Generating Spatial Knowledge Graphs with 2D Indoor Floorplan Data: A Case Study on the Jeonju Express Bus Terminal
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Published:2024-02-09
Issue:2
Volume:13
Page:52
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ISSN:2220-9964
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Container-title:ISPRS International Journal of Geo-Information
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language:en
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Short-container-title:IJGI
Author:
Jang Hanme1ORCID, Yu Kiyun12, Kim Jiyoung3ORCID
Affiliation:
1. Department of Civil and Environmental Engineering, Seoul National University, Seoul 08826, Republic of Korea 2. Institute of Engineering Research, Seoul National University, Seoul 08826, Republic of Korea 3. Social Eco-Tech Institute (SETI), KonKuk University, Seoul 05029, Republic of Korea
Abstract
With the boom in online information, knowledge graphs like Freebase, Wikidata, and YAGO have emerged, thanks to the introduction of the RDF (Resource Description Framework). As RDF data grew, more and more spatial data was incorporated into it. While we have a lot of 2D data for outdoor spaces, mapping indoor spaces in 3D is challenging because it is expensive and time-consuming. In our research, we turned 2D blueprints into detailed 3D maps and then translated this into RDF format. We used the Jeonju Express Bus Terminal in South Korea as our test case. We made an automated tool that can turn 2D spatial data into 3D data that fits the IndoorGML standard. We also introduced terms like ‘loc’, ‘indoorgml-lite’, and ‘bloc’ to describe indoor spaces in the RDF format. Once we put our data into a GraphDB database, we could easily search for specific details and routes inside buildings. This work fills a significant gap in knowledge graphs concerning indoor spaces. However, the production of large-scale data across varied areas remains a challenge, pointing towards future research directions for more comprehensive indoor spatial information systems.
Funder
Korea Agency for Infrastructure Technology Advancement National Research Foundation of Korea
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