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Data Friction: Physics-Inspired Metaphor to Evaluate the Technical Difficulties in Trustworthy Data Sharing

  • Matteo Falconi,
  • Giacomo Lombardo,
  • Pierluigi Plebani,
  • Sebastian Werner

摘要

Data sharing between organizations is becoming an ever-increasing necessity. Data sharing allows organizations to improve business processes that depend on what happens in other organizations, just as having data from other organizations can enrich data analysis models. However, even though data is seen as the new oil, it does not move like oil. There are several technical and organizational factors that make data sharing difficult. In this work, inspired by the definition of friction in physics, we want to provide a first friction model that is able to capture the elements that hinder data sharing. The proposed model hypothesizes that through the adoption of data mesh in conjunction with a service-oriented sharing approach, we can utilize this model to reduce and reuse the effort for sharing data.