Peter Mooney

Bio: Peter Mooney is an academic researcher from Maynooth University. The author has contributed to research in topics: Volunteered geographic information & Geospatial analysis. The author has an hindex of 27, co-authored 138 publications receiving 2952 citations. Previous affiliations of Peter Mooney include United States Environmental Protection Agency & Polytechnic University of Milan.

Crowdsourcing, citizen science or volunteered geographic information? The current state of crowdsourced geographic information

Abstract: Citizens are increasingly becoming an important source of geographic information, sometimes entering domains that had until recently been the exclusive realm of authoritative agencies. This activity has a very diverse character as it can, amongst other things, be active or passive, involve spatial or aspatial data and the data provided can be variable in terms of key attributes such as format, description and quality. Unsurprisingly, therefore, there are a variety of terms used to describe data arising from citizens. In this article, the expressions used to describe citizen sensing of geographic information are reviewed and their use over time explored, prior to categorizing them and highlighting key issues in the current state of the subject. The latter involved a review of ~100 Internet sites with particular focus on their thematic topic, the nature of the data and issues such as incentives for contributors. This review suggests that most sites involve active rather than passive contribution, with citizens typically motivated by the desire to aid a worthy cause, often receiving little training. As such, this article provides a snapshot of the role of citizens in crowdsourcing geographic information and a guide to the current status of this rapidly emerging and evolving subject.

Towards quality metrics for OpenStreetMap

Abstract: Volunteered Geographic Information (VGI) is currently a "hot topic" in the GIS community. The OpenStreetMap (OSM) project is one of the most popular and well supported examples of VGL Traditional measures of spatial data quality are often not applicable to OSM as in many cases it is not possible to access ground-truth spatial data for all regions mapped by OSM. We investigate to develop measures of quality for OSM which operate in an unsupervised manner without reference to a "trusted" source of ground-truth data. We provide results of analysis of OSM data from several European countries. The results highlight specific quality issues in OSM. Results of comparing OSM with ground-truth data for Ireland are also presented.

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

Abstract: 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.

Characteristics of Heavily Edited Objects in OpenStreetMap

Abstract: This paper describes the results of an analysis of the OpenStreetMap (OSM) database for the United Kingdom (UK) and Ireland (correct to April 2011). 15, 640 OSM ways (polygons and polylines), resulting in 316, 949 unique versions of these objects, were extracted and analysed from the OSM database for the UK and Ireland. In our analysis we only considered “heavily edited” objects in OSM: objects which have been edited 15 or more times. Our results show that there is no strong relationship between increasing numbers of contributors to a given object and the number of tags (metadata) assigned to it. 87% of contributions/edits to these objects are performed by 11% of the total 4128 contributors. In 79% of edits additional spatial data (nodes) are added to objects. The results in this paper do not attempt to evaluate the OSM data as good/poor quality but rather informs potential consumers of OSM data that the data itself is changing over time. In developing a better understanding of the characteristics of “heavily edited” objects there may be opportunities to use historical analysis in working towards quality indicators for OSM in the future.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

The knowledge-creating company : how Japanese companies create the dynamics of innovation

Abstract: How has Japan become a major economic power, a world leader in the automotive and electronics industries? What is the secret of their success? The consensus has been that, though the Japanese are not particularly innovative, they are exceptionally skilful at imitation, at improving products that already exist. But now two leading Japanese business experts, Ikujiro Nonaka and Hiro Takeuchi, turn this conventional wisdom on its head: Japanese firms are successful, they contend, precisely because they are innovative, because they create new knowledge and use it to produce successful products and technologies. Examining case studies drawn from such firms as Honda, Canon, Matsushita, NEC, 3M, GE, and the U.S. Marines, this book reveals how Japanese companies translate tacit to explicit knowledge and use it to produce new processes, products, and services.

Modern Applied Statistics With S

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Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

Abstract: From the Publisher: The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.