Related papers: Utilizing SciPy and other open source packages to …
In this chapter we first outline some of the popular computing environments used for analysing neural data, followed by a brief discussion of 'software carpentry', basic tools and skills from software engineering that can be of great use to…
Scientific advancement relies on the ability to share and reproduce results. When data analysis or calculations are carried out using software written by scientists there are special challenges around code versions, quality and code…
We introduce SciWING, an open-source software toolkit which provides access to pre-trained models for scientific document processing tasks, inclusive of citation string parsing and logical structure recovery. SciWING enables researchers to…
SciPy is an open source scientific computing library for the Python programming language. SciPy 1.0 was released in late 2017, about 16 years after the original version 0.1 release. SciPy has become a de facto standard for leveraging…
We discuss here our vision for an Open-Science platform for computational Materials Science. Such a platform needs to rely on three pillars, consisting of 1) open data generation tools (including the simulation codes, the scientific…
A large number of computational scientific research projects make use of open source software packages. However, the development process of such tools frequently differs from conventional software development; partly because of the nature…
Scientific open-source software (OSS) has greatly benefited research communities through its transparent and collaborative nature. Given its critical role in scientific research, ensuring the sustainability of such software has become…
SkyPy is an open-source Python package for simulating the astrophysical sky. It comprises a library of physical and empirical models across a range of observables and a command-line script to run end-to-end simulations. The library provides…
With the advent of open source software, a veritable treasure trove of previously proprietary software development data was made available. This opened the field of empirical software engineering research to anyone in academia. Data that is…
Large language models (LLMs) are rapidly transforming materials science. This review examines recent LLM applications across the materials discovery pipeline, focusing on three key areas: mining scientific literature , predictive modelling,…
Open science describes the movement of making any research artefact available to the public and includes, but is not limited to, open access, open data, and open source. While open science is becoming generally accepted as a norm in other…
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…
We present an expository overview of technical and cultural challenges to the development and adoption of automation at various stages in the data science prediction lifecycle, restricting focus to supervised learning with structured…
Science advances not only through the accumulation of facts but also through the evolution of tools. Crucially, tools are rarely used in isolation. They form tool portfolios, combinations shaped by a discipline's workflows and analytical…
The Open Databases Integration for Materials Design (OPTIMADE) application programming interface (API) empowers users with holistic access to a growing federation of databases, enhancing the accessibility and discoverability of materials…
A plethora of scientific software packages are published in repositories, e.g., Zenodo and figshare. These software packages are crucial for the reproducibility of published research. As an additional route to scholarly knowledge graph…
Open source software is a rapidly evolving center for distributed work, and understanding the characteristics of this work across its different contexts is vital for informing policy, economics, and the design of enabling software. The…
In the era of data-driven science, conducting computational experiments that involve analysing large datasets using heterogeneous computational clusters, is part of the everyday routine for many scientists. Moreover, to ensure the…
For over a decade, the SpacePy project has contributed open-source solutions for the production and analysis of heliophysics data and simulation results. Here we introduce SpacePy's functionality for the scientific user and present relevant…
We have developed an open-source software package (SedSimple) for stratigraphic forward modeling. It is aimed for use in research and education. The package uses ASCII files for input and output to facilitate understanding, debugging and…