| Title | A Data Provenance Visualization Approach |
| Publication Type | Conference Paper |
| Year of Publication | 2018 |
| Authors | Yazici, I. M., Karabulut, E., Aktas, M. S. |
| Conference Name | 2018 14th International Conference on Semantics, Knowledge and Grids (SKG) |
| Keywords | Big Data, Classification algorithms, component, composability, Data analysis, data lineage, data provenance, data provenance visualization approach, data visualisation, Data visualization, Human Behavior, metadata, Metrics, open source visualization tool, Prototypes, PROV-O, Provenance, provenance visualization, pubcrawl, public domain software, Resiliency, social networking (online), Tools, W3C-PROV-O specification compatible provenance data |
| Abstract | Data Provenance has created an emerging requirement for technologies that enable end users to access, evaluate, and act on the provenance of data in recent years. In the era of Big Data, the amount of data created by corporations around the world has grown each year. As an example, both in the Social Media and e-Science domains, data is growing at an unprecedented rate. As the data has grown rapidly, information on the origin and lifecycle of the data has also grown. In turn, this requires technologies that enable the clarification and interpretation of data through the use of data provenance. This study proposes methodologies towards the visualization of W3C-PROV-O Specification compatible provenance data. The visualizations are done by summarization and comparison of the data provenance. We facilitated the testing of these methodologies by providing a prototype, extending an existing open source visualization tool. We discuss the usability of the proposed methodologies with an experimental study; our initial results show that the proposed approach is usable, and its processing overhead is negligible. |
| DOI | 10.1109/SKG.2018.00019 |
| Citation Key | yazici_data_2018 |
A Data Provenance Visualization Approach