Dataset 2017 - Open Dataset and Software Track

One aspect of MMSys that we encourage is the reproducibility of research work and the use of common artefacts (open dataset, source code, ...). Sharing artefacts is a way to advance the field, which allows others to replicate research results more easily, to build and improve multimedia systems. The "Open Dataset and Source Code Track" provides an opportunity for researchers and practitioners to make their work available and citable. Authors publishing artefacts will benefit by increasing the public awareness of their effort.
The two main artefacts we are looking for are Datasets and Source Code. In both cases, the accepted papers that describe the artefacts will be included in the conference proceedings. In addition, the accepted papers will be especially visible on the ACM Digital Libraries with the appropriate "ACM reproducibility badge" http://www.acm.org/publications/policies/artifact-... The authors of accepted artefacts will be invited to present their work at the MMSys 2017 "Open Dataset and Source Code Track". In addition:
the authors of accepted datasets will have the opportunity to have their dataset hosted from MMSys for at least five years as well as the dataset being listed in Qualinet Databases.
the authors of accepted source code will be invited to demonstrate their software as part of the regular conference program.
Authors are encouraged to prepare as much documentation as possible, including examples of how the provided artefact might be used as well as the motivation for it. Papers should be from 2 to 6 pages long (in PDF format) prepared in the ACM style and written in English. Regarding the submission of dataset, the authors should make their data or code available by providing a public URL for download. Regarding the submission of source code, the software must be licensed in such a manner that it can be used free of charge in academic and research settings. All source code, license, installation instructions, and other documentation must be available on a public web page or on publicly available software repositories (for example GitHub and Bitbucket).
All submissions will be peer-reviewed by at least two members of the technical program committee of the MMSys 2017. Criteria of selection include:
Datasets: The collection methodology and the value of the dataset as a resource for the research community.
Source Code: The broad applicability and potential impact, novelty, technical depth, demo suitability