D03 | Visual Exploration and Analysis of Provenance Data

Prof. Melanie Herschel, Universität Stuttgart
Email | Website

Melanie Herschel

Prof. Ulrik Brandes, Universität Konstanz
Email | Website

Ulrik Brandes

Houssem Ben Lahmar, Universität Stuttgart – Email

To analyze or debug complex data processing applications, or to ensure their understandability and repeatability, provenance techniques are increasingly being deployed, resulting in large volumes and a wide variety of provenance data. The long-term goal of this project is to leverage visualization techniques to efficiently and effectively explore provenance data. In the first funding period, we will focus on properly visualizing the full provenance data generated for one run of a data-processing pipeline. This involves both quantifiably identifying suited visualizations for various provenance types and ensuring user-friendly provenance data generation and visualization in existing data processing pipelines.

Research Questions

What are suitable visualization techniques for different settings defined by varying types of provenance and applications?

Which metrics can quantitatively assess provenance data visualization quality?

How can such metrics support tuning processes generating and managing provenance data?

Which types of provenance are best suited to achieve the goals of reproducibility and predictability for selected visual computing processes?

Visualizing and Interacting with Provenance Data

Publications

  1. Lahmar, Houssem Ben; Herschel, Melanie (2017): „Provenance-based Recommendations for Visual Data Exploration“. In: International Workshop on Theory and Practice of Provenance (TAPP). (International Workshop on Theory and Practice of Provenance (TAPP)).
  2. Baazizi, Mohamed Amine; Lahmar, Houssem Ben; Colazzo, Dario; u. a. (2017): „Schema Inference for Massive JSON Datasets“. In: Conference on Extending Database Technology (EDBT). (Conference on Extending Database Technology (EDBT)), S. 222–233.
  3. Herschel, Melanie; Hlawatsch, Marcel (2016): „Provenance: On and Behind the Screens.“. In: Özcan, Fatma; Koutrika, Georgia; Madden, Sam (Hrsg.) ACM International Conference on the Management of Data (SIGMOD). ACM (ACM International Conference on the Management of Data (SIGMOD)), S. 2213–2217.
  4. Diestelkämper, Ralf; Herschel, Melanie; Jadhav, Priyanka (2017): „Provenance in DISC Systems: Reducing Space Overhead at Runtime“. In: International Workshop on Theory and Practice of Provenance (TAPP). (International Workshop on Theory and Practice of Provenance (TAPP)).