This paper explores new methods of anonymising and representing large human-generated datasets (here mobile phone activity data). We use a quadtree algorithm developed by Lagonigro et. al (2020) to spatially aggregate mobile in-app events and compare outputs obtained between days and against an ordnance survey grid. We aim to demonstrate potential usage of new computational tools and exemplify their potential to inform more elaborate and project-specific regionalisation methods
Spatial data collection in an organizational setup is growing in terms of the number of applications...
In this paper, we introduce a large-scale activity gathering system with mobile sensor devices such ...
The era of Big Data and the emergence of new sources of geo-information, including mobile phone dat...
In the last few years, the rise of big data has rapidly revolutionized how people communicate, move ...
In the last few years, the rise of big data has rapidly revolutionized how people communicate, move ...
The Responsive Mobile Coverage (RMC) framework proposes a methodology for using mobile telephone net...
We use location data from multiple mobile phone applications to describe daily, weekly, seasonal and...
This paper explores the discrepancies in analysis resulting from aggregating data to different scale...
When coupled with spatio-temporal context, location-based data collected in mobile cellular networks...
When coupled with spatio-temporal context, location-based data collected in mobile cellular network...
This paper outlines the development of a classification for a new set of optimised spatial units for...
There are numerous situations when it is utmost important to share efficiently some spatial data amo...
<div>Increasing popularity of social networks made them a viable data source for many data mining ap...
The last few years has seen the use of mobile technology become ubiquituos. Many millions of citizen...
A variety of cutting edge applications for mobile phones exploit the availability of phone sensors t...
Spatial data collection in an organizational setup is growing in terms of the number of applications...
In this paper, we introduce a large-scale activity gathering system with mobile sensor devices such ...
The era of Big Data and the emergence of new sources of geo-information, including mobile phone dat...
In the last few years, the rise of big data has rapidly revolutionized how people communicate, move ...
In the last few years, the rise of big data has rapidly revolutionized how people communicate, move ...
The Responsive Mobile Coverage (RMC) framework proposes a methodology for using mobile telephone net...
We use location data from multiple mobile phone applications to describe daily, weekly, seasonal and...
This paper explores the discrepancies in analysis resulting from aggregating data to different scale...
When coupled with spatio-temporal context, location-based data collected in mobile cellular networks...
When coupled with spatio-temporal context, location-based data collected in mobile cellular network...
This paper outlines the development of a classification for a new set of optimised spatial units for...
There are numerous situations when it is utmost important to share efficiently some spatial data amo...
<div>Increasing popularity of social networks made them a viable data source for many data mining ap...
The last few years has seen the use of mobile technology become ubiquituos. Many millions of citizen...
A variety of cutting edge applications for mobile phones exploit the availability of phone sensors t...
Spatial data collection in an organizational setup is growing in terms of the number of applications...
In this paper, we introduce a large-scale activity gathering system with mobile sensor devices such ...
The era of Big Data and the emergence of new sources of geo-information, including mobile phone dat...