HOKKAIDO UNIVERSITY INFORMATION INITIATIVE CENTER

Knowledge Generation Infrastructure Research Division

Research Overview

The Knowledge Generation Infrastructure Research Division was established in 2026 to research, develop, and deploy Knowledge Generation Foundations centered on research data and artificial intelligence (AI). The division focuses on designing and implementing an integrated infrastructure that combines research data with advanced AI technologies. Through this effort, it aims to enhance research productivity, enable data-driven discovery, and strengthen the overall research capabilities of Hokkaido University.

Mission

In recent years, scientific research has experienced a rapid increase in both the volume and complexity of data. Consequently, research paradigms that systematically manage large-scale datasets and apply advanced analytical techniques to generate new knowledge are becoming essential.
The division addresses these evolving demands by advancing Knowledge Generation Foundations that integrate research data with AI technologies. Its mission is to facilitate efficient knowledge creation, promote data-driven research practices, and reinforce institutional research excellence.

Roles

The division is responsible for the design, development, and operation of core infrastructure for knowledge generation, including research data platforms and AI integration systems. It leads initiatives to ensure these infrastructures are effectively utilized across the university.
Key responsibilities include:
• Developing systems that manage the full lifecycle of research data—from generation and accumulation to sharing, analysis, and publication
• Enabling seamless integration of data and AI to accelerate knowledge discovery
• Promoting research digital transformation (DX) and AI transformation (AIX) in collaboration with university-wide DX initiatives
• Supporting efficient, scalable, and interoperable research environments

Research Areas

To realize Knowledge Generation Foundations, the division conducts research in the following areas:
• Advanced artificial intelligence and machine learning, including foundation models for generative AI
• Architecture design and optimization of research data infrastructures and knowledge systems
• Lifecycle management technologies for diverse research data (generation, storage, sharing, processing, and publication)
• Metadata schema design and data governance methodologies for heterogeneous scientific data
• Integration of AI with multi-agent simulation for social system analysis and decision support
In addition, the division promotes the digital transformation of traditionally paper-based research records, enabling structured data capture and facilitating AI-driven analysis.

Social Significance

With the advancement of open science, data sharing and reuse have become central to modern research. The division contributes to establishing a “data-driven research ecosystem” that accelerates scientific discovery and innovation.
Furthermore, by leveraging AI and large-scale data analytics for social system modeling and simulation, the division supports evidence-based decision-making and contributes to addressing complex societal challenges, including sustainability.
Ultimately, the Knowledge Generation Infrastructure Research Division aims to establish new paradigms of scientific research by integrating data and AI, fostering continuous knowledge circulation, and generating both academic and societal value.

Staff