23 papers · ranked by Valyu relevance
Authors not listed
Scientific discovery relies on innovative software as much as experimental methods, especially in proteomics, where computational tools are essential for mass spectrometer setup, data analysis, and interpretation. Since the introduction of SEQUEST, proteomics software has grown into a complex ecosystem of algorithms…
Rita Kukafka, Neil Chue Hong, Simon Hettrick, Ye Ye + 21 more
Background The National Cancer Institute Informatics Technology for Cancer Research (ITCR) program provides a series of funding mechanisms to create an ecosystem of open-source software (OSS) that serves the needs of cancer research. As the ITCR ecosystem substantially grows, it faces the challenge of the long-term…
Raphael Sonabend, Hugo Gruson, Leo Wolansky, Agnes Kiragga + 2 more
'Daniel S. Katz' 'Jason A. Papin'] This paper extends the FAIR (Findable, Accessible, Interoperable, Reusable) guidelines to provide criteria for assessing if software conforms to best practices in open source. By adding “USE” (User-Centered, Sustainable, Equitable), software development can adhere to open source best…
Rui Li, Vaibhav Sharma, Subasini Thangamani, Artur Yakimovich
Open-source research software has proven indispensable in modern biomedical image analysis. A multitude of open-source platforms drive image analysis pipelines and help disseminate novel analytical approaches and algorithms. Recent advances in machine learning allow for unprecedented improvement in these approaches.…
Clark D. Asay
The software industry's history is also its future. Its history has been defined by both abundance and scarcity, and its future will be, too. In the 1970s and 80s, perceived software scarcity led U.S. legislators to formally grant intellectual property protections to software creators. Later, a different kind of…
Yo Yehudi, Carole Goble, Caroline Jay
The global value of open source software is estimated to be in the billions or trillions worldwide 1 , but despite this, it is often under-resourced and subject to high-impact security vulnerabilities and stability failures 2,3 . In order to investigate factors contributing to open source community longevity, we…
Mario Zuliani, C. J. Lortie
Open science, work and knowledge that are developed in full, offers critical resources that provide students with insights into the process of research in many fields. There are extensive opportunities within environmental sciences to incorporate open science into undergraduate level courses. There are seven major open…
Madiha Zahrah Choksi, Ilan Mandel, David Goedicke, Yan Shvartzshnaider
'Yan Shvartzshnaider'] Centralization in code hosting and package management in the 2010s created fundamental shifts in the social arrangements of open source ecosystems. In a regime of centralized open source, platform effects can both empower and detract from communities depending on underlying technical…
Stan Zajdel, Diego Elias Costa, Hafedh Mili
The Open Source Software movement has been growing exponentially for a number of years with no signs of slowing. Driving this growth is the wide-spread availability of libraries and frameworks that provide many functionalities. Developers are saving time and money incorporating this functionality into their…
Giuditta Parolini
The paper discusses legal aspects relevant to the development of research software and practical approaches taken by research software engineers to deal with them. Intellectual Property Rights on software are considered alongside licensing choices made by the research community. The discussion addresses the ambiguities…
Bhavesh Patel, Sanjay Soundarajan, Zicheng Hu
Findable, Accessible, Interoperable, and Reusable (FAIR) guiding principles tailored for research software have been proposed by the FAIR for Research Software (FAIR4RS) Working Group. They provide a foundation for optimizing the reuse of research software. The FAIR4RS principles are, however, aspirational and do not…
Authors not listed
The increasing importance and predictive power of modern molecular modeling, driven by physics- and machine learning-based methods, necessitates a new collaborative architecture to replace the isolated, traditional model of software development. The traditional approach often led to redundant engineering effort, high…
Toufique Ahmed, Christian Bird, Prémkumar Dévanbu, Saikat Chakraborty
'Saikat Chakraborty'] Large Language models (LLMs) are finding wide use in software engineering practice. These models are extremely data-hungry, and are largely trained on open-source (OSS) code distributed with permissive licenses. In terms of actual use however, a great deal of software development still occurs in…
Caroline Morton, Nicholas Devito, Jessica Morley, Iain Dillingham + 5 more
There is no one method for code review; however in general it is best to review often, and not at the end of the project, and for both the researcher and the code reviewer to have clear expectations of what code review will entail. For example, does it include running the code entirely or simply looking and commenting…
Authors not listed
Raman spectroscopy is an increasingly powerful and fast-growing analytical technique across diverse disciplines, from materials science and chemistry to biology and medicine, thanks to advances in Raman instrumentation and greatly supported by the flourishing of chemometrics and artificial intelligence (AI). However…
Nitesh Kumar Sharma, Ram Ayyala, Dhrithi Deshpande, Yesha M Patel + 11 more
Data-driven computational analysis is becoming increasingly important in biomedical research, as the amount of data being generated continues to grow. However, the lack of practices of sharing research outputs, such as data, source code and methods, affects transparency and reproducibility of studies, which are…
Christopher Woods, Lester Hedges, Adrian Mulholland, Maturos Malaisree + 10 more
Sire is a Python/C++ library that is used to both prototype new algorithms and as an interoperability engine for exchanging information between molecular simulation programs. It provides a collection of file parsers and information converters that together make it easier to combine and leverage the functionality of…
Dana E. Cobb-Lewis, Devin Synder, Sonya Dumanis, Robert Thibault + 6 more
The open science movement aims to transform the research landscape by promoting research transparency in order to enable reproducibility and replicability, lower the barriers for collaboration, and reduce unnecessary duplication. Recently, in recognition of the value of open science, funding agencies have begun to…
Chris Macek, Brad Cunningham, Nicolas Boillot
Global health has been historically committed to adopting open-source software in health applications globally. This is due to a well-intentioned commitment to capacity-building and the belief that open-source systems enable in-country capacity to take over technology implementations without being locked into specific…
Caroline M. Kelsey, Jebediah Taylor, Laura Pirazzoli, Renata Di Lorenzo + 2 more
Open science practices work to increase methodological rigor, transparency, and replicability of published findings. This review aims to reflect and commemorate what the functional Near Infrared Spectroscopy (fNIRS) community has done to promote open science practices in fNIRS research and set goals to accomplish over…
Christian B. Strømme, A. Kelly Lane, Aud H. Halbritter, Elizabeth Law + 7 more
Open Science (OS) comprises a variety of practices and principles that are broadly intended to improve the quality and transparency of research, and the concept is gaining traction. Since OS has multiple facets and still lacks a unifying definition, it may be interpreted quite differently among practitioners. Moreover…
Jeremy Li, Alex Rubinsteyn, Sergey Feldman, Timothy O’Donnell + 18 more
Scientific computing has become a central component of modern scientific discovery. Yet many computational tools are developed by small, specialized teams under incentives that encourage the release of rapidly prototyped tooling without commensurate attention to engineering concerns, including performance and…
Authors not listed
The discoverability and reusability of data is critical for machine learning to drive new discovery in the chemical sciences, and the ‘FAIR Guiding Principles for scientific data management and stewardship’ provide a measurable set of guidelines that can be used to ensure the accessibility of reusable data. We…