Análisis de datos etnográficos, antropológicos y arqueológicos: una aproximación desde las humanidades digitales y los sistemas complejos

La llegada de las Ciencias de la Computación, el Big Data, el Análisis de Datos, el Aprendizaje Automático y la Minería de Datos ha modificado la manera en que se hace ciencia en todos los campos científicos, dando lugar, a su vez, a la aparición de nuevas disciplinas tales como la Mecánica Computacional, la Bioinformática, la Ingeniería de la Salud, las Ciencias Sociales Computacionales, la Economía Computacional, la Arqueología Computacional y las Humanidades Digitales –entre otras. Cabe destacar que todas estas nuevas disciplinas son todavía muy jóvenes y están en continuo crecimiento, por lo que contribuir a su avance y consolidación tiene un gran valor científico. En esta tesis doctoral contribuimos al desarrollo de una nueva línea de investigación dedicada al uso de modelos formales, métodos analíticos y enfoques computacionales para el estudio de las sociedades humanas tanto actuales como del pasado.El Ministerio de Ciencia e Innovación • Proyecto SimulPast – “Transiciones sociales y ambientales: simulando el pasado para entender el comportamiento humano” (CSD2010-00034 CONSOLIDER-INGENIO 2010). • Proyecto CULM – “Modelado del cultivo en la prehistoria” (HAR2016-77672-P). • Red de Excelencia SimPastNet – “Simular el pasado para entender el comportamiento humano” (HAR2017-90883-REDC). • Red de Excelencia SocioComplex – “Sistemas Complejos Socio-Tecnológicos” (RED2018-102518-T). La Consejería de Educación de la Junta de Castilla y León • Subvención a la línea de investigación “Entendiendo el comportamiento humano, una aproximación desde los sistemas complejos y las humanidades digitales” dentro del programa de apoyo a los grupos de investigación reconocidos (GIR) de las universidades públicas de Castilla y León (BDNS 425389

An integrated computational and collaborative approach for city resilience planning

Given the rise in climate change-related extreme events, there is an urgent need for cities and regions to implement resilience plans based on data and evidence and developed in collaboration with key stakeholders. However, current planning and decision-making processes rely on limited data and modelling. Moreover, stakeholder engagement is significantly inhibited by social, political, and technological barriers. The research presented in this thesis aims to enhance resilience planning practice through the development and evaluation of an integrated computational and collaborative scenario planning approach. The scenario planning approach is tested within a geodesign framework and supported by several planning support systems (PSS), including urban growth models. These PSS tools are made accessible to key stakeholders through dedicated planning support theatres, enabling participants to collaborate both in-person and online. Through two empirical case studies conducted in Australian regions, this research integrates data-driven modelling (computational) with people-led geodesign (collaborative) approaches for scenario forecasting and planning. The first case study explores anticipatory/normative scenarios, while the second focuses on exploratory scenario planning, with both aiming to enhance city and regional resilience. This thesis examines the roles played by both simple digital tools and purpose-built planning support theatres in scenario planning processes with key stakeholders. The research investigates the utility of data-driven models in supporting collaborative scenario planning. Both integration experiments received positive feedback from most participants. However, to truly improve the process, there is a need for widely available high-quality spatial and temporal datasets, including localised climate change impact data. In summary, an integrated computational and collaborative approach, augmented by data and technology, can provide an evidence base for decision-making towards a resilient future, fostering deeper engagement of the local community and across-government collaboration in scenario planning

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity