AT-GIS: highly parallel spatial query processing with associative transducers

Users in many domains, including urban planning, transportation, and environmental science want to execute analytical queries over continuously updated spatial datasets. Current solutions for largescale spatial query processing either rely on extensions to RDBMS, which entails expensive loading and indexing phases when the data changes, or distributed map/reduce frameworks, running on resource-hungry compute clusters. Both solutions struggle with the sequential bottleneck of parsing complex, hierarchical spatial data formats, which frequently dominates query execution time. Our goal is to fully exploit the parallelism offered by modern multicore CPUs for parsing and query execution, thus providing the performance of a cluster with the resources of a single machine. We describe AT-GIS, a highly-parallel spatial query processing system that scales linearly to a large number of CPU cores. ATGIS integrates the parsing and querying of spatial data using a new computational abstraction called associative transducers(ATs). ATs can form a single data-parallel pipeline for computation without requiring the spatial input data to be split into logically independent blocks. Using ATs, AT-GIS can execute, in parallel, spatial query operators on the raw input data in multiple formats, without any pre-processing. On a single 64-core machine, AT-GIS provides 3× the performance of an 8-node Hadoop cluster with 192 cores for containment queries, and 10× for aggregation queries

Programming patterns and development guidelines for Semantic Sensor Grids (SemSorGrid4Env)

The web of Linked Data holds great potential for the creation of semantic applications that can combine self-describing structured data from many sources including sensor networks. Such applications build upon the success of an earlier generation of 'rapidly developed' applications that utilised RESTful APIs. This deliverable details experience, best practice, and design patterns for developing high-level web-based APIs in support of semantic web applications and mashups for sensor grids. Its main contributions are a proposal for combining Linked Data with RESTful application development summarised through a set of design principles; and the application of these design principles to Semantic Sensor Grids through the development of a High-Level API for Observations. These are supported by implementations of the High-Level API for Observations in software, and example semantic mashups that utilise the API

CacophonyViz: Visualisation of Birdsong Derived Ecological Health Indicators

The purpose of this work was to create an easy to interpret visualisation of a simple index that represents the quantity and quality of bird life in New Zealand. The index was calculated from an algorithm that assigned various weights to each species of bird. This work is important as it forms a part of the ongoing work by the Cacophony Project which aims to eradicate pests that currently destroy New Zealand native birds and their habitat. The map will be used to promote the Cacophony project to a wide public audience and encourage their participation by giving relevant feedback on the effects of intervention such as planting and trapping in their communities. The Design Science methodology guided this work through the creation of a series of prototypes that through their evaluation built on lessons learnt at each stage resulting in a final artifact that successfully displayed the index at various locations across a map of New Zealand. It is concluded that the artifact is ready and suitable for deployment once the availability of real data from the automatic analysis of audio recordings from multiple locations becomes available

Using Open Street Maps data and tools for indoor mapping in a Smart City scenario

Ponencias, comunicaciones y pósters presentados en el 17th AGILE Conference on Geographic Information Science "Connecting a Digital Europe through Location and Place", celebrado en la Universitat Jaume I del 3 al 6 de junio de 2014.This paper explains the experience of implementing a Smart City scenario using Open Street Maps tools and data. An indoor mapping system including not only a localization and navigation solution, but also a natural speaking environment as a human to machine interface is proposed. The solution is based on a NoSQL database for storing GIS data, a public web service layer used to obtain information, user’s current position, navigation routes and human language interaction. An Android mobile client application is used for providing the proper access to all these services. As a case study, the system was successfully implemented in the U-TAD University. The results shown in this paper can be considered as a demonstration of the previous work related to indoor data representation (IndoorOSM draft) and the navigation solution designed at the Universidade do Minho based on Open Trip Planner. In addition, FHC25 includes a tagging proposal for human language recognition systems

Interactive web-based application for Slovenian dialectal texts

The Slovene language has 56 dialects, grouped into 7 dialect groups. A lot of literature on Slovene dialects already exists in physical form, but the goal of this thesis was to develop an interesting, interactive web application which would let its users see all the dialects on a map, read their characteristics and listen to their sound recordings. In addition, an administrative part was created to allow the addition of more examples. The front end part was developed using technologies such as HTML5, CSS, JavaScript, Google Maps and the AngularJS framework. The back end was created using the PHP language and the MySQL database. Consequently we created the first application of this kind for Slovenian dialects