Sciunits: Reusable Research Objects
Not on the map. Why?
Abstract (arXiv)
Science is conducted collaboratively, often requiring knowledge sharing about computational experiments. When experiments include only datasets, they can be shared using Uniform Resource Identifiers (URIs) or Digital Object Identifiers (DOIs). An experiment, however, seldom includes only datasets, but more often includes software, its past execution, provenance, and associated documentation. The Research Object has recently emerged as a comprehensive and systematic method for aggregation and identification of diverse elements of computational experiments. While a necessary method, mere aggregation is not sufficient for the sharing of computational experiments. Other users must be able to easily recompute on these shared research objects. In this paper, we present the sciunit, a reusable research object in which aggregated content is recomputable. We describe a Git-like client that efficiently creates, stores, and repeats sciunits. We show through analysis that sciunits repeat computational experiments with minimal storage and processing overhead. Finally, we provide an overview of sharing and reproducible cyberinfrastructure based on sciunits gaining adoption in the domain of geosciences.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 18 Jul 2017.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2022: 1; 2023: 0; 2024: 0; 2025: 1; 2026: 1.
3 papers.
- 2022A domain-specific language for describing machine learning datasetscited by 12
- 2025AI-Generated Code Is Not Reproducible (Yet): An Empirical Study of Dependency Gaps in LLM-Based Coding Agentscited by 5
- 2026Code That Works, Environments That Don't: Measuring Environment Reproducibility in AI-Generated Softwarecited by 0
- 2026Code That Works, Environments That Don't: Measuring Environment Reproducibility in AI-Generated Software30 Sep 2026
- 2025AI-Generated Code Is Not Reproducible (Yet): An Empirical Study of Dependency Gaps in LLM-Based Coding Agents26 Dec 2025
- 2022A domain-specific language for describing machine learning datasets5 Jul 2022