Provenance of Visual Interpretations in the Exploration of Data

UoM administered thesis: Phd

  • Authors:
  • Aqeel Al-Naser

Abstract

The thesis addresses the problem of capturing and tracking multi-user interpretations of 3D spatial datasets. These interpretations are completed after the end of the visualization pipeline to identify and extract features of interest, and are subjective to human intuition and knowledge. Users may also assess regions of these interpretations. Consequently, the thesis proposes a provenance-enabled interpretation pipeline. It adopts and extends the W3C PROV data model, producing a provenance model for visual interpretations. This was implemented for seismic imaging interpretation in a proof-of-concept prototype architecture and application. Accumulation of users' interpretations and annotations are captured by the provenance model in a fine-grained form. The captured provenance information can be utilised to filter data.The work of this thesis was evaluated in three parts. First, a usability evaluation by geoscientists was conducted by postgraduate students in the field of geoscience to illustrate the system's ability in allowing users to amend others' interpretations and trace the history of amendments. Second, a conceptual evaluation of this research was approached by interviewing domain experts. The importance of this research to the industry was assured. Interviewees perceived and shared potential implementations of this work in the workflow of seismic interpretation. Limitations and concerns of the work were highlighted. Third, a performance evaluation was conducted to illustrate the behaviour of the architecture on commodity machines as well as on a multi-node parallel database, such that a new functionality in fine-grained provenance can be implemented simply but with an acceptable performance in realistic visualization tasks. The measures suggested that the current implementation achieved an acceptable performance in comparison to conventional methods.The proposed provenance model in an interpretation pipeline is believed to be a promising shift in methods of data management and storage which can record and preserve interpretations by users as a result of visualization. The approach and software development in this thesis represented a step in this direction.

Details

Original languageEnglish
Awarding Institution
Supervisors/Advisors
  • John Brooke (Supervisor)
Award date1 Aug 2015