Posts Tagged ‘free’

  • Data.gov – Also an Geospatial Datasource.

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    It is hard to compare American datasources with European ones, because of the different legal pre-conditions. In the USA all data produced with public resources such as taxes have to be available to the public without additional costs for usage. Most counties in the European Union (EU) follow an different strategy, where geospatial data have to be purchased. This is one point why for example the Inspire initiative and Data.gov can hardly be compared.

    datagov

    According to data.gov the platform was established with following reason:

    The purpose of Data.gov is to increase public access to high value, machine readable datasets generated by the Executive Branch of the Federal Government. Although the initial launch of Data.gov provides a limited portion of the rich variety of Federal datasets presently available, we invite you to actively participate in shaping the future of Data.gov by suggesting additional datasets and site enhancements to provide seamless access and use of your Federal data. Visit today with us, but come back often. With your help, Data.gov will continue to grow and change in the weeks, months, and years ahead.
    The platform provides different tools to search for data. One way is to use a searchable data catalog that includes access to raw data, but you can also use your applications to connect to this catalog. If in your opinion important datasets are missing you can suggest more datasets. The usage of the platfom is described in a tutorial.
    RAW data is available in XML, KML, CSV/TXT, ESRI formats or as maps and others.
    [via data.gov]
  • Cloudmade – An alternative Javascript mapping API

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    CloudMade was founded by Steve Coast and Nick Black in 2007 to provide services around open mapdata. Steve Coast is also the founder of OpenStreetMap (OSM), one of the most prominent source for free map data based on the wiki idea. Therefore there is a strong relationship between OpenStreetMap and CloudMade, with the aim to “continue the democratization of geo data and to expand access to open geo data through a range of simple yet powerful tools and APIs.

    The current version of their APIs allows developers to integrate OpenStreetMap data into mobile and web-based applications. The major differences between most of similar services (beginning with Google Maps API), the CloudMade team highlights to be free from restrictive licencing.

    Currently their APIs are closed pre-Alpha and is only available to registered users. To take part on this program you can sign up. They follow a bottom up approach and try to reduce complexity in terms to use geographical tools.

    [via CloudMade]

  • Writing KML from my C# Application

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    geKML is a project allowing to generate KML/KMZ documents from a C#.NET application.  geKML consists of .NET classes that will generate a properly formatted KML document that the Google Earth and Google Maps application can understand.  The purpose of these objects are to help the developer to easily construct their desired KML document hierarchy.  These objects will not help the developer decide what hierarchy is best for their application.  Unfortunately you’ll will still need to know how to structure your KML. geKML is hosted on SourceForge and is available for free.

    How you can getting started

    (original excerpt form the homepage)

    The most important class you’ll need to use every time, is the geKML class.  This class will be the one responsible for writing the proper KML header information, and it will also kick off the generation of the rest of the KML objects.

    To instantiate the geKML object, you will first need to decide what your “root” KML object will be.  It can be any object that Google Earth will recognize as a root object.  Popular choices are the Feature classes (NetworkLink, Placemark, ScreenOverlay, GroundOverlay, Folder, Document).  For simplicity sake, I recommend starting with the geDocument or geFolder object.

    Since most of the Google Earth classes are optional, you’ll have to instantiate most of these objects as you want to use them and then add them to any properties or collections.

    Once you have added all of the objects into your geKML.kmlRoot property, you will want to call the geKML.ToKML() method which will return a properly formatted KML byte array, which you can then save to a file or stream from a web server.

    Below is a simple example of a basic document (root) and a placemark that exists within that document.  For simplicity sake this example uses hard coded values for properties, but in practice you will probably use values from some dynamic data source.

    Welcome to the Google Earth KML API .NET 2.0 Website.  This website will host the official current documentation for the ge-kml project that is hosted on SourceForge.net.  Text versions of the documentation will also be hosted there, but due to scripting and formatting limitations I have chosen to host the official documentation here.  All menu items other than “Home” will take you to the project on SourceForge.

    Click on the image to see the class diagramm in full size.

    One simple Example from the Homepage:

    using System; using System.Collections.Generic; using System.Text; using System.IO; using Google.KML; namespace Examples { public static class Example1{ public static void RunExample(string FileName) { // Use a Document as the root of the KML geDocument doc = new geDocument();  doc.Name = "My Root Document"; //Create a Placemark to put in the document //This placemark is going to be a point //but it could be anything in the Geometry class gePlacemark pm = new gePlacemark(); //Create some coordinates for the point at which //this placemark will sit. (Lat / Lon) geCoordinates coords = new geCoordinates(new geAngle90(37.422067), new geAngle180(-122.084437)); //Create a point with these new coordinates gePoint point = new gePoint(coords); //Assign the point to the Geometry property of the placemark. pm.Geometry = point; //Now lets add some other properties to our placemark pm.Name = "My Placemark"; pm.Snippet = "This is where I put my Placemark"; pm.Description = "I wonder where this is..."; //Finally, add the placemark to the document doc.Features.Add(pm); //Now that we have our document, lets create our KML geKML kml = new geKML(doc); //And our results... File.WriteAllBytes(FileName, kml.ToKML()); } } }

    [via: http://gekml.boseefus.com/]

    Written and submitted from Home, using my 802.11g WiFi network.

  • Free Addressdata for Austria

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    An open and downloadable address dataset is useful for many geospatial applications. Therefore the Fachhochschule Nordwestschweiz has developed a platform where users can enter own addresses for benefit of the whole community. Recently FH Kärnten has adopted this idea to create a address dataset for Austria. Until now less than 100 addresses are stored but this could change soon. You can add addresses at the homepage of the portal: http://www.openaddresses.at

    Since Google provides a very sophisticated geocoding function including most of the addresses in Austria the success of this project is questionable. One advantage of OpenAdresses is the possibility to download the dataset as CSV or XML. We will see how big the growth of will be.

    The Idea:

    In the last few years web applications have integrated users more and more in the design, the processing and gathering of information.
    Some of the these applicatins are Wikis and famous sites such as youtube, etc.
    We had the idea at our institute of launching an experiment to collect a complete set of geocoded address information for Switzerland. This data is supposed to

    • be freely available to all interested companies or private persons and may be used at no license fee
    • be captured and maintained by the Web Community
    • store not only the details of an address but their co-ordinates as well.

    Of course there is already a complete geocoded address dataset for the whole of Switzerland – but it is fairly expensive. With the OpenAddress idea we want
    to investigate whether it is possible to create such an comprehensive dataset based both on the most recent technologies and the Web Community.
    We believe that the more people there are who join in, the less the effort of each individual will be. If many, many people help with their very local know-how, we will be able to achieve this goal.
    Besides: it is very easy: just click on the map and enter the details of an address – that’s it. Or use a list of addresses and go sequentially through it.

    Of course we would like the individual to collect and enter more than just one address:
    This could be: Addresses of the places where you work, you live, meet your friends, have your hair cut or your teeth checked, the most famous restaurant, as well as the most famous restaurant and other popular locations etc.

    A few comments:

    • Whoever needs many addresses should collect and enter many. This is especially meant for companies who will use this data in a commercial environment.
    • The project is based on trust: We neither check nor log what is collected and entered.
    • The project is based on the “open” philosophy which also works in the area of open source software: the community is responsible for quality and completeness.
    • Do invite colleagues to join in and help – the more the better!
    • Keep informed and use the ’statistics’ option to follow the progress.

    As stated before: it is an experiment. But we believe it will work – with your help!

    What will this address information be used for?
    Many applications and solutions in the area of geographic context need highly detailed data. Full address data including georeference is part of it.

    [via: http://www.openaddresses.at]

    Written and submitted from Home, using my 802.11g WiFi network.

  • Free online GIS Book

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    The book “Geospatial Analysis” can freelay be accessed online. This book should be a comprehensive independent guide to principles, techniques and software tools as stated at the online. The authors, de Smith, Goodchild and Longley, are quite prominet.

    Topics covered include:

    Principal concepts of geospatial analysis, their origins and methodological context
    Core components of geospatial analysis, including distance and directional analysis, geometrical processing, map algebra, and grid models
    Exploratory spatial data analysis (ESDA) and spatial statistics, including spatial autocorrelation and spatial regression
    Surface analysis, including surface form analysis, gridding and interpolation methods
    Network and locational analysis, including shortest path calculation, travelling salesman problems, facility location and arc routing
    Geocomputational methods, including agent-based modelling, artifical neural networks and evolutionary computing.

    View the whole Book online!

    Written and submitted from Home, using my 802.11g WiFi network.

  • Openstreetmap is growing

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    The OpenStreetMap project is growing. The project can be compared with wikipadia. OpenStreetMap is a free editable map of the whole world. It is made by people like you. OpenStreetMap allows you to view, edit and use geographical data in a collaborative way from anywhere on Earth.

    OpenStreetMap is a project aimed squarely at creating and providing free geographic data such as street maps to anyone who wants them. The project was started because most maps you think of as free actually have legal or technical restrictions on their use, holding back people from using them in creative, productive or unexpected ways.

    Contributors to OpenStreetMap take handheld GPS devices with them on journeys, or go out specially to record GPS tracks. They record street names, village names and other features using notebooks, digital cameras, and voice-recorders.

    Back at the computer, contributors upload those GPS logs showing where they travelled, and trace-out the roads on OpenStreetMap’s collaborative database. Using their notes, contributors add the street names, information such as the type of road or path, and the connections between roads.

    That data is then processed to produce detailed street-level maps, which can be published freely on sites such as Wikipedia, used to create handheld or in-car navigation devices, or printed and copied without restriction.

    munich_0608to0709b_small.gif

    This Animation showing the development of OSM in the area Munich, the capital of Bavaria, Germany. Time shown: August 2006 until September 2007. This animation is also shown at the German page on Munich.

    » Read the rest of the entry..

  • GeoNames – A Free GeoWebservice

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    GeoNames is a geographical data base freely available and accessible through various Web services, under a Creative Commons attribution license.

    The GeoNames database contains over 8,000,000 geographical names corresponding to over 6,500,000 unique features. All features are categorized into one out of nine feature classes and further subcategorized into one out of 645 feature codes. Beyond names of places in various languages, data stored include latitude, longitude, elevation, population, administrative subdivision and postal codes. All coordinates use the WGS84 system (World Geodetic System 1984). Those data are accessible free of charge through a number of Web services and a daily database export. The Web services include direct and reverse geocoding, finding places through postal codes, finding places next to a given place, and finding Wikipedia articles about neighbouring places.

    Each GeoNames feature is represented as a Web resource identified by a stable URI. This URI provides access, through content negotiation, either to the HTML wiki page, or to a RDF description of the feature, using elements of the GeoNames ontology. This ontology describes the GeoNames features properties using the Web Ontology Language, the feature classes and codes being described in the SKOS language. Through Wikipedia articles URL linked in the RDF descriptions, GeoNames data are linked to DBpedia data and other RDF Linked Data.

    500px-geonamesdensity.png

    Desnsity Feature map. Bright areas indicates a high feature density for GeoNames. Dense regions are Bosnia Herzegowina (1.008 features per km²) , Germany (0.447), North Korea (0.318), Pakistan (0.154) and the east coast of the US.

    [www.geonames.org]

    Written and submitted from Home, using my 802.11g WiFi network.