Related papers: Reproducible Experiment Platform
High-Performance Computing (HPC) platforms enable scientific software to achieve breakthroughs in many research fields such as physics, biology, and chemistry, by employing Research Software Engineering (RSE) techniques. These include 1)…
This paper investigates the conceptual relationship between openness and reproducibility using a model-centric approach, heavily informed by probability theory and statistics. We first clarify the concepts of reliability, auditability,…
Data processing frameworks are an essential part of HEP experiments' software stacks. Frameworks provide a means by which code developers can undertake the essential tasks of physics data processing, accessing relevant inputs and storing…
The LHCb Stripping project is a pivotal component of the experiment's data processing framework, designed to refine vast volumes of collision data into manageable samples for offline analysis. It ensures the re-analysis of Runs 1 and 2…
A complete declarative description of the computational environment is often missing when researchers share their materials. Without such description, software obsolescence and missing system components can jeopardize computational…
Challenges to reproducibility and replicability have gained widespread attention, driven by large replication projects with lukewarm success rates. A nascent work has emerged developing algorithms to estimate the replicability of published…
This paper proposes an interpretable non-model sharing collaborative data analysis method as one of the federated learning systems, which is an emerging technology to analyze distributed data. Analyzing distributed data is essential in many…
The reliability of a high-throughput biological experiment relies highly on the settings of the operational factors in its experimental and data-analytic procedures. Understanding how operational factors influence the reproducibility of the…
Every year the PHENIX collaboration deals with increasing volume of data (now about 1/4 PB/year). Apparently the more data the more questions how to process all the data in most efficient way. In recent past many developments in HEP…
We present an application, EasyScan_HEP, for connecting programs to scan the parameter space of High Energy Physics (HEP) models using various sampling algorithms. We develop EasyScan_HEP according to the principle of flexibility and…
Modern science clearly demands for a higher level of reproducibility and collaboration. To make research fully reproducible one has to take care of several aspects: research protocol description, data access, environment preservation,…
Increased reproducibility of machine learning research has been a driving force for dramatic improvements in learning performances. The scientific community further fosters this effort by including reproducibility ratings in reviewer forms…
Scientific knowledge increasingly depends on complex computational processes where both hardware and software layers can influence research outcomes. As computational complexity grows, classical-quantum integration provides a lens for…
In recent decades the analysis of data has become increasingly computational. Correspondingly, this has changed how scientific and statistical work is shared. For example, it is now commonplace for underlying analysis code and data to be…
Computational reproducibility is essential for the credibility of scientific findings, particularly in the social sciences, where findings often inform real-world decisions. Manual reproducibility assessment is costly and time-consuming, as…
Context: Experiment replications play a central role in the scientific method. Although software engineering experimentation has matured a great deal, the number of experiment replications is still relatively small. Software engineering…
The Scikit-HEP project is a community-driven and community-oriented effort with the aim of providing Particle Physics at large with a Python scientific toolset containing core and common tools. The project builds on five pillars that…
Reproducibility is a confused terminology. In this paper, I take a fundamental view on reproducibility rooted in the scientific method. The scientific method is analysed and characterised in order to develop the terminology required to…
Reproducibility is a cornerstone of science. FAIR (findable, accessible, interoperable, and reusable) data is often a vital step towards testing the reproducibility of results. The implementation of FAIR principles in the astrophysical…
The high-performance computing (HPC) community has adopted incentive structures to motivate reproducible research, with major conferences awarding badges to papers that meet reproducibility requirements. Yet, many papers do not meet such…