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Modelling and Assessing Spatial Big Data: Use Cases of the OpenStreetMap Full-History Dump

Modelling and Assessing Spatial Big Data: Use Cases of the OpenStreetMap Full-History Dump

Alexey Noskov, A. Yair Grinberger, Nikolaos Papapesios, Adam Rousell, Rafael Troilo, Alexander Zipf
Copyright: © 2019 |Pages: 29
ISBN13: 9781522579274|ISBN10: 1522579273|ISBN13 Softcover: 9781522593010|EISBN13: 9781522579281
DOI: 10.4018/978-1-5225-7927-4.ch002
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MLA

Noskov, Alexey, et al. "Modelling and Assessing Spatial Big Data: Use Cases of the OpenStreetMap Full-History Dump." Spatial Planning in the Big Data Revolution, edited by Angioletta Voghera and Luigi La Riccia, IGI Global, 2019, pp. 16-44. https://doi.org/10.4018/978-1-5225-7927-4.ch002

APA

Noskov, A., Grinberger, A. Y., Papapesios, N., Rousell, A., Troilo, R., & Zipf, A. (2019). Modelling and Assessing Spatial Big Data: Use Cases of the OpenStreetMap Full-History Dump. In A. Voghera & L. La Riccia (Eds.), Spatial Planning in the Big Data Revolution (pp. 16-44). IGI Global. https://doi.org/10.4018/978-1-5225-7927-4.ch002

Chicago

Noskov, Alexey, et al. "Modelling and Assessing Spatial Big Data: Use Cases of the OpenStreetMap Full-History Dump." In Spatial Planning in the Big Data Revolution, edited by Angioletta Voghera and Luigi La Riccia, 16-44. Hershey, PA: IGI Global, 2019. https://doi.org/10.4018/978-1-5225-7927-4.ch002

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Abstract

Many methods for intrinsic quality assessment of spatial data are based on the OpenStreetMap full-history dump. Typically, the high-level analysis is conducted; few approaches take into account the low-level properties of data files. In this chapter, a low-level data-type analysis is introduced. It offers a novel framework for the overview of big data files and assessment of full-history data provenance (lineage). Developed tools generate tables and charts, which facilitate the comparison and analysis of datasets. Also, resulting data helped to develop a universal data model for optimal storing of OpenStreetMap full-history data in the form of a relational database. Databases for several pilot sites were evaluated by two use cases. First, a number of intrinsic data quality indicators and related metrics were implemented. Second, a framework for the inventory of spatial distribution of massive data uploads is discussed. Both use cases confirm the effectiveness of the proposed data-type analysis and derived relational data model.

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