SCHO: An Ontology Based Model for Computing Divergence Awareness in Distributed Collaborative Systems

Abstract

Multi-synchronous collaboration allows people to work concurrently on copies of a shared document which generates divergence. Divergence awareness allows to localize where divergence is located and estimate how much divergence exists among the copies. Existing divergence awareness metrics are highly coupled to their original applications and can not be used outside their original scope. In this paper, we propose the {SCHO} ontology: a unified formal ontology for constructing and sharing the causal history in a distributed collaborative system. Then we define the existing divergence metrics in a declarative way based on this model. We validate our work using real data extracted from software engineering development projects.