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      Trustworthy COVID-19 Mapping: Geo-spatial Data Literacy Aspects of Choropleth Maps

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          Abstract

          Since the COVID-19 (coronavirus disease 2019) pandemic is a global phenomenon, many scientists and research organizations create thematic maps to visualize and understand the spatial spread of the disease and to inform mankind. Nowadays, Geographic Information Systems (GIS) and web mapping technologies enable people to create digital maps on demand. This fosters the permanent update of COVID-19 map products, even by non-cartographers, and their publication in news, media and scientific publications. With the ease and speed of map-making, many map creators seem to forget about the fundamental principles of good and easy-to-read thematic choropleth maps, which requires geo-spatial data literacy. Geo-spatial data literacy is an important skill, to be able to judge the reliability of spatial data, and to create ingenuous thematic maps. This contribution intends to make people of disciplines other than those that are map-related aware of the power of thematic maps and how one can create trustworthy thematic maps instead of misleading thematic maps which could, in a worst case,  lead to misinterpretation.

          Translated abstract

          Da die Pandemie COVID-19 (Coronavirus-Krankheit 2019) ein globales Phänomen ist, erstellen viele Wissenschaftlerinnen und Wissenschaftler sowie Forschungsorganisationen thematische Karten, um die räumliche Ausbreitung der Krankheit zu visualisieren und zu verstehen und um die Menschheit darüber zu informieren. Heutzutage ermöglichen Geographische Informationssysteme (GIS) und Web-Mapping-Technologien kurzfristig die bedarfsgerechte Erstellung digitaler Karten. Dies fördert die ständige Aktualisierung von COVID-19-Kartenprodukten, auch von Nicht-Kartographen, und ihre Veröffentlichung in Nachrichten, Medien und wissenschaftlichen Publikationen. Angesichts der Leichtigkeit und Schnelligkeit der Kartenerstellung scheinen viele Kartographen die Grundprinzipien guter und leicht lesbarer thematischer Choroplethenkarten zu vergessen, was Geo-Datenkompetenz erfordert. Geo-Datenkompetenz ist eine wichtige Fähigkeit, um die Glaubwürdigkeit von Geodaten beurteilen zu können und vertrauenswürdige thematische Karten erstellen zu können. Mit diesem Beitrag sollen Menschen anderer als kartenbezogener Disziplinen auf die Einflußmöglichkeiten thematischer Karten aufmerksam gemacht werden und darauf, wie man verläßliche thematische Karten erstellen kann, anstelle von irreführenden thematischen Karten, die im schlimmsten Fall zu Fehlinterpretationen führen könnten.

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          COVID-19: Challenges to GIS with Big Data

          Highlights • GIS with big data provides geospatial information to fight COVID-19. • Big data showed power on epidemic transmission analysis and prevention decision making support. • Challenges still continue in data aggregation, knowledge discovery, and dynamic expression.
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            Evaluation of Methods for Classifying Epidemiological Data on Choropleth Maps in Series

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              The need for GIScience in mapping COVID-19

              Since first being tracked in China in late 2019, the effects of the COVID-19 coronavirus have shaped global patterns of morbidity and mortality, as well as exposed the strengths and limitations of health care systems and social safety nets. Without question, reporting of its impact has been bolstered in large part through near real-time daily mapping of cases and fatalities. Though these maps serve as an effective political and social tool in communicating disease impact, most visualizations largely over-emphasize their usefulness for tracking disease progression and appropriate responses. Messy and inconsistent health data are a big part of this problem, as is a paucity of high-resolution spatial data to monitor health outcomes. Another issue is that the ease of producing out-of-the box products largely out paces the response to the core challenges inherent in the poor quality of most geo-referenced data. Adopting a GIScience approach, and in particular, making use of location-based intelligence tools, can improve the shortcomings in data reporting and more accurately reveal how COVID-19 will have a long-term impact on global health.
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                Author and article information

                Contributors
                carsten.juergens@rub.de
                Journal
                KN J Cartogr Geogr Inf
                KN J Cartogr Geogr Inf
                Kn - Journal of Cartography and Geographic Information
                Springer International Publishing (Cham )
                2524-4957
                2524-4965
                23 October 2020
                23 October 2020
                : 1-7
                Affiliations
                GRID grid.5570.7, ISNI 0000 0004 0490 981X, Geomatics Group, Institute of Geography, Faculty of Geosciences, , Ruhr University Bochum, ; 44780 Bochum, Germany
                Author information
                http://orcid.org/0000-0002-2338-7987
                Article
                57
                10.1007/s42489-020-00057-w
                7583689
                33134849
                b7323966-b278-434d-a4b5-634463143371
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 6 August 2020
                : 7 October 2020
                Categories
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                data literacy,thematic map,covid-19,corona pandemic,mapping,big data,choropleth map

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