”Hide and Tweet”: A game to teach schoolchildren about spatial technologies

As part of the Geotechnology research team at NUI Maynooth we were involved in the preparation and running of various activities in the Summer School on Computer Science for school children aged between 12 to 18 years old. Since year 2009 we have been constantly developing, testing, and deploying some geospatial software applications which were used by the children for activities in the summer school programme. The high level goal of this development was to help school children become more familiar GPS devices and computerbased Location-based services (LBS) technologies which are now playing such a crucial role in today’s Internet connected society. The software applications were used as part of games and tasks for the children. In our paper we shall describe how these games have evolve during these years, the educational aspects and benefits of the game and how both the software components and devices were developed. Overall, children participating in the summerschool provided their comments in the form of a survey. They felt that there were now more aware about possibilities in geoinformatics available with “ordinary off the shelf devices”. Different issues related with webbased maps (Google Maps, OpenStreetMap, Bing Maps, etc) were introduced and we explained the differences between them. Most importantly in case of geo-technologies we felt that the activities helped the children become aware that that computing and positioning happens everywhere and is not tied with the desk and the desktop computer.We summarise our experiences gained in these last three years and discuss the educational gains of this type of game-based approach to location-based technologies to schoolchildren. All of our software is developed using free and open-source components meaning that it can be deployed by any school or educational facility with minimum cost. A smartphone-based version of the software has also been developed

OpenStreetMap standalone server as a core of system for environmental data publication for wide public in Ireland

In this paper is possible to find info about system developed by EPA Environmental Protection Agency and NUI3 Maynooth for presenting environmental data collected by EPA in graphical easy to understanding for wide audience form, with focus on showing them especially on simple mobile devices like most basic telephones with Java Mobile edition on board

Comparison of the accuracy of OpenStreetMap for Ireland with Google Maps and Bing Maps

We describe a comparison of the accuracy of OpenStreetMap for Ireland with Google Maps and Bing Maps. Five case study cities and towns are chosen for this comparison. Each mapping system is analysed for accuracy under three main headings: spatial coverage, currency, and ground-truth positional accuracy. We find that while there is no clear winner amongst the three mapping platforms each show individual differences and similarities for each of the case study locations. We believe the results described in this paper are useful for those developing Location-based services for countries such as Ireland where access to high-quality geospatial data is often prohibitively expensive or made difficult by other barriers such as lack of data or access restrictions

Development of a server to manage a customised local version of OpenStreetMap in Ireland

In this paper we describe the software architecture of a prototype web-based GIS system for the deliver environmental research data in Ireland. The central component in this system is OpenStreetMap which provides the base layers of geographical data. An OpenStreetMap data collection campaign for our university town was carried out earlier this year yieldeding a spatially rich OpenStreetMap representation of Maynooth. Our server (OpenStreetMap database, supporting software, and specially generated map tiles) has been used by several GIS and location-based services projects in our department. One such example is a mobile device-based pedestrian navigation system is described in this paper. We describe some of the components of our server system. This includes a description of the management of the local copy of the OpenStreetMap database and the generation of sets of customised map tiles

Sketches of Generic Framework for Quality Assessment of Volunteered Geographical Data

The history of volunteered geographical information movement dosn’t have such a long tradition. As was mentioned by [1] Kounadi (2009) in her thesis, a whole movement emerged when Google map API was hacked and the first crowd sourcing services like HousingMaps.com and Adrian Holovaty’s Chicago Crime3 emerged. In general, the whole movement is based as marked by [2] Goodchild (2007) "human is able to act as an intelligent sensor, perhaps equipped with such simple aids as GPS or even the means of taking measurements of environmental variables". Amateur enthusiast start to be cartographers but the difference is that they don’t have much knowledge about the many aspects of map making. Some authors [3] Coleman et al. (2009) even argue that these contributors can be organized in groups from "Neophyte" to "Expert Authority". Everyone can contribute to the Neogeography field but not everyone contributes data of the same quality. The reason for that is a lack of practice and knowledge which can be improved by practice and experience in map making, amazing to see the citation from [4] Andrew et al. (2009) "How such technologies and tools evolve, is not only dependent on advances in technology itself but also the users of such technology". What is interesting when we look generally at an example of OpenStreetMap which is probably now the best and biggest service of volunteered geographical information system in use today but not the only one. If we talk about contributors from my own experience, I have found that knowledge about mapping practices and conventions is spread between people, from the most influential to complete beginners, by good advice and imitation. We, as researchers are interested how this evolution of quality in data my affect a final product map in a system like OpenStreetMap and we are curious if there will be some way for automatic assessment

Sketches of Generic Framework for Quality Assessment of Volunteered Geographical Data

The history of volunteered geographical information movement dosn’t have such a long tradition. As was mentioned by [1] Kounadi (2009) in her thesis, a whole movement emerged when Google map API was hacked and the first crowd sourcing services like HousingMaps.com and Adrian Holovaty’s Chicago Crime3 emerged. In general, the whole movement is based as marked by [2] Goodchild (2007) "human is able to act as an intelligent sensor, perhaps equipped with such simple aids as GPS or even the means of taking measurements of environmental variables". Amateur enthusiast start to be cartographers but the difference is that they don’t have much knowledge about the many aspects of map making. Some authors [3] Coleman et al. (2009) even argue that these contributors can be organized in groups from "Neophyte" to "Expert Authority". Everyone can contribute to the Neogeography field but not everyone contributes data of the same quality. The reason for that is a lack of practice and knowledge which can be improved by practice and experience in map making, amazing to see the citation from [4] Andrew et al. (2009) "How such technologies and tools evolve, is not only dependent on advances in technology itself but also the users of such technology". What is interesting when we look generally at an example of OpenStreetMap which is probably now the best and biggest service of volunteered geographical information system in use today but not the only one. If we talk about contributors from my own experience, I have found that knowledge about mapping practices and conventions is spread between people, from the most influential to complete beginners, by good advice and imitation. We, as researchers are interested how this evolution of quality in data my affect a final product map in a system like OpenStreetMap and we are curious if there will be some way for automatic assessment

Comparison of the accuracy of OpenStreetMap for Ireland with Google Maps and Bing Maps

We describe a comparison of the accuracy of OpenStreetMap for Ireland with Google Maps and Bing Maps. Five case study cities and towns are chosen for this comparison. Each mapping system is analysed for accuracy under three main headings: spatial coverage, currency, and ground-truth positional accuracy. We find that while there is no clear winner amongst the three mapping platforms each show individual differences and similarities for each of the case study locations. We believe the results described in this paper are useful for those developing Location-based services for countries such as Ireland where access to high-quality geospatial data is often prohibitively expensive or made difficult by other barriers such as lack of data or access restrictions

Assessing the Quality of Open Spatial Data for Mobile Location-based Services Research and Applications

New trends in GIS such as Volunteered Geographical Information (VGI), Citizen Science, and Urban Sensing, have changed the shape of the geoinformatics landscape. The OpenStreetMap (OSM) project provided us with an exciting, evolving, free and open solution as a base dataset for our geoserver and spatial data provider for our research. OSM is probably the best known and best supported example of VGI and user generated spatial content on the Internet. In this paper we will describe current results from the development of quality indicators for measures for OSM data. Initially we have analysed the Ireland OSM data in grid cells (5km) to gather statistical data about the completeness, accuracy, and fitness for purpose of the underlying spatial data. This analysis included: density of user contributions, spatial density of points and polygons, types of tags and metadata used, dominant contributors in a particular area or for a particular geographic feature type, etc. There greatest OSM activity and spatial data density is highly correlated with centres of large population. The ability to quantify and assess if VGI, such as OSM, is of sufficient quality for mobile mapping applications and Location-based services is critical to the future success of VGI as a spatial data source for these technologies

A Multi-lingual pedestrian navigation and campus guidance system using CloudMade API

The importance of a good campus navigation system cannot be ignored as the users will vary from students, special guests, visitors and multi-lingual attendees. Providing a navigation and guidance system with a multi-lingual interface helps in personalizing the system according to the user’s preference for the language of interaction. [Pascal Neis, 2009] is an example of a multi-lingual routing application for navigation developed at the University of Bonn where optimal paths are generated with textual description in the user’s preferred language. Natural language generation (NLG) is the subfield of artificial intelligence and computational linguistics. It is concerned with the construction of computer systems that can produce understandable texts in human languages and form some underlying non-linguistic representation of information in order to meet specified communicative goals [McDonald D.D., 1987]

A Multi-lingual pedestrian navigation and campus guidance system using CloudMade API

The importance of a good campus navigation system cannot be ignored as the users will vary from students, special guests, visitors and multi-lingual attendees. Providing a navigation and guidance system with a multi-lingual interface helps in personalizing the system according to the user’s preference for the language of interaction. [Pascal Neis, 2009] is an example of a multi-lingual routing application for navigation developed at the University of Bonn where optimal paths are generated with textual description in the user’s preferred language. Natural language generation (NLG) is the subfield of artificial intelligence and computational linguistics. It is concerned with the construction of computer systems that can produce understandable texts in human languages and form some underlying non-linguistic representation of information in order to meet specified communicative goals [McDonald D.D., 1987]