How Open Source Software Contributors Are Accelerating Biomedicine

“Each day, hundreds of thousands of scientists use open source software to advance biology and medicine, from studying cells in a microscope image to understanding how genes behave in healthy cells. Open source software underpins much of modern scientific research — providing reproducibility, transparency, and opportunities for collaboration. The impact of these tools is on par with some of the most cited papers in science in terms of reuse and adoption, yet even the most widely-used research software often lacks dedicated funding.

Our Essential Open Source Software for Science (EOSS) program was created to support these efforts — from software maintenance to growth, development, and community engagement for open source tools that are critical to science. We asked nine grantees from the first cycle of the EOSS program what drives them to create tools and how their commitment to open source moves science forward….”

Copyright Guide for Scientific Software | Zenodo

Abstract:  Today, science involves software. And although many scientists understand that their work stands on the shoulders of others, they may not know how copyright affects their rights to use others’ software, or how they can publish their software tools so others can use or cite it. The Copyright Guide to Scientific Software, a joint project of the Harvard Cyberlaw Clinic and the Center for Astrophysics, in association with the Software Preservation Network, aims to fill that gap, by providing clear, easy-to-read answers to common questions about how scientific software and copyright interact. 

 

The importance and challenges of sharing research software Tickets, Wed 5 Feb 2020 at 18:00 | Eventbrite

“Research software is increasingly being recognised as an important research output which also has a role in supporting the transparency and reproducibility of papers and associated experimental results. Funders such as Wellcome now include software in their data sharing policies, while more journals are supporting open sharing of software. The Research Software Engineering movement, which has developed over the last few years to support the people who build research software, is also developing awareness and understanding of the importance of research software….”

Open Software Means Kinder Science – Scientific American Blog Network

“As a marine ecologist, I never expected I would one day advocate that science should operate more like the tech industry.

This is not about “moving fast and breaking things.” For me, it is about openness. 

Open software, both a driver and a result of Silicon Valley’s success, has been game-changing for me as a scientist. Its transformative power has improved my ability to analyze data and collaborate with other scientists….

My own transformation from scientist to open science champion has emboldened me to help enable others, and to help bring the kindness of the open software community to science. That is the whole idea behind the Openscapes, an organization I founded to advocate for open practices in environmental science. The idea is to empower early career scientists with existing open tools and communities, focusing on the research group, the campus and beyond….”

Knowledge Futures Group

“The Knowledge Futures Group is a non-profit technology organization where promising new projects nurtured at knowledge institutions get built to scale and compete with proprietary alternatives.

Founded at MIT, directed by educators, publishers, and technologists, and supported by a consortium of funders and partners, the KFG brings the intelligence and experience of knowledge institutions together with the product development speed and capacity of technology companies.

We build better futures….”

Frontiers | Opportunities in Open Science With AI | Big Data

“This article examines the current trends and elaborates the future potentials of AI in its role for making science more open and accessible. Based on the experience derived from a research project called Microsoft Academic, the advocates have reasons to be optimistic about the future of open science as the advanced discovery, ranking, and distribution technologies enabled by AI are offering strong incentives for scientists, funders and research managers to make research articles, data and software freely available and accessible….”

TU Delft Strategic Plan Open Science 2020-2024 | TU Delft Repositories

Abstract:  Open Science is creating new forms of scientific interaction that were impossible or undreamed of in an earlier age. This has a strong impact on core academic processes like research, education and innovation. It is, for instance, easier to replicate an experiment if the relevant data sets are digitally available to any scientist who wishes to corroborate her colleague’s findings.TU Delft has a long history of engagement with Open Science. Yet, with its Open Science Programme 2020-2024, Research and Education in the Open Era, TU Delft wishes to take Open Science to the next level: a situation in which Open Science has become the default way of practising research and education, and the “information era” has become the “open era”. It is TU Delft’s ambition to be frontrunner in this revolutionary process. This is reflected in the TU Delft Strategic Framework 2018-2024, with “openness” as one of its major principles.The TU Delft Open Science Programme 2020-2024 tackles all areas of scholarly engagement where restrictions limit the flow of academic knowledge. It proposes new approaches to the process of research, education and innovation, with a strong focus on transparency, integrity and efficiency.The programme consists of five interrelated projects: Open Education, Open Access, Open Publishing Platform, FAIR Data, and FAIR Software. The projects are aimed at creating and disseminating various types of resources for the benefit of TU Delft researchers, teachers and students, as well as the general public. They will range from educational materials and software to a publishing platform. All outputs of the programme will be as ‘FAIR’ as possible: findable, accessible, interoperable and reusable.

Towards FAIR principles for research software | Data Science

Abstract:  The FAIR Guiding Principles, published in 2016, aim to improve the findability, accessibility, interoperability and reusability of digital research objects for both humans and machines. Until now the FAIR principles have been mostly applied to research data. The ideas behind these principles are, however, also directly relevant to research software. Hence there is a distinct need to explore how the FAIR principles can be applied to software. In this work, we aim to summarize the current status of the debate around FAIR and software, as a basis for the development of definite community-agreed principles for FAIR research software in the future. We discuss what makes software different from data with respect to the application of the FAIR principles, present an analysis of where the existing principles can directly be applied to software, where they need to be adapted or reinterpreted, and where the definition of additional principles is required. Furthermore, we discuss desired characteristics of research software that go beyond FAIR.