In agriculture research, as Emily Black and Ross Maidment indicate, Open Research translates not only into Open Access to scholarly output, e.g., journal articles or empirical data, but also into the Open Source code that underlies the digital infrastructure, e.g., TAMSAT-ALERT, for a global, Africa-oriented early warning system for weather events. This removes fee-related barriers, facilitates stakeholder engagement, and ensures transparency, simplicity and uptake among potential platform users, such as farmers in Malawi. In other words, Open Access in science contributes to trust building, cross-border collaborations and value-added product development with an emphasis on low-income countries.
Similarly, in the domain of environmental science, as Jon Blower highlights, Open Access, primarily through shared Open Source software, drives solution adoption by research organizations, government agencies and industry players not only locally but also globally. Projects based on Open Science principles, e.g., Copernicus Marine Service, have been found to create value and generate additional grant-derived income, which has more than offset the expected revenue streams from proprietary licensing.
This is also relevant for the globally oriented projects, such as the Global Flood Awareness System that offers freely accessible seasonal forecasts, underlying empirical data and associated scholarly paper, which accelerates information exchange, data visualization and applied forecasting in close correspondence to user needs, as Rebecca Emerton notes. Additionally, ad Nat Hansen and Philip Beaman suggest, in the fields of philosophy and psychology, Open Access can assist dealing with the challenges of experimental research setup reproducibility, such as through access to study designs via the Open Science Framework. This also contributes to hypothesis testing, research method development and finding sharing, e.g., for confirmatory or exploratory studies.
For fundamental science, Open Research platforms, such as the Zooniverse, allow drawing on the input from citizen scientists from around the world for a distributed and systemic exploration of complex platforms, e.g., solar coronal mass ejections. According to Chris Scott, Open Research has enabled harnessing the credited contributions of thousands of volunteers for the production of several scholarly articles, while opening novel lines of inquiry and further developing research methods.
Likewise, for neuroimaging, Open Science, e.g., the Brain Imaging Data Structure, translates into making scholarly communication more efficient, such as by relying on preprint servers for an early dissemination of findings, code and data, and open source tools for the sharing of best practices and research designs, as Inge Lasser adds.
Thus, on the one hand, Open Research practices can be expected to maximize output exposure, promote early career research and facilitate professional network building, such as via co-authorships, as Marcello De Maria suggests.
On the other hand, Open Science solutions, such as the low-cost Raspberry Pi computer, can lead to scientific discoveries, e.g., in the field of microbiological imaging, via more customizable research design, hardware and software deployed for the processing of format-independent data streams, as Al Edwards reminds.
By Pablo Markin
Featured Image Credits: Spiral Galaxy M83, Berkley, CA, USA, July 2, 2016 | © Courtesy of NASA, ESA, and the Hubble Heritage Team (STScI/AURA)/NASA Hubble Space Telescope/Flickr.
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