Study on construction and transfer of knowledge graphs from heterogeneous data for predicting traffic problems

2020 Fiscal Year Final Research Report

• Project/Area Number: 19K24375
• Research Category: Grant-in-Aid for Research Activity Start-up
• Allocation Type: Multi-year Fund
• Review Section: 1002:Human informatics, applied informatics and related fields
• Research Institution: National Institute of Advanced Industrial Science and Technology (2020); National Institute of Maritime, Port and Aviation Technology (2019)
• Principal Investigator: Egami Shusaku 国立研究開発法人産業技術総合研究所, 情報・人間工学領域, 研究員 (20846000)
• Project Period (FY): 2019-08-30 – 2021-03-31
• Keywords: ナレッジグラフ / オントロジー / セマンティックWeb / 航空交通管理 / 相互運用性 / 交通問題

Outline of Final Research Achievements

This study integrated traffic-related heterogeneous data as a knowledge graph (KG) and made it possible to search heterogeneous information and predict traffic problems. In air traffic management (ATM), there is a problem in terms of semantic interoperability between heterogeneous information systems. In this study, we proposed a method for enriching semantic interoperability in ATM by KG technologies. As a result, we confirmed that the proposed method integrated ATM-related data at the spatiotemporal conceptual level and enabled the inference search of problems occurring on air routes. On the other hand, traffic-related information is accumulated in different formats, even in a large private area such as a campus. Therefore, we proposed a method to analyze and predict traffic problems by integrating heterogeneous information as KG.

Free Research Field

セマンティックWeb，オントロジー

Academic Significance and Societal Importance of the Research Achievements

異なる場所で集積される異なるデータでは，語彙，対象範囲，粒度，設計における視点などが異なるため，異種情報間の横断的な連携と問題予測等へ効果的な応用が困難である．本研究はこの問題を解決するため，概念間の関係を明示的に記述するオントロジーの構築・マッピング・応用の手法の提案しており，学術的な意義があると考える．さらに，航空交通情報共有基盤のテストシステムへの導入により，実用性についても考察しており，社会的意義があると考える．