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Data-knowledge co-driven innovations in engineering and management.

Yingji Xia1, Xiqun Michael Chen1, Sudan Sun2

  • 1Institute of Intelligent Transportation Systems, College of Civil Engineering and Architecture, Zhejiang University, Hangzhou, China.

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Summary
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This study introduces data-knowledge co-driven innovations for intelligent engineering and management. It advocates for interdisciplinary approaches to tackle complex data utilization challenges in modern applications.

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Area of Science:

  • Engineering and Management Science
  • Data Science
  • Innovation Studies

Background:

  • Modern intelligent engineering and management demand sophisticated data utilization.
  • Existing methodologies face challenges with complex, evolving data landscapes.

Discussion:

  • Proposes data-knowledge co-driven innovations as a solution.
  • Highlights the integration of data and knowledge for enhanced decision-making.
  • Emphasizes the need for advanced data analytics and knowledge representation.

Key Insights:

  • Data-knowledge co-driven approaches offer a novel framework for innovation.
  • Interdisciplinary methodologies are crucial for addressing multifaceted engineering and management problems.
  • Synergistic utilization of data and knowledge enhances problem-solving capabilities.

Outlook:

  • Advocates for the widespread adoption of these methodologies in diverse applications.
  • Suggests future research directions in hybrid intelligent systems.
  • Predicts significant advancements in intelligent engineering and management through this paradigm shift.