Researchers at Hull are practising openness in a range of exciting ways. Every discipline has different ideas about what constitutes openness and different ways to practice it. This pages describes just a few examples. If their open research work interests you, feel free to get in touch with them.
Dr Shane Lindsay, Coglang and Team Respire Laboratories, School of Psychology and Social Work
My research labs work on questions involving language and memory consolidation, and the influence of respiration on cognition. My approach to Open Research is ultimately motivated by desire to orient towards epistemic virtue. As a scientist I believe that science as a collective enterprise we should strive towards practices that maximise advancing scientific knowledge rather than individual rewards. Open Research does not guarantee this outcome, but I believe a community wide embrace of Open Research practices will help keep firmly in this direction, and help steer us away from practices which might reduce the quality of our epistemic goods. My own conversion toward Open Research has been through awareness of what has become known as the "credibility crisis" in psychology, which has raised similar concerns in many other fields as well. A driver for this crisis has been difficulty in the replication of research. Having experienced these challenges first hand, I wanted to improve the robustness of our research, and became convinced of the necessity of Open Research as part of an integral part of range of practices that individual scientists can engage to increase the credibility of our science.
The main ways Open Research has impacted our work is the use of open data and resources, pre-registration and registered reports. As well as providing open data and resources for our own research outputs, the sharing from others of data and resources such as experimental scripts and stimuli has facilitated our own research in the construction of new studies. Pre-registration, where research and analysis plans are made public before data collection, helps to improve our planning and sharpen our predictions to allow more constrained tests of theories. In psychology, an important methodological development has been the emergence of the registered report format, which is a form of pre-registration where a journal commits to publishing a study regardless of the results. My research group is still in the early stages of the move to fully Open Research practices but have now two registered reports under review. This report format has the individual benefit of helping ensure research outputs and impact regardless of the outcome of often capricious data. But for the collective benefit of psychological science, it also means that the publication record will be less biased towards our hypotheses shown to be true, as historically psychology (along with other fields) has a strong tendency against publishing null findings, which is an impediment to our scientific progress.
Prof Grant Abt, School of Sport, Health and Rehabilitation Sciences
Our research covers the science of physical activity, technology, and elite sport performance. Ash Warner and supervisory team are examining how wearable technology can help people achieve the physical activity guidelines recommended by governments, Ben Greenhough and supervisory team are examining how virtual reality can help elite football players, and Aimee Evans and supervisory team are examining the recovery strategies used in elite football and whether these align with the evidence-base.
About five years ago, Prof Abt had a ‘road to Damascus’ moment. He realised that his research, and the research in his discipline, needed radical change. This moment was the culmination of several years listening to other researchers who were highlighting the many limitations and poor methods being practiced across the quantitative research disciplines, such as psychology and exercise science. These authors (such as Chris Chambers and Brian Nosek) were highlighting how lack of pre-registration, lack of data sharing, and questionable research practices (p-hacking, HARKing, publication bias, low statistical power, human errors) were creating a ‘replication crisis’ in psychology, and probably in his own discipline as well. From that moment he realised that his own research needed to change, and that the work of his postgraduate students would also need to change. There is emerging evidence that open research practices are leading to more rigorous research, so the inclusion (and training) of postgraduate researchers in open research is now an important element of the postgraduate degree experience.
The fundamental change in our way of working is that all decisions regarding method and statistical analyses are now taken prior to data collection and published on a public-facing website. This is the process called pre-registration. Here are some examples of our postgraduate students' study pre-registrations published prior to data collection:
All three postgraduate students view this change in working practice as a positive experience. Ash says “I’ve found using the Open Science Framework pre-registration a positive experience, to which we regularly refer when discussing our analysis plan. The process has been helpful throughout the data collection and analysis stages, and I think it has improved the overall rigour of our methodology and analysis. It is certainly something I will continue to advocate in future research”. Ben also agrees that study pre-registration has been a positive step, stating “the pre-registration process allowed me to critically appraise my own method before I began data collection, and upheld accountability in how I reported my results. I believe that this process improved the quality of my work and is a process I plan to use in the future”.
Aimee’s experience is probably typical of many, when initially she experienced some frustration at the delay in data collection. However, reflecting on the process she now says “Pre-registration forced me to identify and evaluate what I will do with my data and how it will be analysed. As a result of this additional time spent on my pre-registration, when all my data are collected the analysis process will be straightforward and less time-consuming as I have already put the hard hours in to figure this out. My PhD has taught me valuable life skills and the preregistration process has been a vital part of this”.
Human Technology Laboratory, School of Psychology and Social Work
I am a social and cognitive neuroscientist studying how humans perceive actions performed by humans and non-human agents (e.g., robots). I have been the first to introduce OR practices within the School of Psychology and Social work. OR is fundamental for any Psychology and Neuroscience research. OR practices provide more information to form an opinion about the strengths and weaknesses of new findings. For example, sharing the scripts used to analyse data allow scholars to check the statistical approach of a research.
Adopting OR practices improved the linearity of the steps to take while undergoing a new work. Importantly, they allowed a better planning of the activities after data has been collected and analysed.
The PM Programming Language: writing numerical models for distributed computers
PM is an open-source programming language design and implementation, developed to facilitate the creation of numerical models on distributed parallel computer hardware such as the University of Hull VIPER cluster. The language uses a new paradigm that combines the global view of arrays used by Partitioned Global Address Space languages, such as Unified Parallel C or Chapel, with a simple and robust model for synchronisation. The first version of the language was released in 2014 with updates following in subsequent years. The project was on hiatus during the pandemic, but a new version of the software is expected to be released in November/December 2022 at www.pm-lang.org
While several academic publications on this topic are planned, the PM language is primarily designed as a tool for other researchers, with academics and postgraduate students in the natural and environmental sciences as the main audience. As with the vast majority of new programming languages, this necessitates the adoption of an open research approach. The source code for the PM compiler is released under a permissive MIT license which allows for free copying, redistribution and incorporation in other projects. The language definition is released under the Creative Commons 4.0 Attribution Licence which allows free redistribution and adaptation with the explicit implication that it may be used as the basis for an alternative implementation of the language. By presenting as few barriers as possible, it is hoped that as the language design matures there will be no impediments to the use, or even ultimately the re-implementation of the language by other research groups and organisations.
The PM language was first introduced at the 2014 European Geosciences Union (EGU) general assembly in Vienna. Having developed a very basic version of the language, the author speculatively decided to present it in a poster session alongside his more mainstream research. In the event, this proved to be one of the busiest sessions he had ever presented with many people expressing enthusiasm and encouragement to pursue the project, despite the very undeveloped state of the software at the time. Over the subsequent years (with the exception of the COVID pandemic) development of the language and compiler continued as a “background” project while enthusiasm from colleagues, expressed in venues such as EGU general assemblies, continued unabated. This enthusiasm will have a chance to be repaid in a concrete way when a fully functioning version of the PM compiler is released later this year. A notable feature of open, as opposed to conventional, research has proved to be its ongoing nature – an extended and continuing effort over a longer period of time with each stage available for wider scrutiny and feedback, as opposed to a series of shorter, essentially self-contained projects.
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