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A Visualization Architecture for Collaborative Analytical and Data Provenance Activities
2013
2013 17th International Conference on Information Visualisation
When exploring noisy or visually complex data, such as seismic data from the oil and gas industry, it is often the case that algorithms cannot completely identify features of interest. Human intuition must complete the process. Given the nature of intuition, this can be a source of differing interpretations depending on the human expert; thus we do not have a single feature but multiple views of a feature. Managing multi-user and multi-version interpretations, combined with version tracking, is
doi:10.1109/iv.2013.34
dblp:conf/iv/Al-NaserRIB13
fatcat:d5xeinvhkrdhtdnau6q7hz55l4