GI_Forum 2020, Volume 8, Issue 2 Journal for Geographic Information Science
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Verlag der Österreichischen Akademie der Wissenschaften Austrian Academy of Sciences Press
A-1011 Wien, Dr. Ignaz Seipel-Platz 2
Tel. +43-1-515 81/DW 3420, Fax +43-1-515 81/DW 3400 https://verlag.oeaw.ac.at, e-mail: verlag@oeaw.ac.at |
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DATUM, UNTERSCHRIFT / DATE, SIGNATURE
BANK AUSTRIA CREDITANSTALT, WIEN (IBAN AT04 1100 0006 2280 0100, BIC BKAUATWW), DEUTSCHE BANK MÜNCHEN (IBAN DE16 7007 0024 0238 8270 00, BIC DEUTDEDBMUC)
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GI_Forum 2020, Volume 8, Issue 2 Journal for Geographic Information Science
ISSN 2308-1708 Online Edition ISBN 978-3-7001-8858-2 Online Edition
Julian Bruns,
Florian Micklich,
Johannes Kutterer,
Andreas Abecker,
Philipp Zehnder
S. 107 - 123 doi:10.1553/giscience2020_02_s107 Verlag der Österreichischen Akademie der Wissenschaften doi:10.1553/giscience2020_02_s107
Abstract: The types of data available have changed in the last decade. While, historically, data were gathered in batches and distributed as such, e.g. as a database or shapefile, today we are dealing increasingly with real-time data. This data is produced and consumed continuously in real time. The phenomenon is most commonly known as streaming data. Traditionally, software for spatial analysis, such as a Geographical Information System (GIS) or spatial database, was created and optimized for the batch processing of data. However, the inherent characteristics of streaming data provide new challenges for data-stream processing systems, which have not yet been solved. In this paper, we propose enhancing systems for the handling and analysis of streaming data through the use of spatial operators. We identify Complex Event Processing (CEP) as a promising underlying concept for such a system and use the (open source) self-service IoT toolbox ‘StreamPipes’ as a representative for this. On the basis of a review of the literature, we selected 6 core types of spatial operator and implemented 33 basic spatial operators in 11 groups. These can be combined with the existing non-spatial operators for in-depth analysis of streaming data that involves spatial dimensions. Keywords: streaming data, spatial analysis, big data, complex event processing Published Online: 2020/12/15 12:18:34 Object Identifier: 0xc1aa5576 0x003c13fd Rights:https://creativecommons.org/licenses/by-nd/4.0/
GI_Forum publishes high quality original research across the transdisciplinary field of Geographic Information Science (GIScience). The journal provides a platform for dialogue among GI-Scientists and educators, technologists and critical thinkers in an ongoing effort to advance the field and ultimately contribute to the creation of an informed GISociety. Submissions concentrate on innovation in education, science, methodology and technologies in the spatial domain and their role towards a more just, ethical and sustainable science and society. GI_Forum implements the policy of open access publication after a double-blind peer review process through a highly international team of seasoned scientists for quality assurance. Special emphasis is put on actively supporting young scientists through formative reviews of their submissions. Only English language contributions are published.
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Verlag der Österreichischen Akademie der Wissenschaften Austrian Academy of Sciences Press
A-1011 Wien, Dr. Ignaz Seipel-Platz 2
Tel. +43-1-515 81/DW 3420, Fax +43-1-515 81/DW 3400 https://verlag.oeaw.ac.at, e-mail: verlag@oeaw.ac.at |