Fundamental research for hypothesis generation and explanation in social big data applications

2023 Fiscal Year Final Research Report

• Project/Area Number: 20K12081
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Review Section: Basic Section 62020:Web informatics and service informatics-related
• Research Institution: Tokyo Metropolitan University
• Principal Investigator: Ishikawa Hiroshi 東京都立大学, システムデザイン研究科, 特任教授 (60326014)
• Co-Investigator(Kenkyū-buntansha): 廣田 雅春 岡山理科大学, 総合情報学部, 講師 (70750628)
• Project Period (FY): 2020-04-01 – 2024-03-31
• Keywords: ビッグデータ / モデル / 仮説生成 / 説明基盤

Outline of Final Research Achievements

We proposed a data model using SQL that can describe the subsystem processes of data management and data analysis based on concepts at different levels in a high-level form, and use it to describe the entire hypothesis generation procedure in social big data applications and we showed that it is possible. In addition to systematizing the difference method, we also considered a hypothesis generation method that focuses on data overlapping and mutual complementation. We implemented an explanatory method that does not depend on individual analysis models based on explanatory functions based on attributes or components, and confirmed its validity. With the cooperation of JAXA, the Tokyo Metropolitan Government, and others, we verified the validity of the developed technology by applying it to multiple use cases. The results have been published in several publications (Japanese and English), journals, and international conferences.

Free Research Field

ビッグデータ

Academic Significance and Societal Importance of the Research Achievements

本研究は当該分野の学術的研究(ソーシャルビッグデータサイエンス)の地平を自然科学，医学などへ広げることが期待できる．構築した仮説生成方法論を社会基盤的応用に適用して，方法論の再利用可能性を示すことにより，その妥当性の検証を行い，統合モデルの理論とその実践の道を開き，さらに統合的説明基盤の適用により，ソーシャルビッグデータの利活用と流通を促進する．それらを媒介として，これまで縁遠かった異業種セクタ（JAXA，自動車関連企業，観光系シンクタンクなど）が協業できるようなダイナミックな知的社会（Society5.0）の実現を加速することが期待できる点で，本研究は創造的であり社会的意義も十分に高い.