Related papers: Reproducing Scientific Experiment with Cloud DevOp…
Reproducibility is widely acknowledged as a fundamental principle in scientific research. Currently, the scientific community grapples with numerous challenges associated with reproducibility, often referred to as the ''reproducibility…
Science is conducted collaboratively, often requiring the sharing of knowledge about computational experiments. When experiments include only datasets, they can be shared using Uniform Resource Identifiers (URIs) or Digital Object…
We investigate the feasibility of high performance scientific computation using cloud computers as an alternative to traditional computational tools. The availability of these large, virtualized pools of compute resources raises the…
The proliferation of sensor technologies and advancements in data collection methods have enabled the accumulation of very large amounts of data. Increasingly, these datasets are considered for scientific research. However, the design of…
In this paper we explore the challenges of automating experiments in data science. We propose an extensible experiment model as a foundation for integration of different open source tools for running research experiments. We implement our…
One of the foundations of science is that researchers must publish the methodology used to achieve their results so that others can attempt to reproduce them. This has the added benefit of allowing methods to be adopted and adapted for…
The advent of experimental science facilities-instruments and observatories, such as the Large Hadron Collider, the Laser Interferometer Gravitational Wave Observatory, and the upcoming Large Synoptic Survey Telescope-has brought about…
Computer simulations have become a very powerful tool for scientific research. In order to facilitate research in computational biology, the BioDynaMo project aims at a general platform for biological computer simulations, which should be…
Although reproducibility is a core tenet of the scientific method, it remains challenging to reproduce many results. Surprisingly, this also holds true for computational results in domains such as systems biology where there have been…
Various fields of science face a reproducibility crisis. For quantum software engineering as an emerging field, it is therefore imminent to focus on proper reproducibility engineering from the start. Yet the provision of reproduction…
Scientific research increasingly relies on distributed computational resources, storage systems, networks, and instruments, ranging from HPC and cloud systems to edge devices. Event-driven architecture (EDA) benefits applications targeting…
DevOps is a set of principles and practices to improve collaboration between development and IT Operations. Against the backdrop of the growing adoption of DevOps in a variety of software development domains, this paper describes empirical…
The field of deep learning is experiencing a trend towards producing reproducible research. Nevertheless, it is still often a frustrating experience to reproduce scientific results. This is especially true in the machine learning community,…
Cloud computing is an emerging platform of service computing designed for swift and dynamic delivery of assured computing resources. Cloud computing provide Service-Level Agreements (SLAs) for guaranteed uptime availability for enabling…
The high incidence of irreproducible research has led to urgent appeals for transparency and equitable practices in open science. For the scientific disciplines that rely on computationally intensive analyses of large data sets, a granular…
An essential part of research and scientific communication is researchers' ability to reproduce the results of others. While there have been increasing standards for authors to make data and code available, many of these files are hard to…
Due to the complexity of robotics, the reproducibility of results and experiments is one of the fundamental problems in robotics research. While the problem has been identified by the community, the approaches that address the problem…
The cloud computing paradigm is being adopted by many organizations in different application domains as it is cost effective and offers a virtually unlimited pool of resources. Engineering critical systems can benefit from clouds in…
Crowdsourcing is a multidisciplinary research area including disciplines like artificial intelligence, human-computer interaction, database, and social science. To facilitate cooperation across disciplines, reproducibility is a crucial…
Small to medium-scale data science experiments often rely on research software developed ad-hoc by individual scientists or small teams. Often there is no time to make the research software fast, reusable, and open access. The consequence…