Research on Data Provenance Model for Multidisciplinary Collaboration

• Published in: Computer Supported Cooperative Work and Social Computing Vol. 917; pp. 32 - 49
• Main Authors: Yu, Fangyu, Zhou, Beisi, Lu, Tun, Gu, Ning
• Format: Book Chapter
• Language: English
• Published: Singapore Springer 2019; Springer Singapore
• Series: Communications in Computer and Information Science
• Subjects: Core components; Model comparison; Model practice; Multidisciplinary collaboration; Provenance model
• ISBN: 9789811330438; 9811330433
• ISSN: 1865-0929; 1865-0937
• DOI: 10.1007/978-981-13-3044-5_3

Provenance, which can be applied to assure quality, to reinforce reliability, to track fault, and to reproduce process in the end product, refers to record the lifecycle of a piece of data or thing that accounts for its generation, transformation, manipulation, and consumption, together with an explanation of how and why it got to the present place. Recently, due to its extensive applicative domains, the provenance modeling problems have brought to attention of scientific researchers significantly. In this paper, an overview of core components regarding provenance models in existing literature is presented, with a wide width from modelling methods, model comparison, and model practice, to specified issues. In addition, a collaborative model called CollabPG, was built based on the characteristics of multidisciplinary collaboration. Finally, we discussed several issues in relevance with provenance models. This paper mainly presents an overall exploration and analysis, so that potential insights could be provided for both expert and common users to select or design a provenance-based model in arbitrary applications especially multidisciplinary collaboration.