Gavin McArdle

Gavin McArdle
University College Dublin | UCD · School of Computer Science

PhD Computer Science

About

111
Publications
22,500
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1,974
Citations
Introduction
My research is in the area of urban analytics which is the science of examining data related to cities to provide insight into how they are used by citizens. I am particularly interested in human movement in cities through which we gain new insights into human behaviour.
Additional affiliations
June 2010 - present
National University of Ireland, Maynooth
Position
  • Research Associate
June 2008 - May 2010
University College Dublin
Position
  • Research Associate

Publications

Publications (111)
Article
Objective We assess the potential of exploiting stopwords in biomedical concept names to complete the logical definitions of concepts that are not sufficiently defined. Methods Concepts containing stopwords are selected from the Disorder hierarchy of Systematized NOmenclature of MEDicine (SNOMED-CT). SNOMED-CT consists of two types of concepts: Fu...
Article
Full-text available
This paper offers an analysis of the supply of Airbnb accommodation in Rome, one of the main tourist destinations in the world, the third-largest city in Europe, by the number of Airbnb listings. The aim is to focus on the recent spatial trend of Airbnb listings, including the period of the COVID-19 pandemic, and highlight the main housing and soci...
Article
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Since new urbanism strategies encourage higher density and compact city development, it is expected that the height of urban environments will increase in the next few years as a remedy for many urban problems such as urban sprawl, cost of living, and detrimental environmental impacts of horizontal development of cities. Therefore, urban designers...
Article
Ground-based sky imagers (GSIs) are increasingly becoming popular amongst the remote sensing analysts. This is because such imagers offer fantastic alternatives to satellite measurements for the purpose of earth observations. In this paper, we propose an extremely low-cost and miniature ground-based sky camera for atmospheric study. Built using 3D...
Article
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Over time, neighbourhoods experience different types of change. Neighbourhood change is a spatiotemporal process that involves analysing how attributes of a location change over time. In this article, we explore the capability of short-term property rental data to identify neighbourhoods where change is occurring. The article focuses on the relatio...
Article
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International migration is changing the social structure and cultural landscape of countries and big cities worldwide, especially in developed countries which are the target of job and asylum seekers. On the other hand, cultural diversity is becoming an important concept from different perspectives, such as boosting innovation and spatial segregati...
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Like many developing countries, Iran faces air pollution, especially in its metropolises and industrial cities. Nitrogen dioxide (NO2) is one of the significant air pollutants; therefore, this study aims to investigate the spatiotemporal variability of NO2 using Tropospheric Monitoring Instrument (TROPOMI) sensor mounted on the Sentinel-5P (S5P) sa...
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In 2015, global real estate was worth $217 trillion, which is approximately 2.7 times the global GDP; it also accounts for roughly 60% of all conventional global resources, making it one of the key factors behind any country’s economic growth and stability. The accessibility of spatial big data will help real estate investors make better judgement...
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COVID-19 non-pharmaceutical interventions (NPIs) are changing human mobility patterns; however, the effects on power systems remain unclear. Previous loads and timings along with weather features are often used in literature as input features in load forecasting, but these may be insufficient during COVID-19. As a result, this paper proposes an ana...
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Urban sprawl is a universal phenomenon and can be seen as a city’s low-density and haphazard development from the centre to suburban areas, and it has different adverse environmental effects at local and regional scales, including increasing the cost of infrastructure. Geospatial data and technology can be used to measure urban sprawl and predict u...
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In this paper, we study transferable graph neural networks for street networks. The use of Graph Neural Networks in a transfer learning setting is a promising approach to overcome issues such as the lack of good quality data for training purposes. With transfer learning, we can fine-tune a model trained on a rich sample of data before applying to a...
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The effectiveness of a machine learning model is impacted by the data representation used. Consequently, it is crucial to investigate robust representations for efficient machine learning methods. In this paper, we explore the link between data representations and model performance for inference tasks on spatial networks. We argue that representati...
Article
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Volunteered Geographic Information (VGI) is often collected by non-expert users. This raises concerns about the quality and veracity of such data. There has been much effort to understand and quantify the quality of VGI. Extrinsic measures which compare VGI to authoritative data sources such as National Mapping Agencies are common but the cost and...
Preprint
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The UN-Habitat estimates that over one billion people live in slums around the world. However, state-of-the-art techniques to detect the location of slum areas employ high-resolution satellite imagery, which is costly to obtain and process. As a result, researchers have started to look at utilising free and open-access medium resolution satellite i...
Preprint
Ground-based Whole Sky Imagers (WSIs) are increasingly being used for various remote sensing applications. While the fundamental requirements of a WSI are to make it climate-proof with an ability to capture high resolution images, cost also plays a significant role for wider scale adoption. This paper proposes an extremely low-cost alternative to t...
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Full-text available
The residential real estate market is very important because most people’s wealth is in this sector, and it is an indicator of the economy. Real estate market data in general and market transaction data, in particular, are inherently spatiotemporal as each transaction has a location and time. Therefore, exploratory spatiotemporal methods can extrac...
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The use of IoT has become pervasive and IoT devices are common in many domains. Industrial IoT (IIoT) utilises IoT devices and sensors to monitor machines and environments to ensure optimal performance of equipment and processes. Predictive Maintenance (PM) which monitors the health of machines to determine the probable failure of components is one...
Chapter
Healthcare interoperability has been a major challenge since the early 1980s and still remains an unsolved issue. Attempts in the past have addressed this problem using bespoke solutions, but a generic solution still eludes the healthcare community. This chapter discusses the various levels at which interoperability needs to be preserved for an uni...
Preprint
Full-text available
Over a billion people live in slums in settlements that are often located in ecologically sensitive areas and hence highly vulnerable. This is a problem in many parts of the world, but it is more prominent in low-income countries, where in 2014 on average 65% of the urban population lived in slums. As a result, building resilient communities requir...
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Graph Neural Networks (GNNs) have received wide acclaim in recent times due to their performance on inference tasks for unstructured data. Typically, GNNs operate by exploiting local structural information in graphs and disregarding their global structure. This is influenced by assumptions of homophily and unbiased class distributions. As a result,...
Article
Searching for a property is inherently a multicriteria spatial decision. The decision is primarily based on three high-level criteria composed of household needs, building facilities, and location characteristics. Location choice is driven by diverse characteristics; including but not limited to environmental factors, access, services, and the soci...
Conference Paper
In general, neighbourhoods are susceptible to changes such as economic expansion or decline, new developments and infrastructure, new business and industry, gentrification or super gentrification, decline and abandonment. In this paper, we assess the ability of Airbnb data to identify locations prone to neighbourhood change using data from the Airb...
Article
Advancements in technology over the last two decades have changed how spatial data are created and used. In particular, in the last decade, volunteered geographic information (VGI), i.e., the crowdsourcing of geographic information, has revolutionized the spatial domain by shifting the map-making process from the hands of experts to those of any wi...
Conference Paper
Full-text available
Citizen consumption refers to the goods and services which citizens utilise. This includes time spent on leisure and cultural activities as well as the consumption of necessary and luxury goods and services. The spatial dimension of consumption inequality can show the underlying urban spatial structure and processes of a city. Usually, the main bar...
Article
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The performance of a machine learning algorithm is dependent on the quality of the available data for model development. However, in practical situations, the availability of the data is variable and can be limited. This limitation creates a budget problem for data-driven techniques and the objective in such situations is to develop the best model...
Conference Paper
Advances in machine learning and the availability of spatial data have seen remarkable improvements in recent times. This parallel growth has influenced the increased application of traditional data mining techniques for knowledge discovery on spatial data. However, these techniques assume that the data is drawn from an independent and identical di...
Article
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The Internet of Things (IoT) involves embedding electronics, software, sensors and actuators into physical devices such as vehicles, buildings and a wide range of smart devices. Network connectivity allows IoT devices to collect and exchange data. The prevalence of IoT devices has increased rapidly in last 5 years, driven by cheaper electronics and...
Chapter
With the growing volume of geographically referenced data, there is a need to develop new approaches for efficient storage and processing of massive spatial data. The increase in spatial data has been fueled by the growing availability of ubiquitous mobile devices such as smart phones equipped with GPS, and the awareness of the usefulness of spatia...
Chapter
Full-text available
Volunteered Geographic Information is the term used to describe the process of collecting spatial data using a network of volunteers. The approach collects spatial data to build maps which are often freely accessible. The maps and the underlying data can be used by the public, companies and government agencies for a variety of tasks such as route f...
Preprint
Full-text available
In this paper, we examine the governmentality and the logics of urban control enacted through smart city technologies. Several commentators have noted that the implementation of algorithmic forms of urban governance that utilize big data greatly intensifies the extent and frequency of monitoring populations and systems and shifts the governmental l...
Article
This paper critically reflects on the building of the Dublin Dashboard – a website built by two of the authors that provides citizens, planners, policy makers and companies with an extensive set of data and interactive visualizations about Dublin City, including real-time information – from the perspective of critical data studies. The analysis dra...
Article
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Data are an integral part of the smart city and are used as input for decision-making, policy formation, and to inform citizens and businesses. Re flecting on our experience of developing software applications which rely on urban data, this article examines the veracity of such data (their authenticity and the extent to which they accurately (in te...
Article
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As many cities increase in size across multiple dimensions such as population, economic output and physical size, new methods for understanding and managing cities are required. Data produced by and about urban environments offer insight into what is happening in cities. Real-time data from sensors within the city record current transport and envir...
Article
Full-text available
As many cities increase in size across multiple dimensions such as population, economic output and physical size, new methods for understanding and managing cities are required. Data produced by and about urban environments offer insight into what is happening in cities. Real-time data from sensors within the city record current transport and envir...
Article
Full-text available
Big Data has been variously defined in the literature. In the main, definitions suggest that Big Data possess a suite of key traits: volume, velocity and variety (the 3Vs), but also exhaustivity, resolution, indexicality, relationality, extensionality and scalability. However, these definitions lack ontological clarity, with the term acting as an a...
Article
Nowadays, an abundance of sensors are used to collect very large datasets of moving objects. The movement of these objects can be analysed by identifying common routes. For this, a cluster of trajectories must be defined and the pattern of each cluster discovered. In this article, we introduce a new pattern, called the Trajectory Box Plot (TBP), to...
Article
Full-text available
Since the mid-1990s a plethora of indicator projects have been developed and adopted by cities seeking to measure and monitor various aspects of urban systems. These have been accompanied by city benchmarking endeavours that seek to compare intra- and inter-urban performance. More recently, the data underpinning such projects have started to become...
Article
Within the context of the smart city, data are an integral part of the digital economy and are used as input for decision making, policy formation, and to inform citizens, city managers and commercial organisations. Reflecting on our experience of developing real-world software applications which rely heavily on urban data, this article critically...
Article
Full-text available
Big data has been variously defined in the literature. In the main, definitions suggest that big data are those that possess a suite of key traits: volume, velocity and variety (the 3Vs), but also exhaustivity, resolution, indexicality, relationality, extensionality and scalability. However, these definitions lack ontological clarity, with the term...
Article
This article introduces a microsimulation of urban traffic flows within a large-scale scenario implemented for the Greater Dublin region in Ireland. Traditionally, the data available for traffic simulations come from a population census and dedicated road surveys that only partly cover shopping, leisure, or recreational trips. To account for the la...
Conference Paper
Nowadays, an abundance of sensors are used to collect very large datasets containing spatial points which can be mined and analyzed to extract meaningful patterns. In this article, we focus on different techniques used to summarize and visualize 2D point clusters and discuss their relative strengths. This article focuses on patterns which describe...
Article
The quantity and quality of spatial data are increasing rapidly. This is particularly evident in the case of movement data. Devices capable of accurately recording the position of moving entities have become ubiquitous and created an abundance of movement data. Valuable knowledge concerning processes occurring in the physical world can be extracted...
Article
Full-text available
Extracting meaningful information from the growing quantity of spatial data is a challenge. The issues are particularly evident with spatio-temporal data describing movement. Such data typically corresponds to movement of humans, animals and machines in the physical environment. This article considers a special form of movement data generated throu...
Article
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. Geoperson...
Article
Nowadays, an abundance of sensors are used to collect very large datasets containing spatial points which can be mined and analysed to extract meaningful patterns and information. This article examines patterns which describe the dispersion of 2D data around a central tendency. Several state of the art patterns for point cluster analysis are presen...
Conference Paper
Recent technological advances have increased the quantity of movement data being recorded. While valuable knowledge can be gained by analysing such data, its sheer volume creates challenges. Geovisual analytics, which helps the human cognition process by using tools to reason about data, offers powerful techniques to resolve these challenges. This...
Conference Paper
Movement is a ubiquitous phenomenon in the physical and virtual world. Analysing movement can reveal interesting trends and patterns. In the Human-Computer Interaction (HCI) domain, eye and mouse movements reveal the interests and intentions of users. By identifying common HCI patterns in the spatial domain, profiles containing the spatial interest...
Conference Paper
Full-text available
This paper introduces a micro-simulation of urban traffic flows within a large scale scenario implemented for the Greater Dublin region in Ireland. Traditionally, the data available for traffic simulations come from a population census and dedicated road surveys which only partly cover shopping, leisure or recreational trips. To account for the lat...
Article
Advances in ubiquitous positioning technologies and their increasing availability in mobile devices has generated large volumes of movement data. Analysing these datasets is challenging. While data mining techniques can be applied to this data, knowledge of the underlying spatial region can assist interpreting the data. We have developed a geovisua...
Conference Paper
Full-text available
As people's mobility has increased so too has the use of web maps and other geo-technologies for navigational purposes. Daily usage of these technologies, either embedded in smart phones or through advanced Web GIS, involves carrying out specific spatial tasks. Such spatial tasks can be of various types, context and also consider the physical envir...
Conference Paper
Full-text available
Fuelled by the quantity of available online spatial data that continues to grow, the requirement for filtering spatial content to match mobile users' context becomes increasingly important. This paper introduces a flexible algorithm to derive users' preferences in a mobile and distributed system. Such preferences are implicitly computed from users'...
Article
Today, the Internet plays a major role in distributing learning material within third level education. Multiple online facilities provide access to educational resources. While early systems relied on webpages, which acted as repositories for learning material, nowadays sophisticated online applications manage and deliver learning resources. Course...
Article
Full-text available
The past decade has witnessed a steady growth of open source software usage in industry and academia, leading to a complex ecosystem of projects. Web and subsequently geographical information systems have become prominent technologies, widely adopted in diverse domains. Within this context, we developed an open source web platform for interoperable...
Conference Paper
Due to the recent advances and wide adoption of Web 2.0 technologies, there is an abundance of publicly available user generated content, which can be a valuable resource for researchers, enabling them to apply sophisticated analysis methods on data of unprecedented scale. analysis methods on data of unprecedented scale.