Special Issue "SDI and the Revolutionary Technological Trends"

Special Issue Editors

Assoc. Prof. Ali Mansourian
E-Mail Website
Guest Editor
GIS Centre, Department of Physical Geography and Ecosystem Science, Lund University, 221 00 Lund, Sweden
Tel. +46 46 222 3317
Interests: Spatial Data Infrastructures; Linked data; Spatial Modeling and Analysis; Machine Learning; Spatial Epidemiology; Disaster Management; Urban Planning
Assoc. Prof. Bastiaan Van Loenen
E-Mail Website
Guest Editor
Department of Architecture and The Built Environment, Delft University of Technology, the Netherlands
Interests: (open) spatial data infrastructure; open data, open city; users; volunteered geographic information (VGI); citizen science governance; information law
Assoc. Prof. Lars Bodum
E-Mail Website
Guest Editor
GeoLab, Department of Planning, Aalborg University, Denmark
Interests: open data; digital planning; spatial multimedia and virtual reality; 3D geoinformation and geovisualisation; big data and smart cities
Dr. Mahdi Farnaghi
E-Mail Website
Guest Editor
GIS Centre, Department of Physical Geography and Ecosystem Science, Lund University Sweden
Interests: big data processing; machine learning; SDI; geospatial services and service composition; semantic web

Special Issue Information

Dear Colleagues,

Spatial data infrastructure (SDI) activities have been initiated at local, national, regional, and global levels to enhance the utilization of spatial data and processing tools in decision-making processes. In recent years, several revolutionary technological trends have disruptively changed the way we think about solving spatial problems. Machine learning, linked data, big data processing, blockchain, NoSQL database systems, virtual and augmented reality, and the Internet of Things are some of the scientific achievements that also influence SDIs. Moreover, while movements towards open data urge us to openly disseminate spatial data to wider groups of audiences, the emergence of ethics, laws, and policies about privacy, security, and liability (such as the General Data Protection Regulation—GDPR), also force us to take more conservative approaches. The primary goal of this Special Issue is to explore how the aforementioned and other revolutionary trends can improve or alter diverse aspects of SDIs, including the life cycle of spatial data (data gathering, processing, distribution, use, maintenance, and storage) and the governance of SDIs. Additionally, it is essential to investigate the possibilities that these new ideas and technologies provide for the development and improvement of SDIs, and more importantly how this development will affect the knowledge about and science behind the creation of future SDIs.

Dr. Ali Mansourian
Dr. Bastiaan van Loenen
Dr. Lars Bodum
Dr. Mahdi Farnaghi
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. ISPRS International Journal of Geo-Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • spatial data infrastructure (SDI)
  • machine learning
  • big data processing
  • blockchain
  • NoSQL database systems
  • virtual and augmented reality
  • Internet of Things
  • open data
  • policies
  • regulations

Published Papers (2 papers)

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Research

Open AccessArticle
The Americas’ Spatial Data Infrastructure
ISPRS Int. J. Geo-Inf. 2019, 8(10), 432; https://doi.org/10.3390/ijgi8100432 - 29 Sep 2019
Abstract
During the last decade, the production of geospatial information has increased considerably; however, managing and sharing this information has become increasingly difficult for the organizations that produce it, because it comes from different data sources and has a wide variety of users. In [...] Read more.
During the last decade, the production of geospatial information has increased considerably; however, managing and sharing this information has become increasingly difficult for the organizations that produce it, because it comes from different data sources and has a wide variety of users. In this sense, to have a better use of geospatial information, several countries have developed national spatial data infrastructures (SDIs) to improve access, visualization, and integration of their data and in turn, have the need to cooperate with other countries to develop regional SDIs, which allow better decision making with regional impact. However, its design and development plan requires, as a starting point, to knowing the level of development of the national SDIs to identify the strengths and gaps that exist in the region. This document presents the methodology developed and the results obtained from the evaluation of the status of implementation of the SDI components in each of the member countries of the Regional Committee of United Nations on Global Geospatial Information Management for the Americas (UN-GGIM: Americas), which will contribute to the equal development of SDIs in an integrated and collaborative way in the Americas. Full article
(This article belongs to the Special Issue SDI and the Revolutionary Technological Trends)
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Open AccessArticle
Assessment and Benchmarking of Spatially Enabled RDF Stores for the Next Generation of Spatial Data Infrastructure
ISPRS Int. J. Geo-Inf. 2019, 8(7), 310; https://doi.org/10.3390/ijgi8070310 - 19 Jul 2019
Abstract
Geospatial information is indispensable for various real-world applications and is thus a prominent part of today’s data science landscape. Geospatial data is primarily maintained and disseminated through spatial data infrastructures (SDIs). However, current SDIs are facing challenges in terms of data integration and [...] Read more.
Geospatial information is indispensable for various real-world applications and is thus a prominent part of today’s data science landscape. Geospatial data is primarily maintained and disseminated through spatial data infrastructures (SDIs). However, current SDIs are facing challenges in terms of data integration and semantic heterogeneity because of their partially siloed data organization. In this context, linked data provides a promising means to unravel these challenges, and it is seen as one of the key factors moving SDIs toward the next generation. In this study, we investigate the technical environment of the support for geospatial linked data by assessing and benchmarking some popular and well-known spatially enabled RDF stores (RDF4J, GeoSPARQL-Jena, Virtuoso, Stardog, and GraphDB), with a focus on GeoSPARQL compliance and query performance. The tests were performed in two different scenarios. In the first scenario, geospatial data forms a part of a large-scale data infrastructure and is integrated with other types of data. In this scenario, we used ICOS Carbon Portal’s metadata—a real-world Earth Science linked data infrastructure. In the second scenario, we benchmarked the RDF stores in a dedicated SDI environment that contains purely geospatial data, and we used geospatial datasets with both crowd-sourced and authoritative data (the same test data used in a previous benchmark study, the Geographica benchmark). The assessment and benchmarking results demonstrate that the GeoSPARQL compliance of the RDF stores has encouragingly advanced in the last several years. The query performances are generally acceptable, and spatial indexing is imperative when handling a large number of geospatial objects. Nevertheless, query correctness remains a challenge for cross-database interoperability. In conclusion, the results indicate that the spatial capacity of the RDF stores has become increasingly mature, which could benefit the development of future SDIs. Full article
(This article belongs to the Special Issue SDI and the Revolutionary Technological Trends)
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