Search Results (61)

Variety Dynamics (VD) is a new methodology to identify reasons for failures in spatial data infrastructure (SDI) governance and standardisation as well as potential opportunities for improvement. SDI governance and standardisation situations are often shaped by multiple feedback loops and do not conform to the assumptions needed for causal analysis. This combination is an intrinsic basis for faulty decision and policy making. Variety Dynamics presents geographic information science with a new ability to address the above issues and reveal otherwise hidden structural factors. It shows that most SDI initiatives for change are ineffective because they do not influence variety distributions. Standards are published, coordinating bodies established, and technical platforms deployed without significant changes in equitable outcomes. Variety Dynamics also reveals opportunities for successful SDI policy initiatives leveraging data sovereignty changes that force infrastructure migration and temporarily invert transaction cost structures. After data sovereignty is established, however, any SDI governance and standardisation problems will be likely locked in through path dependencies and accumulated switching costs. Full article

Dangerous goods transport (DGT) is of strategic importance for any economy, and the structure of the fuel and energy industry includes a number of systems and facilities qualified as “critical infrastructure” (CI). Given the current geopolitical situation, sabotage, hybrid or even terrorist activities in the area of logistics and transport pose an increasing threat. At the same time, next to the economic sector, liquid fuels are of great importance to citizens, which is why the transport of this group of goods should be given special importance, ensuring appropriate efficiency and safety parameters, taking into account the risk of intentional, destructive human interference. A significant source of data in the road transport of dangerous goods is the spatial data infrastructure (SDI); digital interactive platforms (DIP) are important here. This scientific research work concerns the application of DIP and related information technologies (IT) in road transport—smart mobility (SM). The main objective of the scientific research work is to develop proposals for effective tools to minimize the overall risk, using publicly available digital interactive platforms. In the implementation of the topic, the following methods were integrated: OKR (Objectives and Key Results), SMART (Specific, Measurable, Achievable, Relevant, Time-bound) and CS (Case Study). The main problem was identified and the main goal of the work was achieved. The results made it possible to present effective risk minimization tools in DGT using DIP. The elaboration was prepared under the research subvention of the AGH University of Krakow, No. 16.16.150.545 in 2026. Full article

Climate change is reshaping territorial safety and water-resource management, calling for digital tools that integrate heterogeneous datasets, enable advanced analyses, and enhance decision-making transparency. This article documents the three-year digital transformation (2022–2025) of the Central Apennine River Basin District Authority (AUBAC), covering > 42,000 km² and serving 8.6 million residents in central Italy. Through an incremental methodology across three releases, AUBAC developed an integrated WebGIS consolidating 613 geospatial layers and near-real-time monitoring from 1844 IoT sensors, implementing a Level 1 (Diagnostic) Digital Twin. Measured results include 141,569 platform visits, an approximately 60% reduction in administrative burden, a 70–80% reduction in plan-processing times, over 5000 users participating in public consultations, and a 40–60% increase in perceived risk understanding. The article presents the research design, platform architecture, evaluation framework, challenges encountered, and recommendations for replicability. The platform supports climate adaptation, disaster-risk reduction, and integrated water-resource management, contributing to SDGs 6, 11, and 13. The experience demonstrates that territorial Digital Twins can deliver tangible operational gains within public administration while establishing a foundation for evolution toward predictive capabilities. Full article

Semantic interoperability remains a critical challenge in Spatial Data Infrastructures (SDIs), particularly when aligning authoritative taxonomies with collaborative folksonomies. Traditional alignment tools often fail to bridge the semantic and structural asymmetry between these schemas. This paper evaluates the capability of Large Language Models (LLMs), specifically distinguishing between traditional architectures and emerging Large Reasoning Models (LRMs), to perform semantic alignment between the Brazilian national topographic data model standard (EDGV) and OpenStreetMap (OSM). Using a formal ontology as a prompting scaffold, we tested seven model versions (including ChatGPT 5, DeepSeek R1, and Gemini 2.5) on their ability to bridge the gap between rigid hierarchical classes and the dynamic, ‘long-tail’ vocabulary of the folksonomy. Results reveal a distinct trade-off: while traditional LLMs exhibited ‘lexical rigidity’ and popularity bias—failing to map low-frequency tags—Reasoning Models demonstrated significantly improved capacity for semantic expansion, correctly identifying complex many-to-one (n:1) relationships across linguistic barriers. However, this reasoning depth often came at the cost of ‘hallucination by over-specification’ and syntactic instability in generating OWL code. We conclude that a neuro-symbolic approach, positioning LRMs as ‘Semantic Catalysts’ within a Human-in-the-Loop (HITL) workflow, provides a viable pathway for interoperability, balancing generative power with the need for logical rigor and spatial validation. Full article

When there is an absence of disaster prevention measures, natural hazards can lead to disasters. An essential part of disaster risk management is the geospatial modeling of devastating hazards, where data sharing is of paramount importance in the context of early-warning systems. This research points out the usefulness of Spatial Data Infrastructures (SDIs) for disaster risk reduction through a literature review, focusing on the necessity of data unification and disposal. Initially, the principles of SDIs are presented, given the fact that this framework contributes significantly to the fulfilment of specific targets and priorities of the Sendai Framework for Disaster Risk Reduction 2015–2030. Thereafter, the challenges of SDIs are investigated in order to underline the main drawbacks stakeholders in emergency management have to come up against, namely the semantic misalignment that impedes efficient data retrieval, malfunctions in the interoperability of datasets and web services, the non-availability of the data in spite of their existence, and a lack of quality data, while also highlighting the obstacles of real case studies on national NSDIs. Thus, diachronic observations on disasters will not be made, despite these comprising a meaningful dataset in disaster mitigation. Consequently, the harmonization of national SDIs with international schemes, such as the Group on Earth Observations (GEO) and European Union’s space program Copernicus, and the usefulness of Artificial Intelligence (AI) and Machine Learning (ML) for disaster mitigation through the prediction of natural hazards are demonstrated. In this paper, for the purpose of disaster preparedness, real-world implementation barriers that preclude SDIs to be completed or deter their functionality are presented, culminating in the proposed future research directions and topics for the SDIs that need further investigation. SDIs constitute an ongoing collaborative effort intending to offer valuable operational tools for decision-making under the threat of a devastating event. Despite the operational potential of SDIs, the complexity of data standardization and coordination remains a core challenge. Full article

This paper presents a systematic, narrative review of 62 academic publications (2015–2025) that explore the integration of spatial data infrastructures (SDIs) with emerging smart city technologies to improve local governance. SDIs provide a structured framework for managing geospatial data and, in combination with IoT sensors, geospatial and 3D platforms, cloud computing and AI-powered analytics, enable real-time data-driven decision-making. The review identifies four key technology areas: IoT and sensor technologies, geospatial and 3D mapping platforms, cloud-based data infrastructures, and AI analytics that uniquely contribute to smart governance through improved monitoring, prediction, visualization, and automation. Opportunities include improved urban resilience, public service delivery, environmental monitoring and citizen engagement. However, challenges remain in terms of interoperability, data protection, institutional barriers and unequal access to technologies. To fully realize the potential of integrated SDIs in smart government, the report highlights the need for open standards, ethical frameworks, cross-sector collaboration and citizen-centric design. Ultimately, this synthesis provides a comprehensive basis for promoting inclusive, adaptive and accountable local governance systems through spatially enabled smart technologies. Full article

In port management, the integration of geographic information systems (GIS) is essential for geospatial analysis in a complex environment shaped by digitalisation and energy transition. Although the adoption of GIS and spatial data infrastructures (SDI) are growing, their use remains with challenges in interoperability and collaborative data management. This study conducts a systematic review to identify the main publications from the past 10 years on the use of GIS and SDI in the maritime sector, using the Scopus and Web of Science databases. The results revealed an annual growth of 8.59% in scientific publications over the past decade, with a focus on environmental monitoring, machine learning, and digitalisation. The findings also suggest the limited use of SDI in the maritime sector, reinforcing the need for future research on interoperability and spatial data integration. Nevertheless, the main trends include the integration of GIS with machine learning, advanced spatial applications, and artificial intelligence, showing an increasing focus on sustainability, environmental monitoring, and innovative management systems. Full article

This study presents a bibliometric analysis of spatial data infrastructure (SDI) research and its application in city development. The fast urbanization and growing complexity of urban management recognize the importance of SDI in supporting sustainable urban planning and innovative city development. This study systematically reviews trends in the publications, key contributors, keywords, and thematic areas of SDI and urban settings. The study uses bibliometric tools such as VOSviewer and Biblioshiny, as well as data from 2003 to 2023. The results show that the number of publications has expanded, and the growth rate in publications has accelerated since 2013, increasing significantly due to geospatial technologies and broadening interest in the concept of smart cities. It identifies the key authors, countries, and collaborative networks that have recognized initiation in the research area. It puts forward the core contributions of Germany, Italy, and Croatia in this field. This research uses keyword co-occurrence and thematic mapping to illustrate dynamic areas of emphasis, including incorporating 3D city models with smart mapping and the application domains of Geographical Information Systems (GISs) and SDI in urban planning. This study further elaborates on other significant developing trends, such as implementing participatory sensing in environmental monitoring and securing SDI within smart city applications. It also highlights enhanced international collaborations toward strengthening the global knowledge base of the challenges in sustainable city development. Hence, this bibliometric analysis is supposed to be used for future research and policy decisions within SDI and city development. Overall, this study will support research by providing a direction for the literature on SDI and city studies and arranging bases for future studies that recommend developing urban resilience and sustainability using the effective practice of geospatial data. Full article

Spatial Data Infrastructure (SDI) is a decision-making tool that is often used in the area of urban planning. At the same time, many other data sources with great utility potential, such as Big Data, can be identified. The aim of the paper is to present the possibility of using mobile Big Data collections with data from Polish SDI, for the purposes of local spatial planning on the example of the tourist town, Mikolajki in Poland. The publication also focuses on assessing the quality of data, as well as the decision-making process supported by these sources. The draft of the local spatial development plan was verified based on integrated data sources. The results showed that the visualization of Big Data as a heat map may be used in urban tasks and as the thematic layer integrated with vector and raster data sets from the SDI in the geographic information system software. The contribution is the practical example how information about users of mobile devices and some information from behavioral profiles may be analyzed for the purposes of verifying planned land use. Full article

Efforts to establish Pakistan’s National Spatial Data Infrastructure (NSDI) have been underway for the past 15 years, and therefore it is necessary to gauge the current progress to channelize efforts into areas that need improvement. This article assessed Pakistan’s NSDI implementation efforts through well-established approaches, including the SDI readiness model, organizational aspects, and state of play. The data were collected from Spatial Data Infrastructure (SDI) and Geographic Information System (GIS) experts. The findings underscored challenges related to human resources, SDI education/culture, long-term vision, lack of awareness of geoinformation (GI), sustainable funding, metadata availability, online geospatial services, and geospatial standards hindering NSDI development in Pakistan. However, certain factors exhibit favorable standings, such as the legal framework for NSDI establishment, web connectivity, geospatial software availability, the unavailability of core spatial datasets, and institutional leadership. Thus, to enhance the development of NSDI in Pakistan, recommendations include bolstering financial and human resources, improving online geospatial presence, and fostering a long-term vision for NSDI. Full article

Geospatial data, especially remote sensing (RS) data, are of significant importance for public services and production activities. Expertise is critical in processing raw data, generating geospatial information, and acquiring domain knowledge and other remote sensing applications. However, existing geospatial service platforms are more oriented towards the professional users in the implementation process and final application. Building appropriate geographic applications for non-professionals remains a challenge. In this study, a geospatial data service architecture is designed that links desktop geographic information system (GIS) software and cloud-based platforms to construct an efficient user collaboration platform. Based on the scalability of the platform, four web apps with different themes are developed. Data in the fields of ecology, oceanography, and geology are uploaded to the platform by the users. In this pilot phase, the gap between non-specialized users and experts is successfully bridged, demonstrating the platform’s powerful interactivity and visualization. The paper finally evaluates the capability of building spatial data infrastructures (SDI) based on GeoNode and discusses the current limitations. The support for three-dimensional data, the improvement of metadata creation and management, and the fostering of an open geo-community are the next steps. Full article

The field of planetary mapping and cartography builds almost exclusively on remote-sensing data and can be defined by three distinct concepts: systematic imaging as performed through spacecraft surveying, reference mapping as performed through the compilation of reference maps, i.e., regional to global image and topographic maps, and thematic mapping, which aims at abstracting and contextualizing spatial information to generate complex thematic maps, such as geologic or geomorphologic maps. While thematic mapping represents the highest form of abstraction of information that is provided through systematic mapping, thematic mapping also provides scientific reasoning in support of systematic mapping and exploration through spatially contextualized knowledge. For the development of knowledge, it is paramount to manage and exploit the value of thematic maps as research products, and to design a reliable and transparent development process from the beginning of the mapping phase as there is almost no validation for thematic maps. A key element in accomplishing these objectives is well-designed structures and metadata which are maintained within spatial data infrastructures (SDI) and shared as a coordinated process in research data management through data models. In this contribution, we focus on the need to transfer planetary thematic maps into findable, accessible, interoperable, reusable (FAIR), as well as transparent research data assets to facilitate improved knowledge extraction and also to compensate for limitations caused by the lack of conventional validation options. We review the current status of planetary thematic mapping, and we discuss the principles and roles of mappers and publishers in the process of creating and stewarding digital planetary maps and associated data products. We then present and discuss a set of recommendations that are closely tied to the FAIR concepts in research data management to accomplish such tasks. Full article

Accessible geospatial data are crucial for informed decision making and policy development in urban planning, environmental governance, and hazard mitigation. Spatial data infrastructures (SDIs) have been implemented to facilitate such data access. However, with the rapid advancements in geospatial software and modelling tools, it is important to re-visit the theoretical discussion about the different roles of data-focused SDIs and decision support and modelling tools, particularly in relation to their different impacts on policy making and policy integration. This research focuses on addressing this issue within the specific context of policy integration in spatial planning and flood risk management. To investigate this, an experiment was conducted comparing a data-focused SDI, the Myplan Viewer, with a prototype Internet-based Spatially Integrated Policy Infrastructure (SIPI). The findings reveal that the SIPI, which provides access to both data and decision support and modelling tools, significantly enhances policy integration compared to the Myplan Viewer. Moreover, drawing upon communicative action theory, this study underscores that while data-focused SDIs support instrumental goals, they possess limitations in facilitating trade-offs and balancing diverse interests in the policy-making process, particularly in supporting strategic and communicative actions. Full article

This study proposes planning for children’s independent mobility through geoinformation technologies by listening to children. This research assumes that children’s values and expectations must be considered in city planning. A bibliographic review identified 15 indicators which make spaces safe and attractive for children to circulate and play. Thematic maps of the indicators were prepared and integrated by a multicriteria analysis by the weights of the evidence according to the hierarchical importance of each variable. The definition of the weights considered the opinions of the children and technicians. The consultation with children was carried out by mapping volunteers (VGI), a consultation on hierarchy, the geodesign of ideas for the area, and an artistic workshop. In the technical study, the query applied the Delphi method. It used the VGI—Volunteered Geographic Information—web-based platform, where children recorded places of topophilia and topophobia, while technicians mapped the presence of 15 indicators. The set of information was made available on a web-based platform called SDI—Spatial Data Infrastructure—in which there are resources for a geodesign workshop where ideas for the area were elaborated through negotiation and cocreation. The product is a transformational design for the area through urban design and the parameterization of its uses. Full article

It is widely accepted that old cadastral maps have multiple uses, such as reestablishing cadastral parcel boundaries, municipality boundaries, and coastal limits, or conducting historical, economic, and social studies. In Spain, the Directorate General for Cadastre, and the National Geographic Institute, has numerous digitized old maps that are accessible to users. In the Comunidad Valenciana, the georeferencing of certain series of old cadastral maps is being carried out in phases, which is one of the subjects of this study. A metric analysis of two series of old cadastral maps from a municipality was conducted. One of the series was georeferenced by the Valencia Provincial Cadastre Office, while the other was georeferenced in this research. Additionally, a spatial data infrastructure (SDI) was created, providing WMS, catalog, and document download services. Metadata were also published, containing information about the source, digitalization process, georeferencing, and achieved accuracy, following the ISO 19115 standard for geographic metadata. Furthermore, through individual and group interviews, participatory social research was conducted, to assess the use of old cadastral maps and the created SDI services, aiming to understand the users’ appreciation of the services. The results of the social research indicate that the SDI services created are highly valued, but certain conditions need to be met to ensure their effective use by the general public in order to avoid misuses and misinterpretations. Full article