#SciData19 Writing Competition: Winning Entry #1

We are proud to publish the first of this year's four winning entries for this years Better Science through Better Data writing competition - congratulations to Anna Holderbaum
#SciData19 Writing Competition: Winning Entry #1
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Better Science through Better Data 2019

In ‘Better Science through Better Data’ (#scidata19) Springer Nature and The Wellcome Trust partner to bring together researchers to discuss innovative approaches to data sharing, open science, and reproducible research, together with demonstrations of exemplary projects and tools. If you are a researcher, this event will give you the chance to learn more about how research data skills can aid career progression, including how good practice in data sharing can enable you to publish stronger peer-reviewed publications. Tickets for the event have now sold out - but you can register for the live stream to watch our keynote talks as they happen from wherever you are in the world. Keynote speakers Shelley Stall Senior Director, Data Leadership American Geophysical Union (AGU) Shelley Stall is the Senior Director for the American Geophysical Union’s Data Leadership Program. She works with AGU’s members, their organizations, and the broader research community to improve data and digital object practices with the ultimate goal of elevating how research data is managed and valued. Better data management results in better science. Shelley’s diverse experience working as a program and project manager, software architect, database architect, performance and optimization analyst, data product provider, and data integration architect for international communities, both non-profit and commercial, provides her with a core capability to guide development of practical and sustainable data policies and practices ready for adoption and adapting by the broad research community. Shelley’s recent work includes the Enabling FAIR Data project, engaging over 300 stakeholders in the Earth, space, and environmental sciences to make data open and FAIR, targeting the publishing and repository communities to change practices by no longer archiving data in the supplemental information of a paper but instead depositing the data supporting the research into a trusted repository where it can be discovered, managed, and preserved. Her talk is entitled: Your Digital Presence Mikko Tolonen Assistant Professor Faculty of Arts at the University of Helsinki Mikko Tolonen is an assistant professor of Digital Humanities at the University of Helsinki. He is the PI of Helsinki Computational History Group (COMHIS). In 2015-17 he also worked in the National Library of Finland on digitized newspapers as professor of research on digital resources. He is the chair of Digital Humanities in the Nordic Countries (DHN). His current main research focus is on an integrated study of early modern public discourse and knowledge production that combines bibliographic metadata and full-text sources. In 2016, he was awarded an Open Science and Research Award by the Finnish Ministry of Education and Culture. His talk is entitled: Integrating Open Science in the Humanities: the Case of Computational History David Stillwell Lecturer in Big Data Analytics and Quantitative Social Science Judge Business School, University of Cambridge David is Lecturer in Big Data Analytics and Quantitative Social Science at Cambridge University’s Judge Business School. David’s research uses big data to understand psychology. He published papers using social media data from millions of consenting individuals to show that the computer can predict a user’s personality as accurately as their spouse can. This research has important public policy implications. How should consumers’ data be used to target them? Should regulators step in, and if so how? David has spoken at workshops at the EU Parliament and to UK government regulators. David has also published research using various big data sources such as from credit card data and textual data to show that spending money on products that match one’s personality leads to greater life satisfaction, that people tend to date others whose personality is similar, and that people who swear seem to be more honest. His talk is entitled: Getting Big Data: Social scientists must strive to be autonomous from corporate charity. Tomas Knapen Assistant Professor Vrije Universiteit Amsterdam - Cognitive Psychology Tomas is a cognitive neuroscientist whose research focuses on the role sensory topographies (visual retinotopy, auditory tonotopy and bodily somatotopy) play in the detailed organization of the human brain and cognition. For this work, Tomas uses state of the art 7-Tesla MRI techniques. Early-career experiences where he ‘failed to replicate’ previous findings have impressed upon him the need to make research reproducible from top to bottom. Because of this, his lab uses only open methods and puts all their data and methods online. Having invested in these methods, Tomas is convinced that, in the end, it is not a burden to perform open science, rather it provides researchers with great opportunities for ground-breaking science. His talk is entitled: How I learned to stop worrying and love Open Science See the event programme. Meet the Programme Committee. Register for the live stream.

Question: What support do researchers need to implement reproducible research?

Answer:

Anna Holderbaum - Queen's University Belfast

Accelerate scientific discovery, generate better products, improve quality of life and protect the environment - these are some of the broad impacts and benefits of reproducible research. It is scientists’ endeavour that their research is reproducible as it provides credibility to results and is a cornerstone of evidence-based decision-making. Recognising the need for reproducibility across the entire research lifecycle has become a multistakeholder priority involving scientists across all career stages, publishers, funding agencies, the public, industry and science policy representatives. Several initiatives have been launched to respond to current challenges and opportunities to improve reproducibility of research. Multiple measures have been adopted by researchers and publishers alike such as improvement of reporting standards, data transparency, and preregistration of studies. From a biological sciences perspective, reproducibility is a multifaceted topic, how can we address it? The scientific process and biological systems are complex and there are many variables to consider, which means scientists must document their research rigorously and comprehensively from the beginning. Often seemingly arbitrary variables such as ambient temperature or season can greatly influence the outcome. For example, hatching rates of plant parasitic nematodes are higher in summer than winter [1] which may significantly alter results of studies testing novel control strategies. Publishers can support this endeavour by encouraging researchers to publish in as much detail as possible and provide no restrictions on length and supplementary materials with digitals tools such as protocols.io [2] to support these processes. International recommendations for reporting agreed upon by relevant experts (e.g. those promoted by the EQUATOR Network [3]) outlining important variables guide researchers to contribute comprehensive reports. On the other hand, too rigorous standardisation has been shown to contribute to poor reproducibility in pre-clinical research while diversity of study samples improved reproducibility of the results. [4] Similarly, ignoring the biological variation in sex by predominantly studying male animals has impeded translation of research findings to humans and measures to include male and female animals have recently been taken by the British Journal of Pharmacology. [5] As such there is potential to advance science by being inclusive, embracing diversity and non-reproducibility. By employing a mathematical model reproducible results were shown to not always be scientifically accurate while accurate scientific results were not always reproducible. [6] Furthermore, diverging observations between two repeated experiments can lead to better understanding of involved variables and processes, e.g. when quality issues with commercial research antibodies were uncovered. [7] It is routine laboratory practice to order reagents and kits, outsource bioinformatic analyses or employ automated data analysis workflows – a reliance that is a double-edged sword. It saves time and resources but leaves little opportunity for researchers to fully grasp the intricacies of each technique resulting in a fast-paced high-pressure environment. There is not a one-size fits it all approach of good science and reproducibility is imperative but not the only criterion. As a research community we can learn from each other - it is important to record and share lessons learned, establish, follow and improve guidelines and continuously critically reflect upon systems in place.

References 

[1] R. E. Ingham, D. Kroese, I. A. Zasada. Effect of Storage Environment on Hatching of the Cyst Nematode Globodera ellingtonae. J. Nematol., 2015, 47, 45. 

[2] L. Teytelman, A. Stoliartchouk, L. Kindler, B. L. Hurwitz. Protocols. io: virtual communities for protocol development and discussion. PLoS Biol., 2016, 14, e1002538. 

[3] I. Simera, D. Moher, J. Hoey, K. F. Schulz, D. G. Altman. A catalogue of reporting guidelines for health research. Eur. J. Clin. Invest., 2010, 40, 35–53. 

[4] B. Voelkl, L. Vogt, E. S. Sena, H. Würbel. Reproducibility of preclinical animal research improves with heterogeneity of study samples. PLoS Biol., 2018, 16, e2003693. 

[5] J. R. Docherty, S. C. Stanford, R. A. Panattieri, S. P. H. Alexander, G. Cirino, C. H. George, D. Hoyer, A. A. Izzo, Y. Ji, E. Lilley. Sex: A change in our guidelines to authors to ensure that this is no longer an ignored experimental variable. Br. J. Pharmacol., 2019. 

[6] B. Devezer, L. G. Nardin, B. Baumgaertner, E. O. Buzbas. Scientific discovery in a model-centric framework: Reproducibility, innovation, and epistemic diversity. PLoS One, 2019, 14, e0216125. 

[7] M. G. Weller. Quality issues of research antibodies. Anal. Chem. Insights, 2016, 11, ACI-S31614.


Don't forget to register for Better Science through Better Data on November 6th at the Wellcome Collection in London to learn about data sharing and open science.

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