Revisiting Urban Dynamics through Social Urban Data:

The study of dynamic spatial and social phenomena in cities has evolved rapidly in the recent years, yielding new insights into urban dynamics. This evolution is strongly related to the emergence of new sources of data for cities (e.g. sensors, mobile phones, online social media etc.), which have potential to capture dimensions of social and geographic systems that are difficult to detect in traditional urban data (e.g. census data). However, as the available sources increase in number, the produced datasets increase in diversity. Besides heterogeneity, emerging social urban data are also characterized by multidimensionality. The latter means that the information they contain may simultaneously address spatial, social, temporal, and topical attributes of people and places. Therefore, integration and geospatial (statistical) analysis of multidimensional data remain a challenge. The question which, then, arises is how to integrate heterogeneous and multidimensional social urban data into the analysis of human activity dynamics in cities? To address the above challenge, this thesis proposes the design of a framework of novel methods and tools for the integration, visualization, and exploratory analysis of large-scale and heterogeneous social urban data to facilitate the understanding of urban dynamics. The research focuses particularly on the spatiotemporal dynamics of human activity in cities, as inferred from different sources of social urban data. The main objective is to provide new means to enable the incorporation of heterogeneous social urban data into city analytics, and to explore the influence of emerging data sources on the understanding of cities and their dynamics.  In mitigating the various heterogeneities, a methodology for the transformation of heterogeneous data for cities into multidimensional linked urban data is, therefore, designed. The methodology follows an ontology-based data integration approach and accommodates a variety of semantic (web) and linked data technologies. A use case of data interlinkage is used as a demonstrator of the proposed methodology. The use case employs nine real-world large-scale spatiotemporal data sets from three public transportation organizations, covering the entire public transport network of the city of Athens, Greece.  To further encourage the consumption of linked urban data by planners and policy-makers, a set of webbased tools for the visual representation of ontologies and linked data is designed and developed. The tools – comprising the OSMoSys framework – provide graphical user interfaces for the visual representation, browsing, and interactive exploration of both ontologies and linked urban data.   After introducing methods and tools for data integration, visual exploration of linked urban data, and derivation of various attributes of people and places from different social urban data, it is examined how they can all be combined into a single platform. To achieve this, a novel web-based system (coined SocialGlass) for the visualization and exploratory analysis of human activity dynamics is designed. The system combines data from various geo-enabled social media (i.e. Twitter, Instagram, Sina Weibo) and LBSNs (i.e. Foursquare), sensor networks (i.e. GPS trackers, Wi-Fi cameras), and conventional socioeconomic urban records, but also has the potential to employ custom datasets from other sources. A real-world case study is used as a demonstrator of the capacities of the proposed web-based system in the study of urban dynamics. The case study explores the potential impact of a city-scale event (i.e. the Amsterdam Light festival 2015) on the activity and movement patterns of different social categories (i.e. residents, non-residents, foreign tourists), as compared to their daily and hourly routines in the periods  before and after the event. The aim of the case study is twofold. First, to assess the potential and limitations of the proposed system and, second, to investigate how different sources of social urban data could influence the understanding of urban dynamics. The contribution of this doctoral thesis is the design and development of a framework of novel methods and tools that enables the fusion of heterogeneous multidimensional data for cities. The framework could foster planners, researchers, and policy makers to capitalize on the new possibilities given by emerging social urban data. Having a deep understanding of the spatiotemporal dynamics of cities and, especially of the activity and movement behavior of people, is expected to play a crucial role in addressing the challenges of rapid urbanization. Overall, the framework proposed by this research has potential to open avenues of quantitative explorations of urban dynamics, contributing to the development of a new science of cities

Linking Abstract Analysis to Concrete Design: A Hierarchical Approach to Verify Medical CPS Safety

Complex cyber-physical systems are typically hierarchically organized into multiple layers of abstraction in order to manage design complexity and provide verification tractability. Formal reasoning about such systems, therefore, necessarily involves the use of multiple modeling formalisms, verification paradigms, and concomitant tools, chosen as appropriate for the level of abstraction at which the analysis is performed. System properties verified using an abstract component specification in one paradigm must then be shown to logically follow from properties verified, possibly using a different paradigm, on a more concrete component description, if one is to claim that a particular component when deployed in the overall system context would still uphold the system properties. But, as component specifications at one layer get elaborated into more concrete component descriptions in the next, abstraction induced differences come to the fore, which have to be reconciled in some meaningful way. In this paper, we present our approach for providing a logical glue to tie distinct verification paradigms and reconcile the abstraction induced differences, to verify safety properties of a medical cyber-physical system. While the specifics are particular to the case example at hand - a high-level abstraction of a safety-interlock system to stop drug infusion along with a detailed design of a generic infusion pump - we believe the techniques are broadly applicable in similar situations for verifying complex cyber-physical system properties

Developing a distributed electronic health-record store for India

The DIGHT project is addressing the problem of building a scalable and highly available information store for the Electronic Health Records (EHRs) of the over one billion citizens of India

Architecture-based Evolution of Dependable Software-intensive Systems

This cumulative habilitation thesis, proposes concepts for (i) modelling and analysing dependability based on architectural models of software-intensive systems early in development, (ii) decomposition and composition of modelling languages and analysis techniques to enable more flexibility in evolution, and (iii) bridging the divergent levels of abstraction between data of the operation phase, architectural models and source code of the development phase

Interpreted graph models

A model class called an Interpreted Graph Model (IGM) is defined. This class includes a large number of graph-based models that are used in asynchronous circuit design and other applications of concurrecy. The defining characteristic of this model class is an underlying static graph-like structure where behavioural semantics are attached using additional entities, such as tokens or node/arc states. The similarities in notation and expressive power allow a number of operations on these formalisms, such as visualisation, interactive simulation, serialisation, schematic entry and model conversion to be generalised. A software framework called Workcraft was developed to take advantage of these properties of IGMs. Workcraft provides an environment for rapid prototyping of graph-like models and related tools. It provides a large set of standardised functions that considerably facilitate the task of providing tool support for any IGM. The concept of Interpreted Graph Models is the result of research on methods of application of lower level models, such as Petri nets, as a back-end for simulation and verification of higher level models that are more easily manipulated. The goal is to achieve a high degree of automation of this process. In particular, a method for verification of speed-independence of asynchronous circuits is presented. Using this method, the circuit is specified as a gate netlist and its environment is specified as a Signal Transition Graph. The circuit is then automatically translated into a behaviourally equivalent Petri net model. This model is then composed with the specification of the environment. A number of important properties can be established on this compound model, such as the absence of deadlocks and hazards. If a trace is found that violates the required property, it is automatically interpreted in terms of switching of the gates in the original gate-level circuit specification and may be presented visually to the circuit designer. A similar technique is also used for the verification of a model called Static Data Flow Structure (SDFS). This high level model describes the behaviour of an asynchronous data path. SDFS is particularly interesting because it models complex behaviours such as preemption, early evaluation and speculation. Preemption is a technique which allows to destroy data objects in a computation pipeline if the result of computation is no longer needed, reducing the power consumption. Early evaluation allows a circuit to compute the output using a subset of its inputs and preempting the inputs which are not needed. In speculation, all conflicting branches of computation run concurrently without waiting for the selecting condition; once the selecting condition is computed the unneeded branches are preempted. The automated Petri net based verification technique is especially useful in this case because of the complex nature of these features. As a result of this work, a number of cases are presented where the concept of IGMs and the Workcraft tool were instrumental. These include the design of two different types of arbiter circuits, the design and debugging of the SDFS model, synthesis of asynchronous circuits from the Conditional Partial Order Graph model and the modification of the workflow of Balsa asynchronous circuit synthesis system.EThOS - Electronic Theses Online ServiceEPSRCGBUnited Kingdo

The UDSA ontology: An ontology to support real time urban sustainability assessment

Urban sustainability assessment frameworks have emerged during the past decade to address holistically the complexity of the urban landscape through a systems approach, factoring in environmental, social and economic requirements. However, the current assessment schemes are (a) static in nature, and as such don't reflect the dynamic and real-time nature of urban artefacts, (b) are not grounded in semantics (e.g. BIM and GIS), and (c) are at best used to assist in regulatory compliance, for instance in energy design, to meet increasingly stringent regulatory requirements. Information and communication technologies provide a new value proposition capitalizing on the Internet of Things (IoT) and semantics to provide real-time insights and inform decision making. Consequently, there is a real need in the field for data models that could facilitate data exchange and handle data heterogeneity. In this study, a semantic data model is considered to support near real-time urban sustainability assessment and enhance the semantics of sensor network data. Based on an extensive review of urban sustainability assessment frameworks and ontology development methodologies, the Urban District Sustainability Assessment (UDSA) ontology has been developed and validated using real data from the site of “The Works”, a newly refurbished neighbourhood in Ebbw Vale, Wales. This novel approach reconciles several domain-specific ontologies within one high-level ontology that can support the creation of real-time urban sustainability assessment software. In addition, this information model is aligned with 29 authoritative urban sustainability assessment frameworks, thus providing a useful resource not only in urban sustainability assessment, but also in the wider smart cities context