Article
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Preserved in Portico This version is not peer-reviewed
Multisource Spatial Data Integration for Use Cases Applications
Version 1
: Received: 16 December 2021 / Approved: 17 December 2021 / Online: 17 December 2021 (11:15:59 CET)
Version 2 : Received: 6 June 2022 / Approved: 7 June 2022 / Online: 7 June 2022 (11:10:07 CEST)
Version 2 : Received: 6 June 2022 / Approved: 7 June 2022 / Online: 7 June 2022 (11:10:07 CEST)
A peer-reviewed article of this Preprint also exists.
Noardo, F. (2022). Multisource spatial data integration for use cases applications. Transactions in GIS, 26, 2874– 2913. https://doi.org/10.1111/tgis.12987 Noardo, F. (2022). Multisource spatial data integration for use cases applications. Transactions in GIS, 26, 2874– 2913. https://doi.org/10.1111/tgis.12987
Abstract
The reuse and integration of data give big opportunities, supported by the F.A.I.R. data principles. Seamless data integration from heterogenous sources has been interest of the geospatial community for long time. However, 3D city models, BIM and information supporting smart cities present higher semantic and geometrical complexity, which pose new challenges, never tackled in a comprehensive methodology. Building on previous theories and studies, this paper proposes an overarching workflow and framework for multisource (geo)spatial data integration. It starts from the definition of use case-based requirements for the integrated data, guides the analysis of integrability of the involved datasets, suggesting actions to harmonise them, until data merging and validation. It is finally tested and exemplified on a case study. This approach allows the development of consistent, well-documented and inclusive data integration workflows, for the sake of use cases automation in various geospatial domains and the production of Interoperable and Reusable data.
Keywords
data integration; interoperability; harmonization; GeoBIM; metadata
Subject
Engineering, Control and Systems Engineering
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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