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ACM REP 2023 : ACM Conference on Reproducibility and Replicability | |||||||||||||||
Link: https://acm-rep.github.io/2023 | |||||||||||||||
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Call For Papers | |||||||||||||||
2023 ACM Conference on Reproducibility and Replicability (ACM REP 2023)
June 27-29, 2023 UC Santa Cruz | Santa Cruz, California | #acmrep The ACM REP international conference aims to bring together experts and practitioners engaged in the advancement and conduct of reproducible science in computing disciplines. The first-of-its-kind conference will serve as a premier forum for the exchange and presentation of the concepts, tools, techniques, practice and state-of-art in reproducible science. The conference committee invites original research contributions and practical system designs, implementations and evaluations on several topics relating to reproducibility and replicability. The ACM REP program will consist of peer-reviewed articles, invited talks, panels, and posters, and demonstrations. The ACM REP conference series is associated with the ACM Emerging Interest Group for Reproducibility and Replicability. All accepted papers will be published by ACM - International Conference Proceedings Series (ICPS) and will be available in the ACM Digital Library. ACM REP 2023 invites submissions in several categories as described below with focus on computing disciplines within computer science and across scientific computing disciplines of biology, chemistry, physics, astronomy, genomics, geosciences, etc. The conference encourages submissions in which experimental results are reproducible in of themselves and, if not, then sufficiently documents the reproducibility experience. Topics of interest include, but are not limited to, the following as they relate to various aspects of reproducibility and replicability. Reproducibility Concepts Experiment dependency management. Experiment portability for code, performance, and related metrics. Software and artifact packaging and container-related reproducibility methods. Approximate reproducibility. Record and replay methods. Data versioning and preservation. Provenance of data-intensive experiments. Automated experiment execution and validation. Reproducibility-aware computational infrastructure. Experiment discoverability for re-use. Approaches for advancing reproducibility. Reproducibility Experiences Experience of sharing and consuming reproducible artifacts. Conference-scale artifact evaluation experiences and practices. Experiences as part of hackathons and summer programs. Classroom and teaching experiences. Usability and adaptability of reproducibility frameworks into already-established domain-specific tools. Frameworks for sociological constructs to incentivize paradigm shifts. Policies around publication of articles/software. Experiences within computational science communities Broader Reproducibility Cost-benefit analysis frameworks for reproducibility. Novel methods and techniques that impact reproducibility. Reusability, repurposability, and replicability methods. Long-term artifact archiving and verification/testing for future reproducibility. |
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