Special Issue "Open Science in the Geospatial Domain"

Special Issue Editor

Guest Editor
Prof. Massimiliano Cannata

Area geomatica Institute of Earth Sciences, University of Applied Sciences and Arts of Southern Switzerland (SUPSI),Manno, Switzerland
Website | E-Mail
Interests: Open Source Geospatial technologies; environmental monitoring systems; natural resource management system; environmental modeling; open standards and web services

Special Issue Information

Dear Colleagues,

Open Science is being adopted by several research foundations and agencies worldwide as a core strategy to foster knowledge diffusion. This represents a new approach to research and educational processes based on OPEN data, sources, methodologies, reviews, access, and educational resources. While benefits are widely recognized, it is not always simple to apply this approach in practice: available resources, set strategies and existing common practices may be obstacles. Despite the fact that in the geospatial domain several open science practices are already widely adopted (see for example the success of Open Source Software at FOSS4G conferences, the number of Open Standards approved by OGC and the diffusion of Open Data created by OpenStreetMap), there are still underestimated and not yet properly addressed factors that limits the full realization of open science. In fact, while using the open standard and producing open source software and data is certainly important, it is not sufficient and different challenges are still to be addressed at a large scale. First and foremost, there are socio-cultural aspects such as the lack of recognition and rewards of open science practices, the overload for opening data, and unwillingness to change defined working procedures. Then, there are technological barriers, such as unintuitive tools for supporting open science, and missing political endorsements, not only by national or international bodies, but also by universities that ultimately implement strategies and policies that require economic investment in the short term to fulfill technical and organizational aspects. Last but not least, there are legal barriers, such as not always clear legal frameworks and lack of licenses understandable by scientists.

This Special Issue aims to show the state-of-the-art in the geospatial domain with respect to the application of Open Science. Contributions on experiences that implement the Open Science approach, or any of the specific Open Science pillars (data, code, paper, review, standards ?), in the geospatial domain, and that discuss principles, barriers and solutions are important to identify future challenges and best practices. This will help scientists harnessing the full potential of this new paradigm and put in practice Open Science, contributing to the future benefit of humanity.

Prof. Dr. Massimiliano Cannata

Guest Editor

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

  • Open Science
  • Open Source Software
  • Open Education Material
  • Open Data
  • Open Standard
  • Open Access
  • Open Methodology

Published Papers (4 papers)

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Research

Open AccessArticle
Recommendation of Heterogeneous Cultural Heritage Objects for the Promotion of Tourism
ISPRS Int. J. Geo-Inf. 2019, 8(5), 230; https://doi.org/10.3390/ijgi8050230
Received: 12 March 2019 / Revised: 6 April 2019 / Accepted: 5 May 2019 / Published: 17 May 2019
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Abstract
The cultural heritage of a region, be it a highly visited one or not, is a formidable asset for the promotion of its tourism. In many places around the world, an important part of this cultural heritage has been catalogued by initiatives backed [...] Read more.
The cultural heritage of a region, be it a highly visited one or not, is a formidable asset for the promotion of its tourism. In many places around the world, an important part of this cultural heritage has been catalogued by initiatives backed by governments and organisations. However, as of today, most of this data has been mostly unknown, or of difficult access, to the general public. In this paper, we present research that aims to leverage this data to promote tourism. Our first field of application focuses on the French Pyrenees. In order to achieve our goal, we worked on two fronts: (i) the ability to export this data from their original databases and data models to well-known open data platforms; and (ii) the proposition of an open-source algorithm and framework capable of recommending a sequence of cultural heritage points of interests (POIs) to be visited by tourists. This itinerary recommendation approach is original in many aspects: it not only considers the user preferences and popularity of POIs, but it also integrates different contextual information about the user as well as the relevance of specific sequences of POIs (strong links between POIs). The ability to export the cultural heritage data as open data and to recommend sequences of POIs are being integrated in a first prototype. Full article
(This article belongs to the Special Issue Open Science in the Geospatial Domain)
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Open AccessArticle
The Light Source Metaphor Revisited—Bringing an Old Concept for Teaching Map Projections to the Modern Web
ISPRS Int. J. Geo-Inf. 2019, 8(4), 162; https://doi.org/10.3390/ijgi8040162
Received: 28 February 2019 / Revised: 20 March 2019 / Accepted: 24 March 2019 / Published: 28 March 2019
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Abstract
Map projections are one of the foundations of geographic information science and cartography. An understanding of the different projection variants and properties is critical when creating maps or carrying out geospatial analyses. The common way of teaching map projections in text books makes [...] Read more.
Map projections are one of the foundations of geographic information science and cartography. An understanding of the different projection variants and properties is critical when creating maps or carrying out geospatial analyses. The common way of teaching map projections in text books makes use of the light source (or light bulb) metaphor, which draws a comparison between the construction of a map projection and the way light rays travel from the light source to the projection surface. Although conceptually plausible, such explanations were created for the static instructions in textbooks. Modern web technologies may provide a more comprehensive learning experience by allowing the student to interactively explore (in guided or unguided mode) the way map projections can be constructed following the light source metaphor. The implementation of this approach, however, is not trivial as it requires detailed knowledge of map projections and computer graphics. Therefore, this paper describes the underlying computational methods and presents a prototype as an example of how this concept can be applied in practice. The prototype will be integrated into the Geographic Information Technology Training Alliance (GITTA) platform to complement the lesson on map projections. Full article
(This article belongs to the Special Issue Open Science in the Geospatial Domain)
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Open AccessArticle
A Knowledge-Based Filtering Method for Open Relations among Geo-Entities
ISPRS Int. J. Geo-Inf. 2019, 8(2), 59; https://doi.org/10.3390/ijgi8020059
Received: 12 November 2018 / Revised: 16 January 2019 / Accepted: 25 January 2019 / Published: 28 January 2019
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Abstract
Knowledge graphs (KGs) are crucial resources for supporting geographical knowledge services. Given the vast geographical knowledge in web text, extraction of geo-entity relations from web text has become the core technology for construction of geographical KGs; furthermore, it directly affects the quality of [...] Read more.
Knowledge graphs (KGs) are crucial resources for supporting geographical knowledge services. Given the vast geographical knowledge in web text, extraction of geo-entity relations from web text has become the core technology for construction of geographical KGs; furthermore, it directly affects the quality of geographical knowledge services. However, web text inevitably contains noise and geographical knowledge can be sparsely distributed, both of which greatly restrict the quality of geo-entity relationship extraction. We propose a method for filtering geo-entity relations based on existing knowledge bases (KBs). Accordingly, ontology knowledge, fact knowledge, and synonym knowledge are integrated to generate geo-related knowledge. Then, the extracted geo-entity relationships and the geo-related knowledge are transferred into vectors, and the maximum similarity between vectors is the confidence value of one extracted geo-entity relationship triple. Our method takes full advantage of existing KBs to assess the quality of geographical information in web text, which is helpful to improve the richness and freshness of geographical KGs. Compared with the Stanford OpenIE method, our method decreased the mean square error (MSE) from 0.62 to 0.06 in the confidence interval [0.7, 1], and improved the area under the receiver operating characteristic (ROC) curve (AUC) from 0.51 to 0.89. Full article
(This article belongs to the Special Issue Open Science in the Geospatial Domain)
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Open AccessArticle
Distributed Geoscience Algorithm Integration Based on OWS Specifications: A Case Study of the Extraction of a River Network
ISPRS Int. J. Geo-Inf. 2019, 8(1), 12; https://doi.org/10.3390/ijgi8010012
Received: 25 September 2018 / Revised: 18 December 2018 / Accepted: 23 December 2018 / Published: 28 December 2018
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Abstract
To understand and solve various natural environmental problems, geoscience research activities are becoming increasingly dependent on the integration of knowledge, data, and algorithms from scientists at different institutes and with multiple perspectives. However, the facilitation of these integrations remains a challenge because such [...] Read more.
To understand and solve various natural environmental problems, geoscience research activities are becoming increasingly dependent on the integration of knowledge, data, and algorithms from scientists at different institutes and with multiple perspectives. However, the facilitation of these integrations remains a challenge because such scientific activities require gathering numerous geoscience researchers to provide data, knowledge, algorithms, and tools from different institutes and geographically distributed locations. The pivotal issue that needs to be addressed is the identification of a method to effectively combine geoscience algorithms in a distributed environment to promote cooperation. To address this issue, in this paper, a scheme for building a distributed geoscience algorithm integration based on the Open Geospatial Consortium web service (OWS) specifications is proposed. The architecture of the geoscience algorithm integration, algorithm service management mechanism, XML description method for algorithm integration, and integrated model execution strategy are designed and implemented. The experiment implements the integration of geoscience algorithms in a distributed cloud environment and evaluates the feasibility and efficiency of the integrated geoscience model. The proposed method provides a theoretical basis and practical guidance for promoting the integration of distributed geoscience algorithms; this approach can help to aggregate the distributed geoscience capabilities to address natural challenges. Full article
(This article belongs to the Special Issue Open Science in the Geospatial Domain)
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ISPRS Int. J. Geo-Inf. EISSN 2220-9964 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
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