Design and Development of Personal GeoServices for Universities

Personal GeoServices are emerging as an interaction paradigm linking users to information rich environments like a university campus or to Big Data sources like the Internet of Things by delivering spatially intelligent web-services. OpenStreetMap (OSM) constitutes a valuable source of spatial base-data that can be extracted, integrated, and utilised with such heterogeneous data sources for free. In this paper, we present a Personal GeoServices application built on OSM spatial data and university-specific business data for staff, faculty, and students. While generic products such as Google Maps and Google Earth enable basic forms of spatial exploration, the domain of a university campus presents specific business information needs, such as “What classes are scheduled in that room over there?” and “How can I get to Prof. Murray’s office from here?” Within the framework of the StratAG project (www.StratAG.ie), an eCampus Demonstrator was developed for the National University of Ireland Maynooth (NUIM) to assist university users in exploring and analysing their surroundings within a detailed data environment. This work describes this system in detail, discussing the usage of OSM vector data, and providing insights for developers of spatial information systems for personalised visual exploration of an area

A Geovisual Analytics Approach for Mouse Movement Analysis

The use of Web maps has created opportunities and challenges for map generation and delivery. While volunteered geographic information has led to the development of accurate and inexpensive Web maps, the sheer volume of data generated has created spatial information overload. This results in difficulties identifying relevant map features. Geopersonalisation, which adapts map content based on user interests offers a solution to this. The technique is especially powerful when implicit indicators of interest are used as a basis for personalisation. This article describes the design and features of VizAnalysisTools, a suite of tools to visualise and interpret users’ implicit interactions with map content. While traditional data mining techniques can be used to identify trends and preferences, visual analytics, in particular Geovisual Analytics, which assists the human cognition process, has proven useful in detecting interesting patterns. By identifying salient trends, areas of interest on the map become apparent. This knowledge can be used to strengthen the algorithms used for Geopersonalisation

Exploring Spatial Business Data: A ROA Based eCampus Application

In Smart environments development, providing users with search utilities for interacting efficiently with web and wireless devices is a key goal. At smaller scales, Google Maps and Google Earth with satellite and street views have helped users for querying general information at specific locations. However, at larger local scales, where detailed 3D geometries linked to business data are needed, there is a recognized lack of related information and functionality for in depth exploration of an area. Linking spatial data and business data helps to enrich the user experience by fulfilling more task specific user needs. This paper presents an eCampus Demonstrator for the National University of Ireland, Maynooth (NUIM) based on a Resource Oriented Architecture (ROA), in which various RESTful web-services have been developed and deployed for querying both spatial data and associated business data. The benefits and drawbacks of the chosen technologies are also discussed. This work can be considered as a platform that can be applied to similar application domains such as exploring business parks, hospitals, museums, etc

EgoViz – a Mobile Based Spatial Interaction System

This paper describes research carried out in the area of mobile spatial interaction and the development of a mobile (i.e. on-device) version of a simulated web-based 2D directional query processor. The TellMe application integrates location (from GPS, GSM, WiFi) and orientation (from digital compass/tilt sensors) sensing technologies into an enhanced spatial query processing module capable of exploiting a mobile device’s position and orientation for querying real-world 3D spatial datasets. This paper outlines the technique used to combine these technologies and the architecture needed to deploy them on a sensor enabled smartphone (i.e. Nokia 6210 Navigator). With all these sensor technologies now available on one device, it is possible to employ a personal query system that can work effectively in any environment using location and orientation as primary parameters for directional queries. In doing so, novel approaches for determining a user’s query space in 3 dimensions based on line-of-sight and 3D visibility (ego-visibility) are also investigated. The result is a mobile application that is location, direction and orientation aware and using these data is able to identify objects (e.g. buildings, points-of-interest, etc.) by pointing at them or when they are in a specified field-of-view

Multimodal Content Delivery for Geo-services

This thesis describes a body of work carried out over several research projects in the area of multimodal interaction for location-based services. Research in this area has progressed from using simulated mobile environments to demonstrate the visual modality, to the ubiquitous delivery of rich media using multimodal interfaces (geo- services). To effectively deliver these services, research focused on innovative solutions to real-world problems in a number of disciplines including geo-location, mobile spatial interaction, location-based services, rich media interfaces and auditory user interfaces. My original contributions to knowledge are made in the areas of multimodal interaction underpinned by advances in geo-location technology and supported by the proliferation of mobile device technology into modern life. Accurate positioning is a known problem for location-based services, contributions in the area of mobile positioning demonstrate a hybrid positioning technology for mobile devices that uses terrestrial beacons to trilaterate position. Information overload is an active concern for location-based applications that struggle to manage large amounts of data, contributions in the area of egocentric visibility that filter data based on field-of-view demonstrate novel forms of multimodal input. One of the more pertinent characteristics of these applications is the delivery or output modality employed (auditory, visual or tactile). Further contributions in the area of multimodal content delivery are made, where multiple modalities are used to deliver information using graphical user interfaces, tactile interfaces and more notably auditory user interfaces. It is demonstrated how a combination of these interfaces can be used to synergistically deliver context sensitive rich media to users - in a responsive way - based on usage scenarios that consider the affordance of the device, the geographical position and bearing of the device and also the location of the device

A Case Study for eCampus Spatial: Business Data Exploration

Location based querying is the core interaction paradigm between mobile citizens and the Internet of Things, so providing users with intelligent web-services that interact efficiently with web and wireless devices to recommend personalised services is a key goal. With today\u27s popular Web Map Services, users can ask for general information at a specific location, but not detailed information such as related functionality or environments. This shortcoming comes from a lack of connection between non-spatial “business” data and spatial “map” data. This chapter presents a novel approach for location-based querying in web and wireless environments, in which non-spatial business data is dynamically connected to spatial base-map data to provide users with spatially-enabled attribute information at particular locations. The proposed approach is illustrated in a case study at the National University of Ireland in Maynooth (NUIM), where detailed 3D campus building models were constructed. Non-spatial university specific business data such as the functionalities and timetables of class rooms/buildings, campus news, noise levels, and navigation are then explored over the web and presented as both mobile and desktop web-services

Mobile 2D and 3D Spatial Query Techniques for the Geospatial Web

The increasing availability of abundant geographically referenced information in the Geospatial Web provides a variety of opportunities for developing value-added LBS applications. However, large data volumes of the Geospatial Web and small mobile device displays impose a data visualization problem, as the amount of searchable information overwhelms the display when too many query results are returned. Excessive returned results clutter the mobile display, making it harder for users to prioritize information and causes confusion and usability problems. Mobile Spatial Interaction (MSI) research into this “information overload” problem is ongoing where map personalization and other semantic based filtering mechanisms are essential to de-clutter and adapt the exploration of the real-world to the processing/display limitations of mobile devices. In this thesis, we propose that another way to filter this information is to intelligently refine the search space. 3DQ (3-Dimensional Query) is our novel MSI prototype for information discovery on today’s location and orientation-aware smartphones within 3D Geospatial Web environments. Our application incorporates human interactions (interpreted from embedded sensors) in the geospatial query process by determining the shape of their actual visibility space as a query “window” in a spatial database, e.g. Isovist in 2D and Threat Dome in 3D. This effectively applies hidden query removal (HQR) functionality in 360º 3D that takes into account both the horizontal and vertical dimensions when calculating the 3D search space, significantly reducing display clutter and information overload on mobile devices. The effect is a more accurate and expected search result for mobile LBS applications by returning information on only those objects visible within a user’s 3D field-of-view. ii

Mobile 2D and 3D Spatial Query Techniques for the Geospatial Web

The increasing availability of abundant geographically referenced information in the Geospatial Web provides a variety of opportunities for developing value-added LBS applications. However, large data volumes of the Geospatial Web and small mobile device displays impose a data visualization problem, as the amount of searchable information overwhelms the display when too many query results are returned. Excessive returned results clutter the mobile display, making it harder for users to prioritize information and causes confusion and usability problems. Mobile Spatial Interaction (MSI) research into this “information overload” problem is ongoing where map personalization and other semantic based filtering mechanisms are essential to de-clutter and adapt the exploration of the real-world to the processing/display limitations of mobile devices. In this thesis, we propose that another way to filter this information is to intelligently refine the search space. 3DQ (3-Dimensional Query) is our novel MSI prototype for information discovery on today’s location and orientation-aware smartphones within 3D Geospatial Web environments. Our application incorporates human interactions (interpreted from embedded sensors) in the geospatial query process by determining the shape of their actual visibility space as a query “window” in a spatial database, e.g. Isovist in 2D and Threat Dome in 3D. This effectively applies hidden query removal (HQR) functionality in 360º 3D that takes into account both the horizontal and vertical dimensions when calculating the 3D search space, significantly reducing display clutter and information overload on mobile devices. The effect is a more accurate and expected search result for mobile LBS applications by returning information on only those objects visible within a user’s 3D field-of-view

A Web and Mobile System for Environmental Decision Support

Current field data collection methods for many of today’s scientific and other observer/monitor type applications are still entrenched in the “clipboard age”, requiring manual data transcription to a database management system at some (often much) later date, and only allows for visualisation and analysis of recently captured field data “back in the lab”. This chapter is targeted at progressing today’s pen & paper methodology into the spatially enabled mobile computing age of realtime multi-media data input, integration, visualisation, and analysis simultaneously both in the field and the lab. The system described is customized to the specific needs of the Canadian Great Lakes Laboratory for Fisheries and Aquatic Sciences Fish Habitat Management Group requirements for fish species at risk assessment, but is ready for adaptation to other environmental agency applications (e.g. forestry, health-pesticide monitoring, agriculture, etc.). The chapter is ideally suited to all agencies responsible for collecting field data of any type that have not yet moved to a state-of-the-art mobile and wireless data collection, visualisation, and analysis work methodolog