Geospatial information infrastructures

Manual of Digital Earth / Editors: Huadong Guo, Michael F. Goodchild, Alessandro Annoni .- Springer, 2020 .- ISBN: 978-981-32-9915-3Geospatial information infrastructures (GIIs) provide the technological, semantic,organizationalandlegalstructurethatallowforthediscovery,sharing,and use of geospatial information (GI). In this chapter, we introduce the overall concept and surrounding notions such as geographic information systems (GIS) and spatial datainfrastructures(SDI).WeoutlinethehistoryofGIIsintermsoftheorganizational andtechnologicaldevelopmentsaswellasthecurrentstate-of-art,andreflectonsome of the central challenges and possible future trajectories. We focus on the tension betweenincreasedneedsforstandardizationandtheever-acceleratingtechnological changes. We conclude that GIIs evolved as a strong underpinning contribution to implementation of the Digital Earth vision. In the future, these infrastructures are challengedtobecomeflexibleandrobustenoughtoabsorbandembracetechnological transformationsandtheaccompanyingsocietalandorganizationalimplications.With this contribution, we present the reader a comprehensive overview of the field and a solid basis for reflections about future developments

Leveraging Container Technologies in a GIScience Project: A Perspective from Open Reproducible Research

Scientific reproducibility is essential for the advancement of science. It allows the results of previous studies to be reproduced, validates their conclusions and develops new contributions based on previous research. Nowadays, more and more authors consider that the ultimate product of academic research is the scientific manuscript, together with all the necessary elements (i.e., code and data) so that others can reproduce the results. However, there are numerous difficulties for some studies to be reproduced easily (i.e., biased results, the pressure to publish, and proprietary data). In this context, we explain our experience in an attempt to improve the reproducibility of a GIScience project. According to our project needs, we evaluated a list of practices, standards and tools that may facilitate open and reproducible research in the geospatial domain, contextualising them on Peng’s reproducibility spectrum. Among these resources, we focused on containerisation technologies and performed a shallow review to reflect on the level of adoption of these technologies in combination with OSGeo software. Finally, containerisation technologies proved to enhance the reproducibility and we used UML diagrams to describe representative work-flows deployed in our GIScience project.This work has been funded by the Generalitat Valenciana through the “Subvenciones para la realización de proyectos de I+D+i desarrollados por grupos de investigación emergentes” programme (GV/2019/016) and by the Spanish Ministry of Economy and Competitiveness under the subprogrammes Challenges-Collaboration 2014 (RTC-2014-1863-8) and Challenges R+D+I 2016 (CSO2016-79420-R AEI/FEDER, EU). Sergio Trilles has been funded by the postdoctoral programme PINV2018 - Universitat Jaume I (POSDOC-B/2018/12) and stays programme PINV2018 - Universitat Jaume I (E/2019/031)

Leveraging Container Technologies in a GIScience Project: A Perspective from Open Reproducible Research

Scientific reproducibility is essential for the advancement of science. It allows the results of previous studies to be reproduced, validates their conclusions and develops new contributions based on previous research. Nowadays, more and more authors consider that the ultimate product of academic research is the scientific manuscript, together with all the necessary elements (i.e., code and data) so that others can reproduce the results. However, there are numerous difficulties for some studies to be reproduced easily (i.e., biased results, the pressure to publish, and proprietary data). In this context, we explain our experience in an attempt to improve the reproducibility of a GIScience project. According to our project needs, we evaluated a list of practices, standards and tools that may facilitate open and reproducible research in the geospatial domain, contextualising them on Peng’s reproducibility spectrum. Among these resources, we focused on containerisation technologies and performed a shallow review to reflect on the level of adoption of these technologies in combination with OSGeo software. Finally, containerisation technologies proved to enhance the reproducibility and we used UML diagrams to describe representative work-flows deployed in our GIScience project

Giving life to the map can save more lives. Wildfire scenario with interoperable simulations

Abstract. In the Mediterranean region, drier and hotter summers are leading to more likely and severe wildfires. The authors propose an innovative approach for situational awareness by giving life to maps and exploiting interoperable GIS, hazard models, simulations, and interconnection analysis processes aimed to enhance preparedness and strengthen the resilience of responding organizations. The information related to a virtual city and its countryside has been implemented in the terrain of simulation systems. The TIGER wildfire model software has been adapted to a scenario where districts, refugee camps and critical infrastructures can be impacted by a fire and has been linked to a smoke dispersion model, and associated impacts to the electricity network and roads. The transfer of computed fire propagation and combustion data to the AI-powered SWORD simulation enable more accurate computing of damage and loss. In SWORD, civil protection, military assets and humanitarian actions can be performed for training and operation preparation. The simulation data about fire and assets' deployments can feed a web app map or a command and control system, thus providing situational awareness for optimal decision-making, and analysis about people in danger, network interconnections and potential service disruption. Disaster managers and commanders can interact with simulated assets performing their chosen courses of action and analyse the outcomes.In conclusion, tests in a wildfire case study demonstrated a high level of interoperability among those systems and the possibility to provide updated situational awareness leading to better emergency preparedness and critical infrastructure resilience building, finally contributing to save more lives.</p

Towards a Theory of GIS Program Management

After a brief flurry of monographs on business and organizational aspects of GIS in the 1990s, little attention has been paid to a systematic approach in support of GIS Program management. Most existing efforts in both public and private enterprises are based on anecdotal evidence. This chapter outlines a range of research questions and the beginning efforts to study modern GIS management practices and help develop a body of knowledge that can be used for the accreditation of GIS Programs and the certification of GIS Program managers

Developing geospatial thinking learning lines in secondary education : the GI Learner project

Geo-ICT is part of the digital economy identified by the European Commission as being vital for innovation, growth, jobs and European competitiveness. It is a rapidly growing business sector, but it is in many countries a shortage occupation sector. More attention to Geo-ICT in education, which relates to geospatial thinking, would help. The GI Learner project developed therefore a geospatial thinking learning line for secondary schools, so that integration of geospatial thinking can take place. The learning line concept used hereby different levels of complexity, referring to the taxonomy of Bloom, taking into account age and capabilities of students. For each of the competencies lesson materials related to the curriculum was produced, thus facilitating the implementation in education on short term. To measure the impact of the learning lines on spatial thinking a self-test was therefore developed, taking into account the level of complexity of each competence (A, B or C) for each age group. The GI Learner project website (http://www.gilearner.eu) provides access to as well the research publications as well as the developed teaching resources

Artificial intelligence and visual analytics in geographical space and cyberspace: Research opportunities and challenges

In recent decades, we have witnessed great advances on the Internet of Things, mobile devices, sensor-based systems, and resulting big data infrastructures, which have gradually, yet fundamentally influenced the way people interact with and in the digital and physical world. Many human activities now not only operate in geographical (physical) space but also in cyberspace. Such changes have triggered a paradigm shift in geographic information science (GIScience), as cyberspace brings new perspectives for the roles played by spatial and temporal dimensions, e.g., the dilemma of placelessness and possible timelessness. As a discipline at the brink of even bigger changes made possible by machine learning and artificial intelligence, this paper highlights the challenges and opportunities associated with geographical space in relation to cyberspace, with a particular focus on data analytics and visualization, including extended AI capabilities and virtual reality representations. Consequently, we encourage the creation of synergies between the processing and analysis of geographical and cyber data to improve sustainability and solve complex problems with geospatial applications and other digital advancements in urban and environmental sciences