This document describes using open source tools like OpenStreetMap, Mapnik, and OpenLayers to create an interactive online atlas for visualizing and analyzing higher education and related government spatial data in the UK. The atlas allows non-technical users to view metrics like school performance and socio-economic indicators in an accessible and self-contained web application without any software installation. The tools were chosen to meet requirements of being straightforward, accessible without plugins, and fully controlled without dependencies on external parties. The atlas was created by generating map tiles from OpenStreetMap and other data with Mapnik and displaying them interactively with OpenLayers.
SDSC Technology Forum: Increasing the Impact of High Resolution Topography Da...OpenTopography Facility
High-resolution topography is a powerful tool for studying the Earth's surface, vegetation, and urban landscapes, with broad scientific, engineering, and educational-based applications. Over the past decade, there has been dramatic growth in the acquisition of these data for scientific, environmental, engineering and planning purposes. In the US, the U.S. Geological Society is undertaking the 3D Elevation Program (3DEP) to map the entire lower 48 with lidar by 2023.
The richness of these topography datasets make them extremely valuable beyond the application that drove their acquisition and thus are of interest to a large and varied user community. A cyberinfrastructure platform that enables users to efficiently discover, access and process these massive volumes of data increases the impact of investments in collection of the data and catalyzes scientific discovery as well as informs critical decisions that are made across our Nation every day that depend on elevation data, ranging from immediate safety of life, property, and environment to long term planning for infrastructure projects.
Join us to hear about the motivations, technology, and data assets behind the National Science Foundation funded OpenTopography platform, which aims to democratize access to high resolution topographic data. OpenTopography’s innovation is in co-locating massive volumes of topographic data with processing tools that enable users with varied expertise and application domains to quickly and easily access and process data, to enable innovation and decision making.
Learn how to get started making Leaflet maps through R statistical software. Sounds crazy? Maybe. But the R package leafletR allows people familiar with R, but maybe not so much with HTML and Javascript coding, to make a basic Leaflet map (interactive, slipping web map) quickly with minimal knowledge of other programming languages.
Example code posted here: https://github.com/MicheleTobias/RCode
Presented at the 46th Society of Cartographers Summer School in Manchester on September 10 2010. The abstract for the talk was as follows: "OpenStreetMap is coming of age, but as it starts to be used more in the mainstream, the age-old questions of quality and completeness are coming to the fore. A range of data sources have been used to build up the map in the UK, from GPS traces to aerial imagery, historic mapping, NaPTAN and the OS Open Data release, each with their own benefits and limitations. This talk looks at a number of studies and tools developed to quantify, compare and address accuracy and coverage of the project in the UK, in an attempt to answer the key questions - is it complete yet and just how good is it?"
Using R to Visualize Spatial Data: R as GIS - Guy LansleyGuy Lansley
This talk demonstrates some of the benefits of using R to visualize spatial data efficiently and clearly.
It was originally presented by Guy Lansley (UCL and the Consumer Data Research Centre) to the GIS for Social Data and Crisis Mapping Workshop at the University of Kent.
40 min presentation to the Map Curators Workshop 2013 held in Hothorpe Hall. The presentation looks at how EDINA has used the knowledge fro running web based mapping services for 15 years to develop a new mobile mapping app. The focus is on "knowing your users" and ensuring that you fulfill their needs.
This is the presentation of the project we did as a part of our final year project. We have developed a utility management system for a housing company using web GIS. Please feel free to contact in case of any queries.
SDSC Technology Forum: Increasing the Impact of High Resolution Topography Da...OpenTopography Facility
High-resolution topography is a powerful tool for studying the Earth's surface, vegetation, and urban landscapes, with broad scientific, engineering, and educational-based applications. Over the past decade, there has been dramatic growth in the acquisition of these data for scientific, environmental, engineering and planning purposes. In the US, the U.S. Geological Society is undertaking the 3D Elevation Program (3DEP) to map the entire lower 48 with lidar by 2023.
The richness of these topography datasets make them extremely valuable beyond the application that drove their acquisition and thus are of interest to a large and varied user community. A cyberinfrastructure platform that enables users to efficiently discover, access and process these massive volumes of data increases the impact of investments in collection of the data and catalyzes scientific discovery as well as informs critical decisions that are made across our Nation every day that depend on elevation data, ranging from immediate safety of life, property, and environment to long term planning for infrastructure projects.
Join us to hear about the motivations, technology, and data assets behind the National Science Foundation funded OpenTopography platform, which aims to democratize access to high resolution topographic data. OpenTopography’s innovation is in co-locating massive volumes of topographic data with processing tools that enable users with varied expertise and application domains to quickly and easily access and process data, to enable innovation and decision making.
Learn how to get started making Leaflet maps through R statistical software. Sounds crazy? Maybe. But the R package leafletR allows people familiar with R, but maybe not so much with HTML and Javascript coding, to make a basic Leaflet map (interactive, slipping web map) quickly with minimal knowledge of other programming languages.
Example code posted here: https://github.com/MicheleTobias/RCode
Presented at the 46th Society of Cartographers Summer School in Manchester on September 10 2010. The abstract for the talk was as follows: "OpenStreetMap is coming of age, but as it starts to be used more in the mainstream, the age-old questions of quality and completeness are coming to the fore. A range of data sources have been used to build up the map in the UK, from GPS traces to aerial imagery, historic mapping, NaPTAN and the OS Open Data release, each with their own benefits and limitations. This talk looks at a number of studies and tools developed to quantify, compare and address accuracy and coverage of the project in the UK, in an attempt to answer the key questions - is it complete yet and just how good is it?"
Using R to Visualize Spatial Data: R as GIS - Guy LansleyGuy Lansley
This talk demonstrates some of the benefits of using R to visualize spatial data efficiently and clearly.
It was originally presented by Guy Lansley (UCL and the Consumer Data Research Centre) to the GIS for Social Data and Crisis Mapping Workshop at the University of Kent.
40 min presentation to the Map Curators Workshop 2013 held in Hothorpe Hall. The presentation looks at how EDINA has used the knowledge fro running web based mapping services for 15 years to develop a new mobile mapping app. The focus is on "knowing your users" and ensuring that you fulfill their needs.
This is the presentation of the project we did as a part of our final year project. We have developed a utility management system for a housing company using web GIS. Please feel free to contact in case of any queries.
Field Data Collecting, Processing and Sharing: Using web Service TechnologiesNiroshan Sanjaya
Collecting, Distributing and Analyzing field data is a crucial part in any geospatial study. Field data collection tools and methods have been developed significantly due to the advancement of technologies such as Global Navigational Satellite Systems (GNSS) and development of smartphones. Accurate field data collection is also a necessary task for broad spatial data analysis and proper decision making. Development of Web technologies led to share the data and information effectively. This study tries to develop a framework based on the Geospatial Semantic Web technologies for disseminating and processing field data. Experimental results from an implemented prototype show that the proposed framework allows to visualize and process the field data in any context. The system of this study is capable of distributing and processing field data using web application. Moreover, the study demonstrates the importance and the capabilities of web services for spatial data gathering and processing. The system has been developed based on Free and Open Source Software (FOSS) packages such as ZOO-Project, Open Data Kit, etc. It enables user to further improve or deploy the system for variety of studies.
Visualising large spatial databases and Building bespoke geodemographicsDr Muhammad Adnan
This presentation outlines my work at the Local Futures and the PhD research. I have been working on a combined project between Local Futures and UCL and the presentation starts by giving an introduction of the project. My PhD investigated the creation of Real-time bespoke geodemographics, and this presentation presents the work i did during the PhD journey.
From 2D Drawings to 3D Navigation networks built with FMESafe Software
This presentation will provide an example of how 2D floorplan drawings can be augmented to generate 3D networks inside buildings. Specifics of the techniques for constructing the network and demonstration of the results will be provided.
Large-Scale Geographically Weighted Regression on SparkViet-Trung TRAN
Geographically Weighted Regression (GWR) is a local version of spatial regression that captures spatial dependency in regression analysis. GWR has many application in practice as a visualization and prediction tool for spatial exploration- (e.g in climate, economy, medical). However, this locally regression model is slow in process upon the volume of calculations and the spatial getting bigger. Improving performance of GWR is an critical issue, but their distributed implementations have not been studied. Recently, with the advent of Spark as well MapReduce framework, the development of machine learning applications and parallel programming becomes easier. In this article, we propose several large-scale implementations of distributed GWR, leveraging Spark framework. We implemented and evaluated these approaches with large datasets. To our best knowledge, this is the first work addressing GWR at large-scale.
Google Earth Web Service as a Support for GIS Mapping in Geospatial Research ...Universität Salzburg
The geospatial work has been performed using combination of the Google Earth imagery, Landsat TM images and Erdas Imagine GIS software. The advantage of utilizing Google Earth scenes with Landsat TM satellite imagery, along with GIS techniques and methods, for inventorying land cover types has been demonstrated for landscape studies. Combination of land cover type characteristics and landscape changes enabled to analyse landscape dynamics, as well as applicability of Google Earth service for thematic mapping. The used data included Landsat TM and ETM+ multi-band imagery covering area in Izmir, western Turkey. The image processing was per- formed using supervised classification in Erdas Imagine software. The Google Earth web service technologies were applied to test the accuracy of mapping via the available module of Erdas Imagine «Linking with Google Earth».
Field Data Collecting, Processing and Sharing: Using web Service TechnologiesNiroshan Sanjaya
Collecting, Distributing and Analyzing field data is a crucial part in any geospatial study. Field data collection tools and methods have been developed significantly due to the advancement of technologies such as Global Navigational Satellite Systems (GNSS) and development of smartphones. Accurate field data collection is also a necessary task for broad spatial data analysis and proper decision making. Development of Web technologies led to share the data and information effectively. This study tries to develop a framework based on the Geospatial Semantic Web technologies for disseminating and processing field data. Experimental results from an implemented prototype show that the proposed framework allows to visualize and process the field data in any context. The system of this study is capable of distributing and processing field data using web application. Moreover, the study demonstrates the importance and the capabilities of web services for spatial data gathering and processing. The system has been developed based on Free and Open Source Software (FOSS) packages such as ZOO-Project, Open Data Kit, etc. It enables user to further improve or deploy the system for variety of studies.
Visualising large spatial databases and Building bespoke geodemographicsDr Muhammad Adnan
This presentation outlines my work at the Local Futures and the PhD research. I have been working on a combined project between Local Futures and UCL and the presentation starts by giving an introduction of the project. My PhD investigated the creation of Real-time bespoke geodemographics, and this presentation presents the work i did during the PhD journey.
From 2D Drawings to 3D Navigation networks built with FMESafe Software
This presentation will provide an example of how 2D floorplan drawings can be augmented to generate 3D networks inside buildings. Specifics of the techniques for constructing the network and demonstration of the results will be provided.
Large-Scale Geographically Weighted Regression on SparkViet-Trung TRAN
Geographically Weighted Regression (GWR) is a local version of spatial regression that captures spatial dependency in regression analysis. GWR has many application in practice as a visualization and prediction tool for spatial exploration- (e.g in climate, economy, medical). However, this locally regression model is slow in process upon the volume of calculations and the spatial getting bigger. Improving performance of GWR is an critical issue, but their distributed implementations have not been studied. Recently, with the advent of Spark as well MapReduce framework, the development of machine learning applications and parallel programming becomes easier. In this article, we propose several large-scale implementations of distributed GWR, leveraging Spark framework. We implemented and evaluated these approaches with large datasets. To our best knowledge, this is the first work addressing GWR at large-scale.
Google Earth Web Service as a Support for GIS Mapping in Geospatial Research ...Universität Salzburg
The geospatial work has been performed using combination of the Google Earth imagery, Landsat TM images and Erdas Imagine GIS software. The advantage of utilizing Google Earth scenes with Landsat TM satellite imagery, along with GIS techniques and methods, for inventorying land cover types has been demonstrated for landscape studies. Combination of land cover type characteristics and landscape changes enabled to analyse landscape dynamics, as well as applicability of Google Earth service for thematic mapping. The used data included Landsat TM and ETM+ multi-band imagery covering area in Izmir, western Turkey. The image processing was per- formed using supervised classification in Erdas Imagine software. The Google Earth web service technologies were applied to test the accuracy of mapping via the available module of Erdas Imagine «Linking with Google Earth».
EDINA runs Geo-services for the education sector in the UK, but did you know that many of it's services are open and available to use by anyone, anywhere? Learn more about Open data, maps and tools that EDINA have made available.
Volunteered Geographic Information and OpenStreetMapchippy
Short introduction to the subject of Volunteered Geographic Information and outlining some of the characteristics, issues themes of VGI
and then a comprehensive talk about the OpenStreetMap Project.
By Tim Waters, at AGI Northern Group (SIG), April 2009, Manchester University
Open Data Portals: 9 Solutions and How they CompareSafe Software
Get a comparison of CKAN, Socrata, ArcGIS Open Data and other top open data solutions. Plus get answers to best practice questions such as: Which datasets are important to share? What are the approximate costs? Which file formats should the data be shared in? How often should the data get updated? And overall, how can we ensure success with our open data portal?
In 2017 I gave a lunchtime Webinar presentation on the opensource mapping solution OpenStreetMap which is rapidly growing in terms of coverage, detail and re-usability.
OpenStreetMap and CycleStreets: collaborative map-making and cartography in t...CycleStreets
Abstract: The arrival of web-based mapping from Google and others has revolutionised, in the space of only five years, the way many people interact with maps and map data. And the success of projects such as Wikipedia highlight how collation of small amounts of information from large numbers of people - an approach called 'crowdsourcing' - can challenge traditional models of data collection and ownership. Bringing these concepts together is OpenStreetMap, a collaborative project to create a free editable map of the world. Well-established enterprises such as the Ordnance Survey are coming under increased pressure from this new model, and large companies such as MapQuest and Microsoft are starting to use and invest in it. Martin Lucas-Smith, Webmaster in the Department, and one of two main developers of the leading UK-wide cycle journey planner website, CycleStreets, will discuss OpenStreetMap, its use within a wide range of systems (from cartography, routing, and even its central role helping deal with the Haiti disaster) and discuss the challenges it poses to traditional forms of cartography and data collection.
Experiences as a producer, consumer and observer of open dataProgCity
Peter Mooney, is an Environmental Protection Agency (EPA) funded Research Fellow at the Department of Computer Science, NUI Maynooth. He has been working with the EPA on making environmental data publicly accessibly for the last ten years.
Presentation was part of The 1st Seminar of the ERC Funded Programmable City Project based at NIRSA, NUI Maynooth, Republic of Ireland.
Poster: Enhancing and Educating with the WxSat Mobile AppKyle Nelson
Poster presented at the Federation of Earth Science Information Partners' (ESIP) 2015 Winter Meeting. Development of educational products and enhancements to the WxSat Mobile App were funded through an ESIP Student Fellow research grant.
Slides of my PhD presentation @ Eurecom, presenting our work on publishing and consuming geo-spatial data and government data using Semantic Web technologies.
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Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
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Delivering Micro-Credentials in Technical and Vocational Education and TrainingAG2 Design
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For more detailed information on delivering micro-credentials in TVET, visit this https://tvettrainer.com/delivering-micro-credentials-in-tvet/
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
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The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
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Higher Education Profiling using Open Source GIS - A Primer on OpenStreetMap Data, Mapnik & OpenLayers
1. Higher Education Profiling using Open Source GISA Primer on OpenStreetMap Data, Mapnik & OpenLayers Oliver O’Brien & Alex Singleton Department of Geography University College London
2. Contents The Problem Requirements The Solution OpenStreetMap Data Mapnik OpenLayers Data Sources Putting it all Together The Completed Atlas
3. The Problem: Presenting the Data A large amount of education-related spatial information available from various governmental bodies but not in a readily accessible graphical form (i.e. maps) for non-technical users. Dept. for Schools, Children and Families Communities and Local Government Higher Education Funding Council for England Higher Education Statistics Agency Office for National Statistics “Widening participation” initiatives require effective ways to view such data, to make decisions on target schools and areas.
4. Requirements I. Straightforward Standalone GISes Hard to use (Haklay, 2009a) Often expensive Require delivery of data to the client
5. Requirements I. Straightforward Web GISes Slow Unattractive Difficult and/or expensive to build May require delivery of vector data to the client
7. Requirements II. Accessible Software installation Requires time and skill Constrained by platform Plug-ins Generally require a fast computer Still some platform issues A solution without installation or plug-ins is most accessible HTML, CSS, AJAX PNG images
8. Requirements III. Self Contained No dependencies on third parties with constraints Ordnance Survey “tile limits” The “derived data” problem, Google and Ordnance Survey Can’t put Ordnance Survey derived data on a Google Maps “mashup” Government departments often provide data that has been geolocated from Ordnance Survey mapping (e.g. using National Grid References) Ordnance Survey is being very active at protecting use of its data at the moment
9. Requirements III. Self Contained Full control over what’s on the map Google’s colour scheme and branding can be distracting
10. The Solution: An Education Atlas Static tiles of choropleth maps Minimal computer requirements Scalable Mapnik Makes “beautiful” raster maps OpenStreetMap data Easily available data source to create background maps Full control over what is included OpenLayers Provides the “slippy map” interface familiar to users Self-contained
11. Using OpenStreetMap Data For a background map to provide context Will include roads, town names, coastlines We don’t want all the data – just what we need Ways to obtain the data Directly from osm.org as XML, requires converting Shapefiles produced by CloudMade or Geofabrik Data quality and completeness Improving rapidly (Haklay, 2009b) Now pretty good for England (Reed, 2009) Can always obtain a very up-to-date dataset www.openstreetmap.org
12. Using Mapnik “Mapnik is a Free Toolkit for developing mapping applications. Above all Mapnik is about making beautiful maps.” – mapnik.org Data Sources Shapefiles PostGIS databases Direct from OpenStreetMap Tiles Can be configured to systemically create square tiles at different zoom levels for the whole country www.mapnik.org
13. Using Mapnik Stylesheets for the cartography e.g. minor rivers and canals <Rule> <Filter>[waterway]='river' or [waterway]='canal'</Filter> <MaxScaleDenominator>80000 </MaxScaleDenominator> <LineSymbolizer> <CssParameter name="stroke">#88c <CssParameter name="stroke-width">3 <CssParameter name="stroke-linejoin”>round <CssParameter name="stroke-linecap">round </LineSymbolizer> <TextSymbolizername="name" face_name="DejaVu Sans Book" size="10" fill="#666" halo_radius="1" placement="line" min_distance="200"/> </Rule>
14. Using OpenLayers A way to display maps on a website Just a simple web browser is needed Accepts “layers” from many sources Google Maps Microsoft Bing, Virtual Earth, Yahoo ArcGIS 9.3 Mapping Services Ordnance Survey OpenSpace More powerful (but more complex) than the popular Google Maps API www.openlayers.org
15. Other Data Sources New Popular Edition Postcoding Government Data Combined with UKBORDERS boundary data, to create choropleths of each educational metric Includes the National Pupil Database with postcode, for Key Stage 4 (GCSE) and Key Stage 5 (A-Level)
16. Putting it all Together: Tile Generation OpenStreetMap API Stylesheet Geofabrik Shapefiles Mapnik PostGIS Database Other .gov.uk Tiles Shapefiles UKBORDERS mySQL Database DSCF.gov.uk
17. Putting it all Together: The Website Web Browsers OpenLayers Tiles mySQL Database The layers in OpenLayers Top: Schools (pins) Middle: Network (B&W) NPEMap Postcodes Bottom: Choropleth (colours)
DCSF – attainment. CLG – IDACI. HEFCE – POLAR. HESA – school-to-university flows. ONS - for census information, from which are derived the Output Area Classifications. Widening participation is also known as Access to Higher Education.
Using ArcGIS as an example here as it is the dominant GIS application, however there are numerous other such as MapInfo, GRASS, Quantum GIS. Some are easier to use, some harder, but almost all require skills beyond that of the average web browser.
Slow – on-the-fly vector display, so slow on the client, or on-the-flyrasterisation, so slow on the server.Unattractive – produced by a GIS rather than a cartographical application, so generally no anti-aliasing or generalisation techniques applied.Difficult/expensive to build – May require delivery of vector data – licensing issues, as the client has a “digital copy” of the vector data, rather than a degraded raster.
Because they are popular, users don’t need “special skills”
Flash is popular, but not available on the iPhone.
If data supplied includes only National Grid References and not latitude/longitude, there is a good chance that it has been derived from Ordnance Survey data. Therefore, in theory, placing that data on a Google Map “mashup” would allow Google ownership of that data, which Ordnance Survey forbids.Ordnance Survey sent a letter to all district councils in the UK recently, advising them of the derived data problem.
Note the added “Parks” symbols roughly correspond to some (but not all) of Google’s own “Tree” symbol for public parks. It would be better if we could choose not to show Google’s own one. Also, you are stuck with Google’s colour scheme – here, the green is different to the green of the main website.
OS OpenSpace have built their own version of OpenLayers, which can be used to display Ordnance Survey mapping imagery. However you cannot directly use the OpenSpace maps in a standalone version of OpenLayers.
OS OpenSpace have built their own version of OpenLayers, which can be used to display Ordnance Survey mapping imagery. However you cannot directly use the OpenSpace maps in a standalone version of OpenLayers.
The data sources are on the left. The intermediate systems are in the middle. The systems used in the final map are in the box on the right.