Multimedia Datasets for Repeatable Experimentation (SS3:MDRE)

 

Information retrieval and multimedia content access has a long history of comparative evaluation and many of the advances in the area over the past decade can be attributed to the availability of open datasets that support comparative and repeatable experimentation. Sharing data and code to allow other researchers to replicate research results is needed in the multimedia modeling field and this will help to improve the performance of systems and the reproducibility of papers published. Researchers within the multimedia community will be encouraged to submit their datasets to this special session. Together with the dataset, authors are asked to provide a paper describing its motivation, design, and usage, a brief summary of the experiments performed to date on the dataset, as well as discussing the way it can be useful to the community.

The benefits for authors who successfully submit are:

  • – Accepted contributions will be included in the conference proceedings
  • – Accepted contributions will be listed in a recognized index of multimedia datasets thereby increasing their visibility
  • – Authors of accepted contributions will be invited to present their dataset as part of the special session at MMM2019

Regarding the submission of a dataset, the authors should make it available by providing a public URL for download, as mentioned above, and agree to the link being maintained on an MMM datasets dedicated site. All datasets must be licensed in such a manner that it can be legally and freely used with all appropriate ethical approvals completed. Authors are encouraged to prepare appropriate and helpful documentation to accompany the dataset, including examples of how it can be used by the community, examples of successful usage and restrictions on usage.

Session organizers:

  • – Cathal Gurrin (Dublin City University, Ireland)
  • – Duc-Tien Dang-Nguyen (Dublin City University, Ireland)
  • – Klaus Schoeffmann (Klagenfurt University, Austria)
  • – Björn Þór Jónsson (IT University of Copenhagen, Denmark)
  • – Michael Riegler (Center for Digitalisation and Engineering & University of Oslo, Norway)
  • – Luca Piras (University of Cagliari, Italy)