In the years since the launch of the World Wide Web in 1993, there have been profoundly transformative changes to the entire concept of publishing—exceeding all the previous combined technical advances of the centuries following the introduction of movable type in medieval Asia around the year 10001 and the subsequent large-scale commercialization of printing several centuries later by J. Gutenberg (circa 1440). Periodicals in print—from daily newspapers to scholarly journals—are now quickly disappearing, never to return, and while no publishing sector has been unaffected, many scholarly journals are almost unrecognizable in comparison with their counterparts of two decades ago. To say that digital delivery of the written word is fundamentally different is a huge understatement. Online publishing permits inclusion of multimedia and interactive content that add new dimensions to what had been available in print-only renderings. As of this writing, the IEEE portfolio of journal titles comprises 59 online only2 (31%) and 132 that are published in both print and online. The migration from print to online is more stark than these numbers indicate because of the 132 periodicals that are both print and online, the print runs are now quite small and continue to decline. In short, most readers prefer to have their subscriptions fulfilled by digital renderings only.
Growing pressure in Australia to translate pre-clinical and clinical research into improving treatment outcomes (https://www.nhmrc.gov.au/research/research-translation-0) means that concerns about the irreproducibility of published data slowing research translation (Collins and Tabak, 2014) must be addressed.
This report describes perspectives from the Workshop on the Future of Research Curation and Research Reproducibility that was collaboratively sponsored by the U.S. National Science Foundation (NSF) and IEEE (Institute of Electrical and Electronics Engineers) in November 2016. The workshop brought together stakeholders including researchers, funders, and notably, leading science, technology, engineering, and mathematics (STEM) publishers. The overarching objective was a deep dive into new kinds of research products and how the costs of creation and curation of these products can be sustainably borne by the agencies, publishers, and researcher communities that were represented by workshop participants. The purpose of this document is to describe the ideas that participants exchanged on approaches to increasing the value of all research by encouraging the archiving of reusable data sets, curating reusable software, and encouraging broader dialogue within and across disciplinary boundaries. How should the review and publication processes change to promote reproducibility? What kinds of objects should the curatorial process expand to embrace? What infrastructure is required to preserve the necessary range of objects associated with an experiment? Who will undertake this work? And who will pay for it? These are the questions the workshop was convened to address in presentations, panels, small working groups, and general discussion.
This symposium will serve as the launch event for our new open, online book, titled The Practice of Reproducible Research. The book contains a collection of 31 case studies in reproducible research practices written by scientists and engineers working in the data-intensive sciences. Each case study presents the specific approach that the author used to achieve reproducibility in a real-world research project, including a discussion of the overall project workflow, major challenges, and key tools and practices used to increase the reproducibility of the research.
This project considers the role of reproducibility in increasing verification and accountability in linguistic research. An analysis of over 370 journal articles, dissertations, and grammars from a ten-year span is taken as a sample of current practices in the field. These are critiqued on the basis of transparency of data source, data collection methods, analysis, and storage. While we find examples of transparent reporting, much of the surveyed research does not include key metadata, methodological information, or citations that are resolvable to the data on which the analyses are based. This has implications for reproducibility and hence accountability, hallmarks of social science research which are currently under-represented in linguistic research.
Improving the reliability and efficiency of scientific research will increase the credibility of the published scientific literature and accelerate discovery. Here we argue for the adoption of measures to optimize key elements of the scientific process: methods, reporting and dissemination, reproducibility, evaluation and incentives. There is some evidence from both simulations and empirical studies supporting the likely effectiveness of these measures, but their broad adoption by researchers, institutions, funders and journals will require iterative evaluation and improvement. We discuss the goals of these measures, and how they can be implemented, in the hope that this will facilitate action toward improving the transparency, reproducibility and efficiency of scientific research.