Indicator modelling and interactive visualisation for urban sustainability assessment

This chapter presents a novel framework for the integration of the principles of sustainable development within the urban design processes. The framework recognises that decision making for sustainable urban planning is a challenging process: requiring an understanding of the complex interactions amongst environmental, economic, and social issues. Methodologies are required that would support non-experts to become more involved in the urban design process. Towards this, the authors develop an indicator modelling and visualisation tool which comprises 1) indicator selection, 2) modelling techniques that allow spatio-temporal prediction of indicators, 3) interactive 3D virtual world where visualisation techniques are used to present indicator information overlaying the virtual world to facilitate effective communication with a wide range of stakeholders. The sustainability modelling and 3D visualisations are shown to have the potential to enhance community engagement within the planning process, thus enhancing public acceptance and participation within the urban or rural development project

Detection, Modelling and Visualisation of Georeferenced Emotions from User-Generated Content

In recent years emotion-related applications like smartphone apps that document and analyse the emotions of the user, have become very popular. But research also can deal with human emotions in a very technology-driven approach. Thus space-related emotions are of interest as well which can be visualised cartographically and can be captured in different ways. The research project of this dissertation deals with the extraction of georeferenced emotions from the written language in the metadata of Flickr and Panoramio photos, thus from user-generated content, as well as with their modelling and visualisation. Motivation is the integration of an emotional component into location-based services for tourism since only factual information is considered thus far although places have an emotional impact. The metadata of those user-generated photos contain descriptions of the place that is depicted within the respective picture. The words used have affective connotations which are determined with the help of emotional word lists. The emotion that is associated with the particular word in the word list is described on the basis of the two dimensions ‘valence’ and ‘arousal’. Together with the coordinates of the respective photo, the extracted emotion forms a georeferenced emotion. The algorithm that was developed for the extraction of these emotions applies different approaches from the field of computer linguistics and considers grammatical special cases like the amplification or negation of words. The algorithm was applied to a dataset of Flickr and Panoramio photos of Dresden (Germany). The results are an emotional characterisation of space which makes it possible to assess and investigate specific features of georeferenced emotions. These features are especially related to the temporal dependence and the temporal reference of emotions on one hand; on the other hand collectively and individually perceived emotions have to be distinguished. As a consequence, a place does not necessarily have to be connected with merely one emotion but possibly also with several. The analysis was carried out with the help of different cartographic visualisations. The temporal occurrence of georeferenced emotions was examined detailed. Hence the dissertation focuses on fundamental research into the extraction of space-related emotions from georeferenced user-generated content as well as their visualisation. However as an outlook, further research questions and core themes are identified which arose during the investigations. This shows that this subject is far from being exhausted.:Statement of Authorship I Acknowledgements II Abstract III Zusammenfassung V Table of Contents VII List of Figures XI List of Tables XIV List of Abbreviations XV 1 Introduction 1 1.1 Motivation 1 1.2 Research Questions 3 1.3 Thesis Structure 4 1.4 Underlying Publications 4 2 State of the Art 6 2.1 Emotions 6 2.1.1 Definitions and Terms 6 2.1.2 Emotion Theories 7 2.1.2.1 James-Lange Theory 9 2.1.2.2 Two-Factor Theory 9 2.1.3 Structuring Emotions 9 2.1.3.1 Dimensional Approaches 10 2.1.3.2 Basic Emotions 11 2.1.3.3 Empirical Similarity Categories 12 2.1.4 Acquisition of Emotions 14 2.1.4.1 Verbal Procedures 14 2.1.4.2 Non-Verbal Procedures 14 2.1.5 Relation between Emotions and Places 15 2.1.6 Emotions in Language 17 2.1.7 Affect Analysis and Sentiment Analysis 20 2.2 User-Generated Content 22 2.2.1 Definition and Characterisation 22 2.2.2 Advantages and Disadvantages 23 2.2.3 Tagging 24 2.2.4 Inaccuracies 28 2.2.5 Flickr and Panoramio 29 2.2.5.1 Flickr 30 2.2.5.2 Panoramio 31 2.3 Related Work on Georeferenced Emotions 32 2.3.1 Emotional Data Resulting from Biometric Measurements 33 2.3.1.1 Bio Mapping 33 2.3.1.2 EmBaGIS 34 2.3.1.3 Ein emotionales Kiezportrait 35 2.3.2 Emotional Data Resulting from Empirical Surveys 35 2.3.2.1 EmoMap 35 2.3.2.2 WiMo 36 2.3.2.3 ECDESUP 37 2.3.2.4 Map of World Happiness 38 2.3.2.5 Emotional Study of Yeongsan River Basin 39 2.3.3 Emotional Data Resulting from User-Generated Content 40 2.3.3.1 Emography 40 2.3.3.2 Twittermood 40 2.3.3.3 Tweetbeat 42 2.3.3.4 Beautiful picture of an ugly place 42 2.3.4 Visualisation in the Related Work 43 3 Methods 45 3.1 Approach for Extracting Georeferenced Emotions from the Metadata of Flickr and Panoramio Photos 45 3.2 Implemented Algorithm 45 3.3 Grammatical Special Cases 47 3.3.1 Degree Words 48 3.3.2 Negation 52 3.3.2.1 Syntactic Negation in English Language 55 3.3.2.2 Syntactic Negation in German Language 57 3.3.3 Modification of Words Affected by Grammatical Special Cases 60 4 Visualisation and Analysis of Extracted Georeferenced Emotions 62 4.1 Data Basis 62 4.2 Density Maps 67 4.3 Inverse Distance Weight 71 4.4 3D Visualisation 73 4.5 Choropleth Mapping 74 4.6 Point Symbols 78 4.7 Impact of Considering Grammatical Special Cases 80 5 Investigation in Temporal Aspects 85 5.1 Annually Occurrence of Emotions 85 5.2 Periodic Events 87 5.3 Single Events 91 5.4 Dependence of Georeferenced Emotions on Different Periods of Time 93 5.4.1 Seasons 95 5.4.2 Months 96 5.4.3 Weekdays 98 5.4.4 Times of Day 99 5.5 Potentials and Limits of Temporal Analyses 99 6 Discussion 100 6.1 Evaluation 100 6.2 Weaknesses and Problems 102 7 Conclusions and Outlook 105 7.1 Answers to the Research Questions 105 7.2 Outlook and Future Work 107 8 Bibliography 112 Appendices XVIIn den letzten Jahren sind emotionsbezogene Anwendungen, wie Apps, die die Emotionen des Nutzers dokumentieren und analysieren, sehr populär geworden. Ebenfalls in der Forschung sind Emotionen in einem sehr technologiegetriebenen Ansatz ein Thema. So auch ortsbezogene Emotionen, die sich somit kartographisch darstellen lassen und auf verschiedene Art und Weisen gewonnen werden können. Das Forschungsvorhaben der Dissertation befasst sich mit der Extraktion von georeferenzierten Emotionen aus geschriebener Sprache unter Verwendung von Metadaten verorteter Flickr- und Panoramio-Fotos, d.h. aus nutzergenerierten Inhalten, sowie deren Modellierung und Visualisierung. Motivation hierfür ist die Einbindung einer emotionalen Komponente in ortsbasierte touristische Dienste, da diese bisher nur faktische Informationen berücksichtigen, obwohl Orte durchaus eine emotionale Wirkung haben. Die Metadaten dieser nutzergenerierten Inhalte stellen Beschreibungen des auf dem Foto festgehaltenen Ortes dar. Die dafür verwendeten Wörter besitzen affektive Konnotationen, welche mit Hilfe emotionaler Wortlisten ermittelt werden. Die Emotion, die mit dem jeweiligen Wort in der Wortliste assoziiert wird, wird anhand der zwei Dimensionen Valenz und Erregung beschrieben. Die extrahierten Emotionen bilden zusammen mit der geographischen Koordinate des jeweiligen Fotos eine georeferenzierte Emotion. Der zur Extraktion dieser Emotionen entwickelte Algorithmus bringt verschiedene Ansätze aus dem Bereich der Computerlinguistik zum Einsatz und berücksichtigt ebenso grammatikalische Sonderfälle, wie Intensivierung oder Negation von Wörtern. Der Algorithmus wurde auf einen Datensatz von Flickr- und Panoramio-Fotos von Dresden angewendet. Die Ergebnisse stellen eine emotionale Raumcharakterisierung dar und ermöglichen es, spezifische Eigenschaften verorteter Emotionen festzustellen und zu untersuchen. Diese Eigenschaften beziehen sich sowohl auf die zeitliche Abhängigkeit und den zeitlichen Bezug von Emotionen, als auch darauf, dass zwischen kollektiv und individuell wahrgenommenen Emotionen unterschieden werden muss. Das bedeutet, dass ein Ort nicht nur mit einer Emotion verbunden sein muss, sondern möglicherweise auch mit mehreren. Die Auswertung erfolgte mithilfe verschiedener kartographischer Visualisierungen. Eingehender wurde das zeitliche Auftreten der ortsbezogenen Emotionen untersucht. Der Fokus der Dissertation liegt somit auf der Grundlagenforschung zur Extraktion verorteter Emotionen aus georeferenzierten nutzergenerierten Inhalten sowie deren Visualisierung. Im Ausblick werden jedoch weitere Fragestellungen und Schwerpunkte genannt, die sich im Laufe der Untersuchungen ergeben haben, womit gezeigt wird, dass dieses Forschungsgebiet bei Weitem noch nicht ausgeschöpft ist.:Statement of Authorship I Acknowledgements II Abstract III Zusammenfassung V Table of Contents VII List of Figures XI List of Tables XIV List of Abbreviations XV 1 Introduction 1 1.1 Motivation 1 1.2 Research Questions 3 1.3 Thesis Structure 4 1.4 Underlying Publications 4 2 State of the Art 6 2.1 Emotions 6 2.1.1 Definitions and Terms 6 2.1.2 Emotion Theories 7 2.1.2.1 James-Lange Theory 9 2.1.2.2 Two-Factor Theory 9 2.1.3 Structuring Emotions 9 2.1.3.1 Dimensional Approaches 10 2.1.3.2 Basic Emotions 11 2.1.3.3 Empirical Similarity Categories 12 2.1.4 Acquisition of Emotions 14 2.1.4.1 Verbal Procedures 14 2.1.4.2 Non-Verbal Procedures 14 2.1.5 Relation between Emotions and Places 15 2.1.6 Emotions in Language 17 2.1.7 Affect Analysis and Sentiment Analysis 20 2.2 User-Generated Content 22 2.2.1 Definition and Characterisation 22 2.2.2 Advantages and Disadvantages 23 2.2.3 Tagging 24 2.2.4 Inaccuracies 28 2.2.5 Flickr and Panoramio 29 2.2.5.1 Flickr 30 2.2.5.2 Panoramio 31 2.3 Related Work on Georeferenced Emotions 32 2.3.1 Emotional Data Resulting from Biometric Measurements 33 2.3.1.1 Bio Mapping 33 2.3.1.2 EmBaGIS 34 2.3.1.3 Ein emotionales Kiezportrait 35 2.3.2 Emotional Data Resulting from Empirical Surveys 35 2.3.2.1 EmoMap 35 2.3.2.2 WiMo 36 2.3.2.3 ECDESUP 37 2.3.2.4 Map of World Happiness 38 2.3.2.5 Emotional Study of Yeongsan River Basin 39 2.3.3 Emotional Data Resulting from User-Generated Content 40 2.3.3.1 Emography 40 2.3.3.2 Twittermood 40 2.3.3.3 Tweetbeat 42 2.3.3.4 Beautiful picture of an ugly place 42 2.3.4 Visualisation in the Related Work 43 3 Methods 45 3.1 Approach for Extracting Georeferenced Emotions from the Metadata of Flickr and Panoramio Photos 45 3.2 Implemented Algorithm 45 3.3 Grammatical Special Cases 47 3.3.1 Degree Words 48 3.3.2 Negation 52 3.3.2.1 Syntactic Negation in English Language 55 3.3.2.2 Syntactic Negation in German Language 57 3.3.3 Modification of Words Affected by Grammatical Special Cases 60 4 Visualisation and Analysis of Extracted Georeferenced Emotions 62 4.1 Data Basis 62 4.2 Density Maps 67 4.3 Inverse Distance Weight 71 4.4 3D Visualisation 73 4.5 Choropleth Mapping 74 4.6 Point Symbols 78 4.7 Impact of Considering Grammatical Special Cases 80 5 Investigation in Temporal Aspects 85 5.1 Annually Occurrence of Emotions 85 5.2 Periodic Events 87 5.3 Single Events 91 5.4 Dependence of Georeferenced Emotions on Different Periods of Time 93 5.4.1 Seasons 95 5.4.2 Months 96 5.4.3 Weekdays 98 5.4.4 Times of Day 99 5.5 Potentials and Limits of Temporal Analyses 99 6 Discussion 100 6.1 Evaluation 100 6.2 Weaknesses and Problems 102 7 Conclusions and Outlook 105 7.1 Answers to the Research Questions 105 7.2 Outlook and Future Work 107 8 Bibliography 112 Appendices XV

Reporting Beyond the Pale: UK news discourse on drones in Pakistan

This article on drone strikes in Pakistan offers a distinctive empirical case study for critical scholarship of counterterrorism. By asking how cosmopolitanism has developed through UK news discourse it also provides a constructivist contribution to the literature on drones. I argue UK news discourse is not cosmopolitan because it focuses on risk and places the Other beyond comprehension. US and UK Governments networked counterterrorism operations have complicated accountability and while a drive for certainty promoted more scrutiny of policy, news media outlets, academics and activists turned to statistical and visual genres of communication that inhibited understanding of the Other

Estimating Footfall From Passive Wi-Fi Signals: Case Study with Smart Street Sensor Project

Measuring the distribution and dynamics of the population at granular level both spatially and temporally is crucial for understanding the structure and function of the built environment. In this era of big data, there have been numerous attempts to undertake this using the preponderance of unstructured, passive and incidental digital data which are generated from day-to-day human activities. In attempts to collect, analyse and link these widely available datasets at a massive scale, it is easy to put the privacy of the study subjects at risk. This research looks at one such data source - Wi-Fi probe requests generated by mobile devices - in detail, and processes it into granular, long-term information on number of people on the retail high streets of the United Kingdom (UK). Though this is not the first study to use this data source, the thesis specifically targets and tackles the uncertainties introduced in recent years by the implementation of features designed to protect the privacy of the users of Wi-Fi enabled mobile devices. This research starts with the design and implementation of multiple experiments to examine Wi-Fi probe requests in detail, then later describes the development of a data collection methodology to collect multiple sets of probe requests at locations across London. The thesis also details the uses of these datasets, along with the massive dataset generated by the ‘Smart Street Sensor’ project, to devise novel data cleaning and processing methodologies which result in the generation of a high quality dataset which describes the volume of people on UK retail high streets with a granularity of 5 minute intervals since August 2015 across 1000 locations (approx.) in 115 towns. This thesis also describes the compilation of a bespoke ‘Medium data toolkit’ for processing Wi-Fi probe requests (or indeed any other data with a similar size and complexity). Finally, the thesis demonstrates the value and possible applications of such footfall information through a series of case studies. By successfully avoiding the use of any personally identifiable information, the research undertaken for this thesis also demonstrates that it is feasible to prioritise the privacy of users while still deriving detailed and meaningful insights from the data generated by the users

A holistic method for improving software product and process quality

The concept of quality in general is elusive, multi-faceted and is perceived differently by different stakeholders. Quality is difficult to define and extremely difficult to measure. Deficient software systems regularly result in failures which often lead to significant financial losses but more importantly to loss of human lives. Such systems need to be either scrapped and replaced by new ones or corrected/improved through maintenance. One of the most serious challenges is how to deal with legacy systems which, even when not failing, inevitably require upgrades, maintenance and improvement because of malfunctioning or changing requirements, or because of changing technologies, languages, or platforms. In such cases, the dilemma is whether to develop solutions from scratch or to re-engineer a legacy system. This research addresses this dilemma and seeks to establish a rigorous method for the derivation of indicators which, together with management criteria, can help decide whether restructuring of legacy systems is advisable. At the same time as the software engineering community has been moving from corrective methods to preventive methods, concentrating not only on both product quality improvement and process quality improvement has become imperative. This research investigation combines Product Quality Improvement, primarily through the re-engineering of legacy systems; and Process Improvement methods, models and practices, and uses a holistic approach to study the interplay of Product and Process Improvement. The re-engineering factor rho, a composite metric was proposed and validated. The design and execution of formal experiments tested hypotheses on the relationship of internal (code-based) and external (behavioural) metrics. In addition to proving the hypotheses, the insights gained on logistics challenges resulted in the development of a framework for the design and execution of controlled experiments in Software Engineering. The next part of the research resulted in the development of the novel, generic and, hence, customisable Quality Model GEQUAMO, which observes the principle of orthogonality, and combines a top-down analysis of the identification, classification and visualisation of software quality characteristics, and a bottom-up method for measurement and evaluation. GEQUAMO II addressed weaknesses that were identified during various GEQUAMO implementations and expert validation by academics and practitioners. Further work on Process Improvement investigated the Process Maturity and its relationship to Knowledge Sharing, resulted in the development of the I5P Visualisation Framework for Performance Estimation through the Alignment of Process Maturity and Knowledge Sharing. I5P was used in industry and was validated by experts from academia and industry. Using the principles that guided the creation of the GEQUAMO model, the CoFeD visualisation framework, was developed for comparative quality evaluation and selection of methods, tools, models and other software artifacts. CoFeD is very useful as the selection of wrong methods, tools or even personnel is detrimental to the survival and success of projects and organisations, and even to individuals. Finally, throughout the many years of research and teaching Software Engineering, Information Systems, Methodologies, I observed the ambiguities of terminology and the use of one term to mean different concepts and one concept to be expressed in different terms. These practices result in lack of clarity. Thus my final contribution comes in my reflections on terminology disambiguation for the achievement of clarity, and the development of a framework for achieving disambiguation of terms as a necessary step towards gaining maturity and justifying the use of the term “Engineering” 50 years since the term Software Engineering was coined. This research resulted in the creation of new knowledge in the form of novel indicators, models and frameworks which can aid quantification and decision making primarily on re-engineering of legacy code and on the management of process and its improvement. The thesis also contributes to the broader debate and understanding of problems relating to Software Quality, and establishes the need for a holistic approach to software quality improvement from both the product and the process perspectives