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EVKG: An interlinked and interoperable electric vehicle knowledge graph for smart transportation system

  • Yanlin Qi
  • , Gengchen Mai*
  • , Rui Zhu
  • , Michael Zhang
  • *Corresponding author for this work

Research output: Contribution to journal › Article (Academic Journal) › peer-review

30 Citations (Scopus)

Abstract

Over the past decade, the electric vehicle (EV) industry has experienced unprecedented growth and diversification, resulting in a complex ecosystem. To effectively manage this multifaceted field, we present an EV-centric knowledge graph (EVKG) as a comprehensive, cross-domain, extensible, and open geospatial knowledge management system. The EVKG encapsulates essential EV-related knowledge, including EV adoption, EV supply equipment, and electricity transmission network, to support decision-making related to EV technology development, infrastructure planning, and policy-making by providing timely and accurate information and analysis. To enrich and contextualize the EVKG, we integrate the developed EV-relevant ontology modules from existing well-known knowledge graphs and ontologies. This integration enables interoperability with other knowledge graphs in the Linked Data Open Cloud, enhancing the EVKG's value as a knowledge hub for EV decision-making. Using six competency questions, we demonstrate how the EVKG can be used to answer various types of EV-related questions, providing critical insights into the EV ecosystem. Our EVKG provides an efficient and effective approach for managing the complex and diverse EV industry. By consolidating critical EV-related knowledge into a single, easily accessible resource, the EVKG supports decision-makers in making informed choices about EV technology development, infrastructure planning, and policy-making. As a flexible and extensible platform, the EVKG is capable of accommodating a wide range of data sources, enabling it to evolve alongside the rapidly changing EV landscape.

Original languageEnglish
Pages (from-to)949-974
Number of pages26
JournalTransactions in GIS
Volume27
Issue number4
Early online date23 May 2023
DOIs
Publication statusPublished - 2 Jun 2023

Bibliographical note

Funding Information:
We would like to thank Professor Krzysztof janowicz for his suggestions on EVKG ontology design. This work is mainly funded by University of Georgia and University of California Davis.

Publisher Copyright:
© 2023 John Wiley & Sons Ltd.

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