Data ShowcaseMSR 2020

The Data Showcase provides a forum to share and discuss important data sets that underpin the work of the Mining Software Repositories community.

Accepted Papers

Call for Papers

Data Showcase papers should describe data sets that are curated by their authors and made available to use by others. Ideally, these data sets should be of value to others in the community, should be preprocessed or filtered in some way, and should provide an easy-to-understand schema. Data showcase papers are expected to include:

• a description of the data source,
• a description of the methodology used to gather the data (including provenance and the tool used to create/generate/gather the data, if any),
• a description of the storage mechanism, including a schema if applicable,
• if the data has been used by the authors or others, a description of how this was done including references to previously published papers,
• a description of the originality of the data set (that is, even if the data set has been used in a published paper, its complete description must be unpublished),
• ideas for future research questions that could be answered using the data set,
• ideas for further improvements that could be made to the data set, and
• any limitations and/or challenges in creating or using the data set.

The data set should be made available at the time of submission of the paper for review, but will be considered confidential until publication of the paper. At the latest upon publication of the paper the authors should archive the data on a persistent repository that can provide a digital object identifier (DOI) such as zenodo.org, figshare.com, Archive.org, or institutional repositories. In this way the data will become citable; the DOI-based citation of the data set should be included in the camera-ready version of the paper.

Data showcase papers are not:

• empirical studies
• tool demos
• or data sets that are
  • based on poorly explained or untrustworthy heuristics for data collection, or
  • result of trivial application of generic tools.

If custom tools have been used to create the data set, we expect the paper to be accompanied by the source code of the tools, along with clear documentation on how to run the tools to recreate the data set. The tools should be open source, accompanied by an appropriate license; the source code should be citable, i.e., refer to a specific release and have a DOI. GItHub provides an easy way to make source code citable. If you cannot provide the source code or the source code clause is not applicable (e.g., because the data set consists of qualitative data), please provide a short explanation of why this is not possible.

Submission

Submit your data paper (maximum 4 pages, plus 1 additional page of references) to EasyChair on or before February 6th, 2020 (abstract due January 30th).

Submitted papers will undergo single-blind peer review. We opt for single-blind peer review (as opposed to the double-blind peer review of the main track) due to the requirement above to describe the ways how data has been used in the previous studies, including the bibliographic reference to those studies. Such reference is likely to disclose the authors’ identity.

To make research data sets and research software accessible and citable, we further encourage authors to attend to the FAIR rules, i.e., data should be: Findable, Accessible, Interoperable, and Reusable.

The submission must conform to the ACM Conference Proceedings Formatting Guidelines (https://www.acm.org/publications/proceedings-template). LaTeX users must use the provided acmart.cls and ACM-Reference-Format.bst without modification, enable the conference format in the preamble of the document (i.e., \documentclass[sigconf,review]{acmart}), and use the ACM reference format for the bibliography (i.e., \bibliographystyle{ACM-Reference-Format}). The review option adds line numbers, thereby allowing referees to refer to specific lines in their comments.

Papers submitted for consideration should not have been published elsewhere and should not be under review or submitted for review elsewhere for the duration of consideration. ACM plagiarism policies and procedures shall be followed for cases of double submission. The submission must also comply with the IEEE Policy on Authorship. Please read the ACM Policy and Procedures on Plagiarism (https://www.acm.org/publications/policies/plagiarism) and the IEEE Plagiarism FAQ (https://www.ieee.org/publications/rights/plagiarism/plagiarism-faq.html) before submitting.

To submit please use the EasyChair link.

Upon notification of acceptance, all authors of accepted papers will be asked to complete a copyright form and will receive further instructions for preparing their camera ready versions. At least one author of each paper is expected to register and present the results at the MSR 2020 conference. All accepted contributions will be published in the conference electronic proceedings.

A selection of the best papers will be invited to EMSE Special Issue.

Important Dates

Abstracts Due: January 30, 2020, 23:59 AOE

Papers Due: February 6, 2020, 23:59 AOE

Author Notification: March 2, 2020

Camera Ready: March 16, 2020, 23:59 AOE

Organization

Olga Baysal, Carleton University, Canada

Bogdan Vasilescu, Carnegie Mellon University, USA