Open Source in Lab Management

• URL: http://arxiv.org/abs/2405.07774v1
• Date: Mon, 13 May 2024 14:18:20 GMT
• Title: Open Source in Lab Management
• Authors: Julien Cohen-Adad,
• Abstract summary: This document explores the advantages of integrating open source software and practices in managing a scientific lab. The broader goal is to promote transparent, reproducible science by adopting open source tools.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This document explores the advantages of integrating open source software and practices in managing a scientific lab, emphasizing reproducibility and the avoidance of pitfalls. It details practical applications from website management using GitHub Pages to organizing datasets in compliance with BIDS standards, highlights the importance of continuous testing for data integrity, IT management through Ansible for efficient system configuration, open source software development. The broader goal is to promote transparent, reproducible science by adopting open source tools. This approach not only saves time but exposes students to best practices, enhancing the transparency and reproducibility of scientific research.

Related papers

• OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models [70.72097493954067]
  Large language models (LLMs) for code have become indispensable in various domains, including code generation, reasoning, tasks and agent systems. We introduce OpenCoder, a top-tier code LLM that not only achieves performance comparable to leading models but also serves as an open cookbook'' for the research community.
  arXiv  Detail & Related papers  (2024-11-07T17:47:25Z)
• OpenR: An Open Source Framework for Advanced Reasoning with Large Language Models [61.14336781917986]
  We introduce OpenR, an open-source framework for enhancing the reasoning capabilities of large language models (LLMs) OpenR unifies data acquisition, reinforcement learning training, and non-autoregressive decoding into a cohesive software platform. Our work is the first to provide an open-source framework that explores the core techniques of OpenAI's o1 model with reinforcement learning.
  arXiv  Detail & Related papers  (2024-10-12T23:42:16Z)
• How to Understand Whole Software Repository? [64.19431011897515]
  An excellent understanding of the whole repository will be the critical path to Automatic Software Engineering (ASE) We develop a novel method named RepoUnderstander by guiding agents to comprehensively understand the whole repositories. To better utilize the repository-level knowledge, we guide the agents to summarize, analyze, and plan.
  arXiv  Detail & Related papers  (2024-06-03T15:20:06Z)
• Automated Extraction and Maturity Analysis of Open Source Clinical Informatics Repositories from Scientific Literature [0.0]
  This study introduces an automated methodology to bridge the gap by systematically extracting GitHub repository URLs from academic papers indexed in arXiv. Our approach encompasses querying the arXiv API for relevant papers, cleaning extracted GitHub URLs, fetching comprehensive repository information via the GitHub API, and analyzing repository maturity based on defined metrics such as stars, forks, open issues, and contributors.
  arXiv  Detail & Related papers  (2024-03-20T17:06:51Z)
• FAIR-USE4OS: Guidelines for Creating Impactful Open-Source Software [0.41942958779358663]
  This paper extends the FAIR (Findable, Accessible, Interoperable, Reusable) guidelines to provide criteria for assessing if software conforms to best practices in open source. The FAIR-USE4OS guidelines will allow funders and researchers to more effectively evaluate and plan open source software projects.
  arXiv  Detail & Related papers  (2024-02-05T09:15:20Z)
• The Software Heritage Open Science Ecosystem [0.0]
  Software Heritage is the largest public archive of software source code and associated development history. It has archived more than 16 billion unique source code files coming from more than 250 million collaborative development projects. It supports empirical research on software by materializing in a single Merkle direct acyclic graph the development history of public code. It ensures availability and guarantees integrity of the source code of software artifacts used in any field that relies on software to conduct experiments.
  arXiv  Detail & Related papers  (2023-10-16T11:32:03Z)
• A Metadata-Based Ecosystem to Improve the FAIRness of Research Software [0.3185506103768896]
  The reuse of research software is central to research efficiency and academic exchange. The DataDesc ecosystem is presented, an approach to describing data models of software interfaces with detailed and machine-actionable metadata.
  arXiv  Detail & Related papers  (2023-06-18T19:01:08Z)
• Katakomba: Tools and Benchmarks for Data-Driven NetHack [52.0035089982277]
  NetHack is known as the frontier of reinforcement learning research. We argue that there are three major obstacles for adoption: resource-wise, implementation-wise, and benchmark-wise. We develop an open-source library that provides workflow fundamentals familiar to the offline reinforcement learning community.
  arXiv  Detail & Related papers  (2023-06-14T22:50:25Z)
• CORL: Research-oriented Deep Offline Reinforcement Learning Library [48.47248460865739]
  CORL is an open-source library that provides thoroughly benchmarked single-file implementations of reinforcement learning algorithms. It emphasizes a simple developing experience with a straightforward and a modern analysis tracking tool.
  arXiv  Detail & Related papers  (2022-10-13T15:40:11Z)
• Defining the role of open source software in research reproducibility [0.0]
  I make a new proposal for the role of open source software. I look for explanation of its success from the perspectives of connectivism. I contend that engenders trust, which we routinely build in community via conversations.
  arXiv  Detail & Related papers  (2022-04-26T19:52:47Z)
• Nine Best Practices for Research Software Registries and Repositories: A Concise Guide [63.52960372153386]
  We present a set of nine best practices that can help managers define the scope, practices, and rules that govern individual registries and repositories. These best practices were distilled from the experiences of the creators of existing resources, convened by a Task Force of the FORCE11 Software Implementation Working Group during the years 2011 and 2012.
  arXiv  Detail & Related papers  (2020-12-24T05:37:54Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.