An analysis of existing production frameworks for statistical and geographic information: Synergies, gaps and integration

The production of official statistical and geospatial data is often in the hands of highly specialized public agencies that have traditionally followed their own paths and established their own production frameworks. In this article, we present the main frameworks of these two areas and focus on the possibility and need to achieve a better integration between them through the interoperability of systems, processes, and data. The statistical area is well led and has well-defined frameworks. The geospatial area does not have clear leadership and the large number of standards establish a framework that is not always obvious. On the other hand, the lack of a general and common legal framework is also highlighted. Additionally, three examples are offered: the first is the application of the spatial data quality model to the case of statistical data, the second of the application of the statistical process model to the geospatial case, and the third is the use of linked geospatial and statistical data. These examples demonstrate the possibility of transferring experiences/advances from one area to another. In this way, we emphasize the conceptual proximity of these two areas, highlighting synergies, gaps, and potential integration. © 2021 by the authors. Licensee MDPI, Basel, Switzerland

A unified data: framework for mapping underground: Project Iceberg. Work package 2, defining the problem space for an integrated data operating system above and below ground

Project Iceberg is an exploratory project undertaken by Future Cities Catapult, British Geological Survey (BGS) and Ordnance Survey (OS). The project aims to address the serious issue of the lack of information about the ground beneath our cities and the un-coordinated way in which the subsurface space is managed. Difficulties relating to data capture and sharing of information about subsurface features are well understood by some sectors and have been explored in previous research and industry reports. This study does not replicate past work, but rather reviews outcomes and explores the barriers to wider uptake of subsurface management systems. The long-term goal is to help increase the viability of land for development and de-risk future investment through better management of subsurface data and ground-related risk. To help achieve this, our study aims to enable a means to discover and access relevant data about the ground’s physical condition and assets housed within it, in a way that is suitable for modern data driven decision making processes. The project considers both physical infrastructure i.e. underground utilities and natural ground conditions i.e. geological data and is divided into three different work packages: Work Package 1: Market research and analysis Work Package 2: Data operation systems and interoperability for a subsurface data platform Work Package 3: Identification of use cases for a subsurface data platform This report summarises the findings of work package 2

Bridging the Geospatial Education-Workforce Divide: A Case Study on How Higher Education Can Address the Emerging Geospatial Drivers and Trends of the Intelligent Web Mapping Era

The purpose of this exploratory collective case study is to discover how geospatial education can meet the geospatial workforce needs of the Commonwealth of Virginia, in the emerging intelligent web mapping era. Geospatial education uses geographic information systems (GIS) to enable student learning by increasing in-depth spatial analysis and meaning using geotechnology tools (Baker & White, 2003). Bandura’s (1977) self-efficacy theory and geography concept of spatial thinking form an integrated theoretical framework of spatial cognition for this study. Data collection included in-depth interviews of twelve geospatial stakeholders, documentation collection, and supporting Q methodology to determine the viewpoints of a total of 41 geospatial stakeholders. Q methodology is a type of data collection that when used as a qualitative method utilizes sorting by the participant to determine their preferences. Data analysis strategies included cross-case synthesis, direct interpretation, generalizations, and a correlation matrix to show similarities in participants\u27 preferences. The results revealed four collaborative perceptions of the stakeholders, forming four themes of social education, technology early adoption, data collaboration, and urban fundamentals. Four strategies were identified for higher education to prepare students for the emerging geospatial workforce trends. These strategies are to teach fundamentals, develop agile faculty and curriculum, use an interdisciplinary approach, and collaborate. These strategies reflect the perceptions of stakeholders in this study on how higher education can meet the emerging drivers and trends of the geospatial workforce

Big Data in Maritime Archaeology: Challenges and Prospects from the Middle East and North Africa

The Middle East and North Africa have witnessed a surfeit of geospatial data collection projects, resulting in big databases with powerful deductive capacities. Despite the valuable insights and expansive evidentiary record offered by those databases, emphasis on anthropogenic threats to cultural heritage, combined with a limited integration of local perspectives, have raised important questions on the ethical and epistemological dimensions of big data. This paper contextualizes maritime cultural heritage (MCH) in those debates through the lens of the Maritime Endangered Archaeology in the Middle East and North Africa project (MarEA). MarEA is developing a unique for the region database for MCH designed to amalgamate a baseline record emphasizing spatial location, state of preservation, and vulnerability. This record will form a stepping stone toward finer-grained research on MCH and its interdisciplinary intersections. It is also developed as an information resource to facilitate local collaborators in prioritizing site monitoring and developing documentation, management, and mitigation strategies.</p

Big Data in Maritime Archaeology: Challenges and Prospects from the Middle East and North Africa

The Middle East and North Africa have witnessed a surfeit of geospatial data collection projects, resulting in big databases with powerful deductive capacities. Despite the valuable insights and expansive evidentiary record offered by those databases, emphasis on anthropogenic threats to cultural heritage, combined with a limited integration of local perspectives, have raised important questions on the ethical and epistemological dimensions of big data. This paper contextualizes maritime cultural heritage (MCH) in those debates through the lens of the Maritime Endangered Archaeology in the Middle East and North Africa project (MarEA). MarEA is developing a unique for the region database for MCH designed to amalgamate a baseline record emphasizing spatial location, state of preservation, and vulnerability. This record will form a stepping stone toward finer-grained research on MCH and its interdisciplinary intersections. It is also developed as an information resource to facilitate local collaborators in prioritizing site monitoring and developing documentation, management, and mitigation strategies

PRESERVING THE VERNACULAR POSTINDUSTRIAL LANDSCAPE: BIG DATA GEOSPATIAL APPROACHES TO HERITAGE MANAGEMENT AND INTERPRETATION

Redundant historical industrial sites, or postindustrial landscapes, face numerous preservation challenges. Functionally obsolete, and often derelict and decaying, these cultural landscapes often retain only a fraction of their original infrastructure. With their historical interconnections made indistinct by their physical separation and obscured by the passage of time, surviving remnants are isolated and disjunct, confounding both their legibility and their consideration for formal historic preservation. Nevertheless, they persist. This dissertation presents a theoretical understanding of the nature of postindustrial landscape preservation, and argues that the material persistence of its historical constituents is the result of previously overlooked processes of informal material conservation, here termed vernacular preservation. Further, this dissertation examines ways that heritage professionals can manage and interpret these vast, complex, and shattered landscapes, using 21st-century digital and spatial tools. Confronted by ongoing depopulation and divestment, and constrained by limited financial capacity to reverse the trend of blight and property loss, communities and individuals concerned with the preservation of vernacular postindustrial landscapes face many unique management and interpretation challenges. The successful heritagization of the postindustrial landscape depends on its comprehension, and communication, as a historically complex network of systems, and I argue that utilizing advanced digital and spatial tool such as historical GIS and procedural modeling can aid communities and heritage professionals in managing, preserving, and interpreting these landscapes. This dissertation presents heritage management and interpretation strategies that emphasize the historical, but now largely missing, spatial and temporal contexts of today’s postindustrial landscape in Michigan’s Copper Country. A series of case studies illustrates the demonstrated and potential value of using a big-data, longitudinally-linked digital infrastructure, or Historical GIS (HGIS), known as the Copper Country Historical Spatial Data Infrastructure (CC-HSDI), for heritage management and interpretation. These studies support the public education and conservation goals of the communities in this nationally-significant mining region through providing accessible, engaging, and meaningful historical spatiotemporal context, and by helping to promote and encourage the ongoing management and preservation of this ever-evolving postindustrial landscape

A cross-functional value chain approach to geospatial information: a guide to practice for the minerals industry

A research dissertation submitted to the Faculty of Engineering and the Built Environment, of the University of the Witwatersrand, in the fulfillment of the requirements for the degree of Master of Science in Engineering. Swellendam, 2018Reproducing a mining project life-cycle in the form of a value chain, from exploration to mine closure, provides a graphical representation of the interdependencies between functions or activities, both upstream and downstream of a particular process. This can be used to develop the concept of geospatial context, i.e. high-level situational awareness. By understanding and responding to geospatial context, geospatial information can be enhanced in direct support of investment decisions and/or operational control. The risk of deficient geospatial information requires effective mitigation and management throughout the full life-cycle of a project, starting with exploration where the geospatial foundation is laid for all work which follows. Therefore, geospatial information is a primary, not secondary consideration at the commencement of a project. The role of mine surveying in protecting the surface and workings of a mine, through the provision of accurate maps, plans and associated geospatial records, protects people and the asset, spanning mine and public safety. Additionally, measuring, monitoring, reconciling and reporting key performance indicators which drive value, enables value creation through improved foresight, efficiency and effectiveness. This dissertation discusses the critical role of geospatial information in risk mitigation and business performance monitoring, with specific reference to the interdependencies between functions such as exploration, mining, processing, environmental protection and mine closure. The value potential is significant.MT 201

Flood hazard hydrology: interdisciplinary geospatial preparedness and policy

Thesis (Ph.D.) University of Alaska Fairbanks, 2017Floods rank as the deadliest and most frequently occurring natural hazard worldwide, and in 2013 floods in the United States ranked second only to wind storms in accounting for loss of life and damage to property. While flood disasters remain difficult to accurately predict, more precise forecasts and better understanding of the frequency, magnitude and timing of floods can help reduce the loss of life and costs associated with the impact of flood events. There is a common perception that 1) local-to-national-level decision makers do not have accurate, reliable and actionable data and knowledge they need in order to make informed flood-related decisions, and 2) because of science--policy disconnects, critical flood and scientific analyses and insights are failing to influence policymakers in national water resource and flood-related decisions that have significant local impact. This dissertation explores these perceived information gaps and disconnects, and seeks to answer the question of whether flood data can be accurately generated, transformed into useful actionable knowledge for local flood event decision makers, and then effectively communicated to influence policy. Utilizing an interdisciplinary mixed-methods research design approach, this thesis develops a methodological framework and interpretative lens for each of three distinct stages of flood-related information interaction: 1) data generation—using machine learning to estimate streamflow flood data for forecasting and response; 2) knowledge development and sharing—creating a geoanalytic visualization decision support system for flood events; and 3) knowledge actualization—using heuristic toolsets for translating scientific knowledge into policy action. Each stage is elaborated on in three distinct research papers, incorporated as chapters in this dissertation, that focus on developing practical data and methodologies that are useful to scientists, local flood event decision makers, and policymakers. Data and analytical results of this research indicate that, if certain conditions are met, it is possible to provide local decision makers and policy makers with the useful actionable knowledge they need to make timely and informed decisions

Towards an ontology and metadata structure for a distributed information system for coastal zone management

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Ocean Engineering, 1999.Includes bibliographical references (leaves 161-166).by Pubudu C. Wariyapola.S.M