Leveraging Standards in Model-Centric Geospatial Knowledge Graph Creation - Archive ouverte HAL Access content directly
Conference Papers Year : 2022

Leveraging Standards in Model-Centric Geospatial Knowledge Graph Creation

Diego Vinasco-Alvarez

Abstract

Understanding the complex urban landscapes of cities and their evolution is becoming an ever more essential area of research for urbanists, city planners, historians, and industry leaders. Toward this endeavor, data-driven 3D semantic city models can be implemented to create tools for understanding, simulating, and modeling these urbanization processes and many other urban phenomena. These implementations often require integrating multidimensional (2D/3D, temporal, and thematic), heterogeneous, and multisource urban data to provide users with more complete views of the changing urban landscape. In recent years, researchers have turned toward Semantic Web technologies such as knowledge graphs as common platforms for integrating these data and their underlying data models. However, simple transformation or conversion of urban data towards these formats is prone to data loss, and integration of urban data model standards lacking interoperability poses its own challenges. This work proposes a model-centric urban data transformation approach towards Semantic Web data formats, based on international standards for facilitating the integration of these urban data and promoting their interoperability in the context of multidimensional city modeling.
Fichier principal
Vignette du fichier
eswc22phdsymposium.pdf (620.38 Ko) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-03693607 , version 1 (10-06-2022)

Identifiers

  • HAL Id : hal-03693607 , version 1

Cite

Diego Vinasco-Alvarez. Leveraging Standards in Model-Centric Geospatial Knowledge Graph Creation. ESWC 2022 Ph.D. Symposium, May 2022, Hersonissos, Greece. ⟨hal-03693607⟩
84 View
159 Download

Share

Gmail Mastodon Facebook X LinkedIn More