Call for Papers

The first goal of this workshop is to present insights gained from experimental results in the area of data management systems. The second goal is to promote the scientific validation of experimental results in the database community and facilitate the emergence of an accepted methodology for gathering, reporting, and sharing performance measures in the data management community.

Current conferences and/or journals do not encourage submission of mostly (or purely) experimental results. It is often difficult or impossible to reproduce the experimental results being published, either because the source code of research prototypes is not made available or because the experimental framework is under documented. Most performance studies have limited depth because of space limitations. Their validity is limited in time because assumptions made in the experimental framework become obsolete.

This workshop is meant as a forum for presenting quantitative evaluation of various data management techniques and systems. We invite the submission of original results from researchers, practitioners and developers. Of particular interest are:

  • performance comparisons between competing techniques,
  • studies revisiting published results,
  • unexpected performance results on rare but interesting cases,
  • negative results,
  • scalability experiments.
We also invite contributions that quantify the performance of deployed applications of data management systems.

To be considered, submissions should present a reproducible experimental framework. Based on the information presented in the paper, it should be possible for a reader to:
  • install and configure the system being studied,
  • reproduce the workload,
  • run the experiments and perform the measurements being reported.
Note that the above requirements do not imply that the software used in the presented measures should be open source. Performance studies on systems whose access is in some ways restricted should very clearly state the version, distribution, and all relevant configuration parameters, enabling a willing reader to reproduce the experiment, once he or she has gained possession of the software.