PhD Computer Science (2004)
BSc Computer Science and Mathematical Physics (1999)
I am very interested in maintaining and extending my research collaborations with other academics, researchers, and industrial partners. Please contact me if you would like to discuss a potential collaboration with me in particular in areas related to my research interests which are outlined below.
I am available for research visits, invited lectures and seminars, conference keynotes, workshops, consultancy, PhD and MSc examinations, funding proposal collaboration etc.
Here are some details of funding awards, research collaborations, merit awards, etc from the last few years.
Some recent papers of different types which have been published and various research activities. This might be of interest to give a flavour of some of the research I'm currently involved in. Please drop me an email if you need any further information.
In recent years we have witnessed the rapid emergence of olunteered Geographical Information (VGI) projects. VGI is being applied more and more for research and applications. Nevertheless, VGI is often denounced due to its heterogeneities in quality, completeness and redundancy. However, these can be improved by applying spatial analysis and data mining techniques. These approaches utilize the relationship between the data from a VGI platform itself and/or cross-utilization of data from other sources, including other VGI platforms or authoritative sources. The purpose of this workshop is to intensively discuss the possibilities of data derivation, knowledge propagation and quality improvement for VGI and VGI analysis.
This report is based on a six-month study of the use of volunteered geographic information (VGI) by government. It focuses on government use of information relating to a location, which was produced through what is known as "crowdsourcing", the process of obtaining information from many contributors amongst the general public, regardless of their background and skill level. The aim of this report is to provide a guide for the successful implementation of VGI in government.
This study aims to analyze spatio-temporal patterns of contributions in OSM by proposing a contribution index (CI) in order to investigate the dynamism of OSM. The CI is based on a per cell analysis of the node quantity, interactivity, semantics, and attractivity (the ability to attract contributors). Additionally this research explores whether OSM has been constantly attracting new users and contributions or if OSM has experienced a decline in its ability to attract continued contributions. Using the Stuttgart region of Germany as a case study the empirical findings of the CI over time confirm that since 2007, OSM has been constantly attracting new users, who create new features, edit the existing spatial objects, and enrich them with attributes. This rate has been dramatically growing since 2011. The utilization of a Cellular Automata-Markov (CA-Markov) model provides evidence that by the end of 2016 and 2020, the rise of CI will spread out over the study area and only a few cells without OSM features will remain.
Volunteered Geographic Information (VGI) has become a popular source of geographic data for GIS practitioners in recent years. VGI datasets are characterised as being: large in volume, subject to dynamic changes and updates, collected through crowdsourcing architectures using a variety of devices and technologies and contain a mixture of structured and unstructured information. Can we call VGI a form of Big Data? Are VGI datasets developing characteristics that make processing them using traditional data processing applications and techniques difficult and unsatisfactory? We explore this question with reference to a number of sources of VGI.
In this paper we examine three geographic crowdsourcing models, namely: volunteered geographic information (VGI), citizen science (CS) and participatory mapping (PM) (Goodchild, 2007; Audubon Society, 1900; and Peluso, 1995). We argue that these geographic knowledge producing practices can be adopted by governments to keep databases up to date (Budhathoki et al., 2008), to gain insight about natural resources (Conrad and Hilchey, 2011), to better understand the socio-economy of the people it governs (Johnston and Sieber, 2013) and as a form of data-based public engagement. The paper will be useful to governments and public agencies considering using geographic crowdsourcing in the future. We begin by defining VGI, CS, PM and crowdsourcing. Two typologies are then offered as methods to conceptualize these practices and the Kitchin (2014) data assemblage framework is proposed as a method by which state actors can critically examine their data infrastructures. A selection of exemplary VGI, CS and PM from Canada and the Republic of Ireland are discussed and the paper concludes with some high level recommendations for administrations considering a geographic approach to crowdsourcing.
This edited volume presents a collection of lessons learned with, and research conducted on, OpenStreetMap, the goal being to promote the project’s integration. The respective chapters address a) state-of-the-art and cutting-edge approaches to data quality analysis in OpenStreetMap, b) investigations on understanding OpenStreetMap contributors and the nature of their contributions, c) identifying patterns of contributions and contributors, d) applications of OpenStreetMap in different domains, e) mining value-added knowledge and information from OpenStreetMap, f) limitations in the analysis OpenStreetMap data, and g) integrating OpenStreetMap with commercial and non-commercial datasets. The book offers an ideal opportunity to present and disseminate a number of cutting-edge developments and applications in the field of geography, spatial statistics, GIS, social science, and cartography.
This volume has presented "OpenStreetMap in GIScience: experiences, research and applications" with a collection of experiences and research carried out with OpenStreetMap as the central and core theme. The volume has sought to build a firm foundation to highlight research work focused on OpenStreetMap. This was one of our original goals when we set out at the beginning of the editorial process. This is, to the best of our current knowledge, the first academically produced volume of its kind which focuses exclusively on OpenStreetMap. Approximately one decade on from the birth of OpenStreetMap in 2004 this volume appears at the most opportune of times. OpenStreetMap has emerged from one of the most tumultuous decades in Information and Communication Technologies (ICT) and possibly in the history of human communication. In the decade where ICT, social media, ubiquitous computing and the Internet of Things emerged OpenStreetMap arguably now proudly stands as one of the best examples of crowd and volunteered-based innovation of this time. Its past has been remarkable and the future for OpenStreetMap is bright.
This is a list of peer-reviewed journal publications of which I am an author. In most cases for the papers below I have included a link to a pre-print or non-formatted print in PDF format which allows most people to access the almost final version of the paper without pay-wall journal access. In all cases please cite the journal paper details correctly and not this website.
This is a listing of some recent invited presentations and seminars I have delivered. Please feel free to link or reproduce the content in these slides. However please cite this website and myself as the original author of the content. Please contact me, using the information above, if you would like me to visit your institute, university, organisation, or conference to present an invite lecture or seminar.
While I am not thinking about spatial data, algorithms, open access to data, or web mapping you will most likely find me: running(marathons), following Manchester United, taking photographs (see my Flickr profile) and enjoying the beauty of the midlands of Ireland (1) (2), (3) . Running is a particular passion of mine and in the past few years I have set reasonably fast personal bests of 2h:32m for the marathon, 1h:12m for the half marathon, 3h:16m for 50 Kilometers, and 15m:37s for 5KM. To January I have completed 71 marathons - which includes 58 sub 3 hour marathons, 38 sub 2:50 marathons and 11 sub 2:40 marathons.