Data Network Game: Enabling Collaboration via Data Mesh

Organizations aim to transform raw data into valuable insights using advanced analytical methods. Since data can be replicated and shared, multiple actors can simultaneously utilize the same information. This study presents the Data Network, a theoretical framework representing potential collaborations among organizations sharing data in large-scale big data projects, using Data Mesh as a supporting architecture. The Data Network Game (DNG) extends this model by applying game theory to analyze inter-organizational collaborations, incorporating market-imposed constraints that limit compatibility. Various scenarios, defined by distinct benefit and cost functions, are explored to understand their impact on coalition formation and market dynamics. A simplified theoretical example shows how coalitions can achieve greater value through collaboration than by acting independently. This model serves as a practical tool for assessing the trade-offs of cooperation and offers insights into manag ing emerging data-driven markets.