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Data sharing behavior is a complex phenomenon influenced by both individual and institutional factors, as well as the availability of internal resources and facilitating conditions. We study factors affecting data sharing by integrating two approaches: at first we test theory-driven relationships within a Structural Equation Modeling framework, then we explore data dependency structure within a data-driven perspective, using Bayesian Network models. The proposed approach is flexible and may be used to implement future intervention strategies aimed at enhancing data sharing practice.

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Exploring Data Sharing Behaviour Using both Theory and Data-Driven Methods

  • 会议论文

  • 发表日期：

    2025年

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  • Federica Cugnata,
  • Chiara Brombin,
  • Roberto Buccione,
  • Clelia Di Serio

摘要

Data sharing behavior is a complex phenomenon influenced by both individual and institutional factors, as well as the availability of internal resources and facilitating conditions. We study factors affecting data sharing by integrating two approaches: at first we test theory-driven relationships within a Structural Equation Modeling framework, then we explore data dependency structure within a data-driven perspective, using Bayesian Network models. The proposed approach is flexible and may be used to implement future intervention strategies aimed at enhancing data sharing practice.