Quoting document parts by cut and paste is the most popular method of aggregating complex data into an expert review or a business intelligence data stream. But doing so breaks the connection between the selected quote and the original document. The second possible origin of missing links between the data source and data use is the document access restriction. In this study we introduce and advocate a novel knowledge management framework with fine-grained text cross-referencing and transclusion features. On top of this, we apply a sticky access control scheme, which enables the permission profile to be applied uniformly across the data use points. Application of the Datagrav framework to the real life enterprise business intelligence data stream is discussed. The observed system behaviour is in good alignment with generic models of social change, which gives additional credibility to the proposed approach to building transclusion-enabled cooperative information systems.
Kochuguev, Sergey and Maslov, Andrey, "DATAGRAV: A FRAMEWORK FOR KNOWLEDGE SHARING USING TRANSCLUSION ENABLED COLLABORATION MEDIA" (2016). Research Papers. 18.