The Open Story Model (OSM): transforming big data into interactive narratives

Big Data has various formats, substandard data models, and diverse semantics. Understanding this vast, continuous, and constantly evolving data is challenging and requires sophisticated data science pipelines that not only turn the raw data into contextual knowledge and insights but also generate meaningful and personalized narratives to facilitate the understanding and interpretation of the Big Data. Existing methods often fail to provide the necessary context and personalization to make data actionable to diverse stakeholders. To achieve this goal, we introduce the Open Story Model (OSM), a novel data science pipeline that: i) transforms the unprocessed data into a structured Knowledge Graph based on a unified graph data model of typed nodes and edges; ii) generates meaningful narratives on top of the Knowledge Graph; and (iii) link narratives to construct personalized stories for various stakeholders based on their goals. We model each story as an interactive data product to allow stakeholders to engage with and manipulate data in real-time to explore, analyze, and visualize the information in ways that suit their specific needs and questions. To demonstrate the practical application and efficacy of the OSM framework, we focus on a use case in the health domain and explore how OSM facilitates the detection and prediction of cancer by transforming the data into personalized stories for various stakeholders.