Empire, business intelligence, call centre, capital controls, charter city, clean water, cloud computing, collateralized debt obligation, commoditize, complexity theory, continuation of politics by other means, corporate governance, corporate social responsibility, credit crunch, crony capitalism, crowdsourcing, cryptocurrency, cuban missile crisis, data is the new oil, David Ricardo: comparative advantage, deglobalization, deindustrialization, dematerialisation, Deng Xiaoping, Detroit bankruptcy, digital map, diversification, Doha Development Round, edge city, Edward Snowden, Elon Musk, energy security, ethereum blockchain, European colonialism, eurozone crisis, failed state, Fall of the Berlin Wall, family office, Ferguson, Missouri, financial innovation, financial repression, fixed income, forward guidance, global supply chain, global value chain, global village, Google Earth, Hernando de Soto, high net worth, Hyperloop, ice-free Arctic, if you build it, they will come, illegal immigration, income inequality, income per capita, industrial cluster, industrial robot, informal economy, Infrastructure as a Service, interest rate swap, Intergovernmental Panel on Climate Change (IPCC), Internet of things, Isaac Newton, Jane Jacobs, Jaron Lanier, John von Neumann, Julian Assange, Just-in-time delivery, Kevin Kelly, Khyber Pass, Kibera, Kickstarter, labour market flexibility, labour mobility, LNG terminal, low cost carrier, manufacturing employment, mass affluent, mass immigration, megacity, Mercator projection, Metcalfe’s law, microcredit, mittelstand, Monroe Doctrine, mutually assured destruction, New Economic Geography, new economy, New Urbanism, off grid, offshore financial centre, oil rush, oil shale / tar sands, oil shock, openstreetmap, out of africa, Panamax, Parag Khanna, Peace of Westphalia, peak oil, Pearl River Delta, Peter Thiel, Philip Mirowski, Plutocrats, plutocrats, post-oil, post-Panamax, private military company, purchasing power parity, QWERTY keyboard, race to the bottom, Rana Plaza, rent-seeking, reserve currency, Robert Gordon, Robert Shiller, Robert Shiller, Ronald Coase, Scramble for Africa, Second Machine Age, sharing economy, Shenzhen was a fishing village, Silicon Valley, Silicon Valley startup, six sigma, Skype, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, South China Sea, South Sea Bubble, sovereign wealth fund, special economic zone, spice trade, Stuxnet, supply-chain management, sustainable-tourism, TaskRabbit, telepresence, the built environment, The inhabitant of London could order by telephone, sipping his morning tea in bed, the various products of the whole earth, Tim Cook: Apple, trade route, transaction costs, UNCLOS, uranium enrichment, urban planning, urban sprawl, WikiLeaks, young professional, zero day

NATIONAL GEOSPATIAL-INTELLIGENCE AGENCY https://nga.​maps.​arcgis.​com/​home/ The National Geospatial-Intelligence Agency provides public access to large volumes of satellite and other geo-data and imagery in support of scientific research, natural disaster recovery operations, and crisis management. NORSE ATTACK MAP http://map.​norsecorp.​com/ Norse, a cyber-threat analysis firm, provides real-time visualizations of global cyber war based on data collected every second from Internet and Dark Web sources, plotting origins of attackers and target attacks. OPENSTREETMAP https://www.​openstreetmap.​org/ OpenStreetMap is a crowdsourced mapping platform maintained by a user community that constantly updates data on transportation networks, store locations, and myriad other content generated and verified through aerial imagery, GPS devices, and other tools. PLANET LABS https://www.​planet.​com/ Planet Labs uses a network of low-orbit satellites to capture the most current images of the entire earth and form composite digital renderings that can be used for commercial or humanitarian applications.

Edison; European Energy Supply Security; Gazprom; International Energy Institute; Natural Earth; Norsk Oljemuseum; OpenStreetMap; Petroleum Economist; U.S. Energy Information Administration; White Stream. pai1.31 The New Arctic Geography. Map created by Jeff Blossom. Arctic Council; Durham University; Grenatec; IBRU; IFT; Ministry of Foreign Affairs of Denmark; Natural Earth; The New York Times; Theodora. pai1.32 The World: 4 Degrees Celsius Warmer. © 2009 Reed Business Information—UK. All rights reserved. Distributed by Tribune Content Agency. pai1.33 One Mega-City, Many Systems. Created by University of Wisconsin–Madison Cartography Laboratory. Government of the Hong Kong Special Administrative Region; Global Administrative Areas; Natural Earth; Noun Project; OpenStreetMap; timeout.​com. pai1.34 Global Data Flows Expanding and Accelerating.

If we are an urban species, then producing data-driven cityscapes—mapping cities from within—is as important as capturing their scale. In the 1980s, GPS technology firms began painstakingly driving and geo-coding roads all over the world, building up databases for the suites of navigational tools that are now in almost every new car’s dashboard. Google soon joined the fray, adding more satellite imagery and street views. Today every individual can become a digital cartographer: Maps have gone from Britannica to Wiki. OpenStreetMap, for example, crowdsources street views from millions of members who can also tag and label any structure, infusing local knowledge and essential insight for everything from simple commuting to delivering supplies during humanitarian disasters.*1 We can now even insert updated imagery from Planet Labs’ two dozen shoe-box-size satellites into 3-D maps and fly through the natural or urban environment.


pages: 464 words: 127,283

Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia by Anthony M. Townsend

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1960s counterculture, 4chan, A Pattern Language, Airbnb, Amazon Web Services, anti-communist, Apple II, Bay Area Rapid Transit, Burning Man, business process, call centre, carbon footprint, charter city, chief data officer, clean water, cleantech, cloud computing, computer age, congestion charging, connected car, crack epidemic, crowdsourcing, DARPA: Urban Challenge, data acquisition, Deng Xiaoping, digital map, Donald Davies, East Village, Edward Glaeser, game design, garden city movement, Geoffrey West, Santa Fe Institute, George Gilder, ghettoisation, global supply chain, Grace Hopper, Haight Ashbury, Hedy Lamarr / George Antheil, hive mind, Howard Rheingold, interchangeable parts, Internet Archive, Internet of things, Jacquard loom, Jacquard loom, Jane Jacobs, jitney, John Snow's cholera map, Khan Academy, Kibera, knowledge worker, load shedding, M-Pesa, Mark Zuckerberg, megacity, mobile money, mutually assured destruction, new economy, New Urbanism, Norbert Wiener, Occupy movement, off grid, openstreetmap, packet switching, Parag Khanna, patent troll, Pearl River Delta, place-making, planetary scale, popular electronics, RFC: Request For Comment, RFID, ride hailing / ride sharing, Robert Gordon, self-driving car, sharing economy, Silicon Valley, Skype, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, smart grid, smart meter, social graph, social software, social web, special economic zone, Steve Jobs, Steve Wozniak, Stuxnet, supply-chain management, technoutopianism, Ted Kaczynski, telepresence, The Death and Life of Great American Cities, too big to fail, trade route, Tyler Cowen: Great Stagnation, Upton Sinclair, uranium enrichment, urban decay, urban planning, urban renewal, Vannevar Bush, working poor, working-age population, X Prize, Y2K, zero day, Zipcar

Inspired by Wikipedia’s model of collaborative knowledge production, in 2004 British computer scientist Steve Coast launched OpenStreetMap. Suddenly, anyone could upload a record of his or her movements along the nation’s road network. By systematically traveling the streets of every city, town, and village in the United Kingdom, an army of volunteers set out to make a freely-usable map. As of 2013, after years of collective surveying and annotation, the crowdsourced street map of England was finally nearing completion. The effort has since expanded around the world, and in poor countries often rivals the government’s own maps. After the 2010 Haiti earthquake, which obliterated the nation’s mapping agency in a building collapse, OpenStreetMap provided essential data to relief organizations. The Indian activists who pioneered slum mapping in the 1990s saw their work as a way to begin integrating poor communities into existing city-planning efforts in the hope of securing a fairer share of government resources.

The Indian activists who pioneered slum mapping in the 1990s saw their work as a way to begin integrating poor communities into existing city-planning efforts in the hope of securing a fairer share of government resources. But with the new chart living online in OpenStreetMap, Map Kibera is focused instead on powering new tools that change how the community is represented in the media, and how organizers lobby the government to address local problems. Voice of Kibera, for instance, is a citizen-reporting site built using another open-source tool called Ushahidi. The name means “testimony” in Swahili, and it was developed in 2008 to monitor election violence in Kenya. Voice of Kibera plots media stories about the community onto the open digital map, and allows residents to send in their own reports by SMS. Another Map Kibera effort recruits residents to monitor the progress of infrastructure projects.

And there will always be an urge to “do something,” if only for self-preservation. As Heeks argues, “In a globalized world, the problems of the poor today can, tomorrow—through migration, terrorism, and disease epidemics—become the problems of those at the pyramid’s top.”50 This brings us to the final dilemma: crowdsourcing and the future role of government in delivering basic services. In smart cities, there will be many new crowdsourcing tools that, like OpenStreetMap, create opportunities for people to pool efforts and resources outside of government. Will governments respond by casting off their responsibilities? In rich countries, governments facing tough spending choices may simply withdraw services as citizen-driven alternatives expand, creating huge gaps in support for the poor. In the slums of the developing world’s megacities, where those responsibilities were hardly acknowledged to begin with, crowdsourced alternatives may allow governments to free themselves from the obligation to equalize services in the future.


pages: 83 words: 23,805

City 2.0: The Habitat of the Future and How to Get There by Ted Books

active transport: walking or cycling, Airbnb, Albert Einstein, big-box store, carbon footprint, cleantech, collaborative consumption, crowdsourcing, demand response, housing crisis, Induced demand, Internet of things, Jane Jacobs, jitney, Kibera, Kickstarter, Kitchen Debate, McMansion, megacity, New Urbanism, openstreetmap, ride hailing / ride sharing, self-driving car, sharing economy, Silicon Valley, smart cities, smart grid, the built environment, The Death and Life of Great American Cities, urban planning, urban renewal, urban sprawl, walkable city, Zipcar

In much the same way that the autocatalytic city makes maximum use of physical materials and space, it is also co-opting technology into its fabric. Community-based groups like Shack/Slum Dwellers International have enlisted citizens to conduct their own censuses and create their own maps, which they publish on open online platforms, thereby expanding our collective knowledge of cities. Map Kibera, for instance, used youth volunteers with handheld GPS units and the wiki OpenStreetMap to create a detailed map of the most famous informal settlement in Nairobi. Until Map Kibera, most government maps showed the area as a forest. The project revealed the network of paths and roads and showed locations of churches, clinics, and stores. Residents of Kibera are now using the map as a platform to report uncompleted or badly built government projects, countering official reports and often exposing corruption.


pages: 369 words: 80,355

Too Big to Know: Rethinking Knowledge Now That the Facts Aren't the Facts, Experts Are Everywhere, and the Smartest Person in the Room Is the Room by David Weinberger

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airport security, Alfred Russel Wallace, Amazon Mechanical Turk, Berlin Wall, Black Swan, book scanning, Cass Sunstein, commoditize, corporate social responsibility, crowdsourcing, Danny Hillis, David Brooks, Debian, double entry bookkeeping, double helix, en.wikipedia.org, Exxon Valdez, Fall of the Berlin Wall, future of journalism, Galaxy Zoo, Hacker Ethic, Haight Ashbury, hive mind, Howard Rheingold, invention of the telegraph, jimmy wales, John Harrison: Longitude, Kevin Kelly, linked data, Netflix Prize, New Journalism, Nicholas Carr, Norbert Wiener, openstreetmap, P = NP, Pluto: dwarf planet, profit motive, Ralph Waldo Emerson, RAND corporation, Ray Kurzweil, Republic of Letters, RFID, Richard Feynman, Richard Feynman, Ronald Reagan, semantic web, slashdot, social graph, Steven Pinker, Stewart Brand, technological singularity, Ted Nelson, the scientific method, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, Thomas Malthus, Whole Earth Catalog, X Prize

People from around the world, especially Haitians living elsewhere, started adding in street names. The map was, according to Dickover, “insanely detailed” within just a couple of weeks, and was routinely used by the World Bank, the United Nations, the US Southern Command, the US Marine Corps, the Coast Guard—“anyone who needed to get across town.” By the third week, the World Bank was funding people from OpenStreetMap to train local Haitians in the use of GPS equipment to add more and more local knowledge. Dickover wants to make this sort of partnership of local people with a distributed network of developers more routine, so that we don’t have to wait for disasters to spur action. So, he has been organizing State Department–sponsored “TechCamps” around the world. For example, at the TechCamp in Santiago, Chile, at the end of 2010, people from Brazil and Argentina said they’d like to have a way to aggregate the data gathered by election monitors so they could get an overall picture of the situation on polling days.


pages: 265 words: 69,310

What's Yours Is Mine: Against the Sharing Economy by Tom Slee

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4chan, Airbnb, Amazon Mechanical Turk, asset-backed security, barriers to entry, Berlin Wall, big-box store, bitcoin, blockchain, citizen journalism, collaborative consumption, congestion charging, Credit Default Swap, crowdsourcing, data acquisition, David Brooks, don't be evil, gig economy, Hacker Ethic, income inequality, informal economy, invisible hand, Jacob Appelbaum, Jane Jacobs, Jeff Bezos, Khan Academy, Kibera, Kickstarter, license plate recognition, Lyft, Marc Andreessen, Mark Zuckerberg, move fast and break things, move fast and break things, natural language processing, Netflix Prize, Network effects, new economy, Occupy movement, openstreetmap, Paul Graham, peer-to-peer, peer-to-peer lending, Peter Thiel, pre–internet, principal–agent problem, profit motive, race to the bottom, Ray Kurzweil, recommendation engine, rent control, ride hailing / ride sharing, sharing economy, Silicon Valley, Snapchat, software is eating the world, South of Market, San Francisco, TaskRabbit, The Nature of the Firm, Thomas L Friedman, transportation-network company, Uber and Lyft, Uber for X, ultimatum game, urban planning, WikiLeaks, winner-take-all economy, Y Combinator, Zipcar

Wikipedia is so identified with web-based collaboration that its name has been incorporated into book titles (Wikinomics: How Mass Collaboration Changes Everything) and related initiatives such as the leaked document site WikiLeaks. In Benkler’s The Wealth of Networks, Wikipedia plays a prominent role as an exemplar of “commons-based peer production.” But Wikipedia turned out to be more the exception than the rule. While there are other not-for-profit large-scale collaborative platforms (OpenStreetMap, for example), no other non-­commercial site has reached anything resembling Wikipedia’s influence. As Sue Gardner, then Executive Director of the Wikimedia Foundation, wrote in 2011: Wikipedia represents the fulfilment of the original promise of the internet: that it’s a kind of poster child for online collaboration in the public interest. Because back when the internet started, we figured it would be full of stuff like Wikipedia.


pages: 330 words: 91,805

Peers Inc: How People and Platforms Are Inventing the Collaborative Economy and Reinventing Capitalism by Robin Chase

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3D printing, Airbnb, Amazon Web Services, Andy Kessler, banking crisis, barriers to entry, basic income, Benevolent Dictator For Life (BDFL), bitcoin, blockchain, Burning Man, business climate, call centre, car-free, cloud computing, collaborative consumption, collaborative economy, collective bargaining, commoditize, congestion charging, creative destruction, crowdsourcing, cryptocurrency, decarbonisation, don't be evil, Elon Musk, en.wikipedia.org, ethereum blockchain, Ferguson, Missouri, Firefox, frictionless, Gini coefficient, hive mind, income inequality, index fund, informal economy, Intergovernmental Panel on Climate Change (IPCC), Internet of things, Jane Jacobs, Jeff Bezos, jimmy wales, job satisfaction, Kickstarter, Lean Startup, Lyft, means of production, megacity, Minecraft, minimum viable product, Network effects, new economy, Oculus Rift, openstreetmap, optical character recognition, pattern recognition, peer-to-peer, peer-to-peer lending, peer-to-peer model, Richard Stallman, ride hailing / ride sharing, Ronald Coase, Ronald Reagan, Satoshi Nakamoto, Search for Extraterrestrial Intelligence, self-driving car, shareholder value, sharing economy, Silicon Valley, six sigma, Skype, smart cities, smart grid, Snapchat, sovereign wealth fund, Steve Crocker, Steve Jobs, Steven Levy, TaskRabbit, The Death and Life of Great American Cities, The Future of Employment, The Nature of the Firm, transaction costs, Turing test, turn-by-turn navigation, Uber and Lyft, Zipcar

Etsy, an online marketplace for makers, is not like a really big craft fair. eBay is different from both classifieds and yard sales. Airbnb is much more than a listing of 1 million bed-and-breakfasts. What distinguishes and transforms these activities is that platforms connect, organize, aggregate, and empower the participating peers. Without the platform—without Airbnb, Etsy, Lyft, TopCoder, or OpenStreetMaps, to name a few—the peer co-creators would not engage, the leveraged excess capacity would be limited, and the consumers of these products and services would not return again and again. Excess capacity turns out to be a key input into a Peers Inc product or service. The cost of experimentation is lowered as new value is extracted out of something that already exists and is already substantially (or entirely) paid for.


pages: 443 words: 98,113

The Corruption of Capitalism: Why Rentiers Thrive and Work Does Not Pay by Guy Standing

3D printing, Airbnb, Albert Einstein, Amazon Mechanical Turk, Asian financial crisis, asset-backed security, bank run, banking crisis, basic income, Ben Bernanke: helicopter money, Bernie Sanders, Big bang: deregulation of the City of London, bilateral investment treaty, Bonfire of the Vanities, Bretton Woods, Capital in the Twenty-First Century by Thomas Piketty, carried interest, cashless society, central bank independence, centre right, Clayton Christensen, collapse of Lehman Brothers, collective bargaining, credit crunch, crony capitalism, crowdsourcing, debt deflation, declining real wages, deindustrialization, Doha Development Round, Donald Trump, Double Irish / Dutch Sandwich, ending welfare as we know it, eurozone crisis, falling living standards, financial deregulation, financial innovation, Firefox, first-past-the-post, future of work, gig economy, Goldman Sachs: Vampire Squid, Growth in a Time of Debt, housing crisis, income inequality, information retrieval, intangible asset, invention of the steam engine, investor state dispute settlement, James Watt: steam engine, job automation, John Maynard Keynes: technological unemployment, labour market flexibility, light touch regulation, Long Term Capital Management, lump of labour, Lyft, manufacturing employment, Mark Zuckerberg, market clearing, Martin Wolf, means of production, mini-job, Mont Pelerin Society, moral hazard, mortgage debt, mortgage tax deduction, Neil Kinnock, non-tariff barriers, North Sea oil, Northern Rock, nudge unit, Occupy movement, offshore financial centre, oil shale / tar sands, open economy, openstreetmap, patent troll, payday loans, peer-to-peer lending, Plutocrats, plutocrats, Ponzi scheme, precariat, quantitative easing, remote working, rent control, rent-seeking, ride hailing / ride sharing, Right to Buy, Robert Gordon, Ronald Coase, Ronald Reagan, savings glut, Second Machine Age, secular stagnation, sharing economy, Silicon Valley, Silicon Valley startup, Simon Kuznets, sovereign wealth fund, Stephen Hawking, Steve Ballmer, structural adjustment programs, TaskRabbit, The Chicago School, The Future of Employment, the payments system, Thomas Malthus, Thorstein Veblen, too big to fail, Uber and Lyft, Uber for X, Y Combinator, zero-sum game, Zipcar

Rentier platforms are also feeding off the erosion of the social commons and commodifying some of its traditional forms. For instance, by offering cheap taxi rides they may reduce the numbers using subsidised public transport and accelerate the loss of public bus services. The real sharing economy is exciting some analysts. Paul Mason sees the emergence of commons-based peer production in the likes of Wikipedia, Linux, OpenStreetMap and Mozilla’s Firefox. In Spain, arts and culture collectives La Tabacalera and Medialab-Prado are prime examples. While these have great potential, they involve a lot of work by unpaid activists and can be pushed out or marginalised by commercial ventures. Many will need state subsidies in order to survive. THE FIFTH LIE OF RENTIER CAPITALISM ‘Everyone can enjoy a life of luxurious leisure if the machine-produced wealth is shared, or most people can end up miserably poor if the machine-owners successfully lobby against wealth redistribution.


pages: 394 words: 110,352

The Art of Community: Building the New Age of Participation by Jono Bacon

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barriers to entry, Benevolent Dictator For Life (BDFL), collaborative editing, crowdsourcing, Debian, en.wikipedia.org, Firefox, game design, Guido van Rossum, Johann Wolfgang von Goethe, Jono Bacon, Mark Shuttleworth, openstreetmap, Richard Stallman, Skype, social software, software as a service, telemarketer, web application

It becomes much deeper, more intrinsic, and more accessible to all. Instead of merely enjoying things together, collaboration PLANNING YOUR COMMUNITY Download at Boykma.Com 35 goes so far as to help people create things together. In these environments, the community also assumes the role of producer of the content. The typical example here is one of the many Free Culture communities, such as Linux, Wikipedia, OpenStreetMap, Creative Commons, etc. In these communities, community members have the opportunity to change the very content that brings them together. The Ubuntu community is one such example. Ubuntu is an entirely free Linux operating system that is designed to provide a complete, free, stable, and secure system for desktops, servers, or mobile devices. Ubuntu is built using hundreds of pieces of preexisting Free Software tools that we refer to as upstream applications.


pages: 933 words: 205,691

Hadoop: The Definitive Guide by Tom White

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Amazon Web Services, bioinformatics, business intelligence, combinatorial explosion, database schema, Debian, domain-specific language, en.wikipedia.org, fault tolerance, full text search, Grace Hopper, information retrieval, Internet Archive, linked data, loose coupling, openstreetmap, recommendation engine, RFID, SETI@home, social graph, web application

Weight each edge (by number of replies, whether it’s symmetric, and so on) and set limits on the number of links from any node. This sharply reduces the intermediate data size, yet still does a reasonable job of estimating cohesiveness. —Philip (flip) Kromer, Infochimps * * * [144] http://infochimps.org/search?query=network [145] http://www.datawrangling.com/wikipedia-page-traffic-statistics-dataset [146] http://www.wormatlas.org/neuronalwiring.html [147] http://www.openstreetmap.org/ [148] All are steady-state network flow problems. A flowing crowd of websurfers wandering the linked-document collection will visit the most interesting pages the most often. The transfer of social capital implied by social network interactions highlights the most central actors within each community. The year-to-year progress of students to higher or lower test scores implies what each school’s effect on a generic class would be


pages: 924 words: 241,081

The Art of Community by Jono Bacon

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barriers to entry, Benevolent Dictator For Life (BDFL), collaborative editing, crowdsourcing, Debian, DevOps, en.wikipedia.org, Firefox, game design, Guido van Rossum, Johann Wolfgang von Goethe, Jono Bacon, Kickstarter, Larry Wall, Mark Shuttleworth, Mark Zuckerberg, openstreetmap, Richard Stallman, side project, Silicon Valley, Skype, slashdot, social graph, software as a service, telemarketer, union organizing, VA Linux, web application

Write-centered communities For some communities, collaboration goes much further. It becomes much deeper, more intrinsic, and more accessible to all. Instead of merely enjoying things together, collaboration goes so far as to help people create things together. In these environments, the community also assumes the role of producer of the content. The typical example here is one of the many Free Culture communities, such as Linux, Wikipedia, OpenStreetMap, Creative Commons, and so on. In these communities, community members have the opportunity to change the very content that brings them together. The Ubuntu community is one such example. Ubuntu is an entirely free Linux operating system that is designed to provide a complete, free, stable, and secure system for desktops, servers, or mobile devices. Ubuntu is built using hundreds of pieces of preexisting Free Software tools that we refer to as upstream applications.