Abstract
The need for interpretation of provenance data increases with the introduction of further provenance related IT-systems. The interpretation of data only becomes intuitively with providing good and efficient visualization possibilities. During the development of general provenance visualization techniques, provenance users are classified into groups regarding their view to provenance information. The end-user requirements are evaluated on an abstract level to have a basis for research. Different intentions of end-users regarding provenance are identified and put into relationship with standard visualization types. Examples for standard visualization types are given and a brief forecast to future achievements is made.
Cite
CITATION STYLE
Kunde, M., Bergmeyer, H., & Schreiber, A. (2008). Requirements for a provenance visualization component. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5272, pp. 241–252). Springer Verlag. https://doi.org/10.1007/978-3-540-89965-5_25
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