Talks and Poster Presentations (with Proceedings-Entry):
C. Bors, T. Gschwandtner, S. Miksch, J. Gärtner:
"QualityTrails: Data Quality Provenance as a Basis for Sensemaking";
Talk: IEEE VIS Workshop on Provenance for Sensemaking,
2014-11-10; in: "Proceedings of the IEEE VIS Workshop on Provenance for Sensemaking",
K. Xu, S. Attfield, T. J. Jankun-Kelly (ed.);
Visual Analytics prototypes increasingly support human sensemaking through providing Provenance information. For data analysts the challenge of knowledge generation starts with assessing the quality of a data set, but Provenance is not yet utilized to aid this task. This position paper aims at characterizing the complexity of Visual Analytics methods introducing Provenance in Data Quality by highlighting the challenges of (1) generating Provenance from Data Quality Control and (2) sensemaking based on Data Quality Provenance.
data provenance, analytic provenance, sensemaking, data quality, quality metrics, visual data analysis
Electronic version of the publication:
Project Head Silvia Miksch:
CVAST: Centre for Visual Analytics Science and Technology (Laura Bassi Centre of Expertise)
Created from the Publication Database of the Vienna University of Technology.