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IJGI
Special Issues
Trustful and Ethical Use of Geospatial Data
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Special Issue "Trustful and Ethical Use of Geospatial Data"

A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).

Deadline for manuscript submissions: 31 December 2023 | Viewed by 3232

Special Issue Editors

Prof. Dr. Maria Antonia Brovelli

E-Mail Website
Guest Editor
Department of Civil and Environmental Engineering, Politecnico di Milano, P.zza Leonardo da Vinci, 32, Building 3, 20133 Milano, Italy
Interests: geospatial web; geodata science; citizen science; open science; open data; open geospatial software; geospatial artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Songnian Li
E-Mail Website
Guest Editor
Department of Civil Engineering, Toronto Metropolitan University, Toronto, ON, Canada
Interests: big geospatial data analytics; data mining and knowledge discovery; human mobility; spatio-temporal dynamics; citizen science; digital twins for smart cities
Special Issues, Collections and Topics in MDPI journals
Dr. Ivana Ivánová

E-Mail Website
Guest Editor
School of Earth and Planetary Sciences, Curtin University, Curtin Perth, Kent Street, Bentley, WA 6102, Australia
Interests: spatial data quality and spatial metadata; provenance of spatial resources; spatial information infrastructures

Special Issue Information

Dear Colleagues,

We are inviting you to submit a research paper to “Trustful and Ethical Use of Geospatial Data”, a Special Issue of the ISPRS International Journal of Geo-Information. This Special Issue aims to explore gaps, challenges and opportunities in geospatial data trust and the ethical use of these data. We are seeking contributions discussing scientific research on how trust and ethical use can be incorporated in geospatial information management and on how further issues in this field can be better addressed. Contributions may take the form of literature review papers, short position/perspective papers and original research papers.

Trustworthy and ethical use of data and information has long been studied but has increasingly become an important topic in geospatial information management due to availability of big geospatial data (both authoritative and crowdsourced). Topics of interest include, but are not limited to: ethics in geospatial information science; mapping and cartography; trust in geospatial data, information and knowledge; ethics of augmented and extended reality and the metaverse; use and misuse of geographic information in social media; and GeoAI data ethics and other related issues, for instance, the use of geospatial science for good (leave no one and no place behind). Examples of questions to be answered include:

  • How can benefits of geospatial data and information be maximised while preserving data privacy and security?
  • Has the ethical use of geospatial data been adequately addressed?
  • Are the current ethical guidelines and standards sufficient?
  • How can the concepts of trust, trust models and trust indicators be applied to geospatial data and information?
  • How can we ensure maps are trustworthy?
  • What are the challenges faced in education and the roles of academics in the trustworthy and ethical use of geospatial data?
  • Do existing approaches to achieving SDGs sufficiently address ethics?
  • What are the fundamental ethical principles for geospatial data used in AI and automated decision making (GeoAI)?

Prof. Dr. Maria Antonia Brovelli
Prof. Dr. Songnian Li
Dr. Ivana Ivánová
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 submissions that pass pre-check are 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 1700 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

  • geospatial data
  • information
  • crowdsourcing
  • ethical use
  • data trustfulness
  • ethics and GeoAI
  • privacy and confidentiality
  • ethical principles and standards
  • evaluation

Published Papers (2 papers)

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Research

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Article
Lossless Watermarking Algorithm for Geographic Point Cloud Data Based on Vertical Stability
by
Mingyang Zhang
,
Jian Dong
,
Na Ren
and
Shuitao Guo
ISPRS Int. J. Geo-Inf. 2023, 12(7), 294; https://doi.org/10.3390/ijgi12070294 - 21 Jul 2023
Viewed by 456
Abstract
With the increasing demand for high-precision and difficult-to-obtain geospatial point cloud data copyright protection in military, scientific research, and other fields, research on lossless watermarking is receiving more and more attention. However, most of the current geospatial point cloud data watermarking algorithms embed [...] Read more.
With the increasing demand for high-precision and difficult-to-obtain geospatial point cloud data copyright protection in military, scientific research, and other fields, research on lossless watermarking is receiving more and more attention. However, most of the current geospatial point cloud data watermarking algorithms embed copyright information by modifying vertex coordinate values, which not only damages the data accuracy and quality but may also cause incalculable losses to data users. To maintain data fidelity and protect its copyright, in this paper, we propose a lossless embedded watermarking algorithm based on vertical stability. First, the watermark information is generated based on the binary encoding of the copyright information and the code of the traceability information. Second, the watermark index is calculated based on the length of the watermark information after compression and the vertical distribution characteristics of the data. Finally, watermark embedding is completed by modifying the relative storage order of the corresponding data according to the index and watermark value. The experimental results show that the proposed algorithm has good invisibility without damaging the data accuracy. In addition, compared with existing algorithms, this method has a higher robustness under operations such as projection transformation, precision perturbation, and vertex deletion of geospatial point cloud data. Full article
(This article belongs to the Special Issue Trustful and Ethical Use of Geospatial Data)
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Article
Using HyperLogLog to Prevent Data Retention in Social Media Streaming Data Analytics
by
Marc Löchner
and
Dirk Burghardt
ISPRS Int. J. Geo-Inf. 2023, 12(2), 60; https://doi.org/10.3390/ijgi12020060 - 09 Feb 2023
Viewed by 1221
Abstract
Social media data are widely used to gain insights about social incidents, whether on a local or global scale. Within the process of analyzing and evaluating the data, it is common practice to download and store it locally. Considerations about privacy protection of [...] Read more.
Social media data are widely used to gain insights about social incidents, whether on a local or global scale. Within the process of analyzing and evaluating the data, it is common practice to download and store it locally. Considerations about privacy protection of social media users are often neglected thereby. However, protecting privacy when dealing with personal data is demanded by laws and ethics. In this paper, we introduce a method to store social media data using the cardinality estimator HyperLogLog. Based on an exemplary disaster management scenario, we show that social media data can be analyzed by counting occurrences of posts, without becoming in possession of the actual raw data. For social media data analyses like these, that are based on counting occurrences, cardinality estimation suffices the task. Thus, the risk of abuse, loss, or public exposure of the data can be mitigated and privacy of social media users can be preserved. The ability to do unions and intersections on multiple datasets further encourages the use of this technology. We provide a proof-of-concept implementation for our introduced method, using data provided by the Twitter API. Full article
(This article belongs to the Special Issue Trustful and Ethical Use of Geospatial Data)
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