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. createPull(name : String, pushID : int) :PullFeed(name); call Pull(name);
Distributed wiki' is a generic term covering various systems, including 'peer-to-peer wiki', 'mobile wiki', 'offline wiki', 'federated wiki' and others. Distributed wikis distribute their pages among the sites of autonomous participants to address various motivations, including high availability of data, new collaboration models and different viewpoints of subjects. Although existing systems share some common basic concepts, it is often difficult to understand the specificity of each one, the underlying complexities or the best context in which to use it. In this paper, we define, classify and characterize distributed wikis. We identify three classes of distributed wiki systems, each using a different collaboration model and distribution scheme for its pages: highly available wikis, decentralized social wikis and federated wikis. We classify existing distributed wikis according to these classes. We detail their underlying complexities and social and technical motivations. We also highlight some directions for research and opportunities for new systems with original social and technical motivations.
Distributed Version Control Systems (DVCS) such as Git or Mercurial allow community of developers to coordinate and maintain well known software such as Linux operating system or Firefox web browser. The Push-Pull-Clone (PPC) collaboration model used in DVCS generates PPC social network where DVCS repositories are linked by push/pull relations. Unfortunately, DVCS tools poorly interoperate and are not navigable. The first issue prevents the development of generic tools and the second one prevents network analysis. In this paper, we propose to reuse semantic web technologies to transform any DVCS system into a social semantic web one. To achieve this objective, we propose SCHO+ a lightweight ontology that allows to represent causal history sharing. This ontology allows each node of the PPC social network to publish semantic datasets. Next, these semantic datasets can be queried with link transversal based query execution for metrics computation and PPC social network discovery. We experimented PPC network discovery and divergence metrics on real data from some representative projects managed by different DVCS tools.
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