# Terminologies for Reproducible Research

arXiv: https://arxiv.org/abs/1802.03311 · HTML: https://mlsanity.com/paper/1802.03311/

## Key facts

- Cited by 11 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Feb 2018.

## Built on by (most cited first, 11 of 11)

- [HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO](https://mlsanity.com/paper/2109.06716/) (2021)
- [Randomness In Neural Network Training: Characterizing The Impact of Tooling](https://mlsanity.com/paper/2106.11872/) (2021)
- [Position: Why We Must Rethink Empirical Research in Machine Learning](https://mlsanity.com/paper/2405.02200/) (2024)
- [Towards Better User Studies in Computer Graphics and Vision](https://mlsanity.com/paper/2206.11461/) (2022)
- [What is Reproducibility in Artificial Intelligence and Machine Learning Research?](https://mlsanity.com/paper/2407.10239/) (2024)
- [Reproducibility of Machine Learning: Terminology, Recommendations and Open Issues](https://mlsanity.com/paper/2302.12691/) (2023)
- [Automating Computational Reproducibility in Social Science: Comparing Prompt-Based and Agent-Based Approaches](https://mlsanity.com/paper/2602.08561/) (2026)
- [Reproducible and Portable Big Data Analytics in the Cloud](https://mlsanity.com/paper/2112.09762/) (2021)
- [Predicting Parkinson's disease trajectory using clinical and functional MRI features: a reproduction and replication study](https://mlsanity.com/paper/2403.15405/) (2024)
- [Coding-agents can replicate scientific machine learning papers](https://mlsanity.com/paper/2607.02134/) (2026)
- [Defining Replicability of Prediction Rules](https://mlsanity.com/paper/2305.01518/) (2023)

## Abstract (arXiv)

Reproducible research---by its many names---has come to be regarded as a key concern across disciplines and stakeholder groups. Funding agencies and journals, professional societies and even mass media are paying attention, often focusing on the so-called "crisis" of reproducibility. One big problem keeps coming up among those seeking to tackle the issue: different groups are using terminologies in utter contradiction with each other. Looking at a broad sample of publications in different fields, we can classify their terminology via decision tree: they either, A---make no distinction between the words reproduce and replicate, or B---use them distinctly. If B, then they are commonly divided in two camps. In a spectrum of concerns that starts at a minimum standard of "same data+same methods=same results," to "new data and/or new methods in an independent study=same findings," group 1 calls the minimum standard reproduce, while group 2 calls it replicate. This direct swap of the two terms aggravates an already weighty issue. By attempting to inventory the terminologies across disciplines, I hope that some patterns will emerge to help us resolve the contradictions.