Enabling research with Open Software and Data Tickets, Tue 11 May 2021 at 11:00 | Eventbrite

“On the 10 – 14 May 2021, during Open Scholarship Week (OSW2021) staff, students, members of the public and a variety of other stakeholders will come together to talk about changing the ways scholarly information is openly communicated, shared and used. OSW2021 will offer a diverse range of talks and workshops representing many different perspectives and disciplines on Open practices in research and education….”

[2104.05891] Science-Software Linkage: The Challenges of Traceability between Scientific Knowledge and Software Artifacts

Abstract:  Although computer science papers are often accompanied by software artifacts, connecting research papers to their software artifacts and vice versa is not always trivial. First of all, there is a lack of well-accepted standards for how such links should be provided. Furthermore, the provided links, if any, often become outdated: they are affected by link rot when pre-prints are removed, when repositories are migrated, or when papers and repositories evolve independently. In this paper, we summarize the state of the practice of linking research papers and associated source code, highlighting the recent efforts towards creating and maintaining such links. We also report on the results of several empirical studies focusing on the relationship between scientific papers and associated software artifacts, and we outline challenges related to traceability and opportunities for overcoming these challenges.

 

Generalizing FAIR – Daniel S. Katz’s blog

“Most researchers and policymakers support the idea of making research, and specifically research outputs, findable, accessible, interoperably, and reusable (FAIR). The concept of FAIR has been well-developed for research data, but this is not the case for all research products. This blog post seeks to consider how the application of FAIR to a range of research products (beyond data) could result in the development of different sets of principles for applying FAIR to different research objects, and to ask about the implications of this….

Data meets science: Open access, code, datasets, and knowledge graphs for machine learning research and beyond

Science and data are interwoven in many ways. The scientific method has lent a good part of its overall approach and practices to data-driven analytics, software development, and data science. Now data science and software lend some tools to scientific research.

Five recommendations for “FAIR software” | Zenodo

“Our Accelerate Open Science Project aims to give context to various developments in the area of Open Science, and to make information about topics such as FAIR data easier accessible.

These slides are an adjusted version of the content from the https://fair-software.eu/ website, which is a collaboration between the Netherlands eScience Center and DANS….”

COPIM releases free code for Open Access project sign up system

“The Community-led Open Publication Infrastructures for Monographs project (COPIM) has today released the code originally written for their Opening the Future initiative, which collects and processes library signups. This release makes the software freely available for any publisher to adapt and use themselves – it is a generic signup system for open-access projects that have consortial membership models….”

Guest Post – Citing Software in Scholarly Publishing to Improve Reproducibility, Reuse, and Credit – The Scholarly Kitchen

“Software is essential to research, and is regularly an element of the work described in scholarly articles. However, these articles often don’t properly cite the software, leading to problems finding and accessing it, which in turns leads to problems with reproducibility, reuse, and proper credit for the software’s developers. In response, the FORCE11 Software Citation Implementation Working Group, comprised of scholarly communications researchers, representatives of nineteen major journals, publishers, and scholarly infrastructures (Crossref, DataCite), have proposed a set of customizable guidelines to clearly identify the software and credit its developers and maintainers. This follows the earlier development of a set of Software Citation Principles. To realize their full benefit, we are now urging publishers to adapt and adopt these guidelines to implement the principles and to meet their communities’ particular needs….”

[2012.13117] Nine Best Practices for Research Software Registries and Repositories: A Concise Guide

Abstract:  Scientific software registries and repositories serve various roles in their respective disciplines. These resources improve software discoverability and research transparency, provide information for software citations, and foster preservation of computational methods that might otherwise be lost over time, thereby supporting research reproducibility and replicability. However, developing these resources takes effort, and few guidelines are available to help prospective creators of registries and repositories. To address this need, 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 Citation Implementation Working Group during the years 2019-2020. We believe that putting in place specific policies such as those presented here will help scientific software registries and repositories better serve their users and their disciplines.