Open Science Approach Research Articles

Improving evidence quality for organisational change management through open science

PurposePopular contingency approaches to organisational change management imply that it is known what and when practices are most appropriate and effective to manage change. The current work aims to question this assumption.Design/methodology/approachThe current work critically reviews the quality of current evidence supporting organisational change management and considers the role of open science practices for the field.FindingsFirst, evidence informing organisational change management is poor, heavily reliant upon unquestioned theoretical models and low-quality cross-sectional or case-study designs. Greater adoption of an evidence-based approach to practice could facilitate organisational change management, but only once a higher quality of evidence is available to inform more robust practical guidance. Second, open science practices look well placed to drive a higher quality of evidence suitable for informing future change management.Originality/valueThe current work highlights the problematic nature of the quality and application of current evidence to inform organisational change and raises a number of recommendations to support future evidence development using an open science approach.

Developing, Analyzing and Sharing Multivariate Datasets: Individual Differences in L2 Learning Revisited

AbstractFollowing the trends established in psychology and emerging in L2 research, we explain our support for an Open Science approach in this paper (i.e., developing, analyzing and sharing datasets) as a way to answer controversial and complex questions in applied linguistics. We illustrate this with a focus on a frequently debated question, what underlies individual differences in the dynamic system of post-pubertal L2 speech learning? We provide a detailed description of our dataset which consists of spontaneous speech samples, elicited from 110 late L2 speakers in the UK with diverse linguistic, experiential and sociopsychological backgrounds, rated by ten L1 English listeners for comprehensibility and nativelikeness. We explain how we examined the source of individual differences by linking different levels of L2 speech performance to a range of learner-extrinsic and intrinsic variables related to first language backgrounds, age, experience, motivation, awareness, and attitudes using a series of factor and Bayesian mixed-effects ordinal regression analyses. We conclude with a range of suggestions for the fields of applied linguistics and SLA, including the use of Bayesian methods in analyzing multivariate, multifactorial data of this kind, and advocating for publicly available datasets. In keeping with recommendations for increasing openness of the field, we invite readers to rethink and redo our analyses and interpretations from multiple angles by making our dataset and coding publicly available as part of our 40th anniversary ARAL article.

A Standardized Project Gutenberg Corpus for Statistical Analysis of Natural Language and Quantitative Linguistics.

The use of Project Gutenberg (PG) as a text corpus has been extremely popular in statistical analysis of language for more than 25 years. However, in contrast to other major linguistic datasets of similar importance, no consensual full version of PG exists to date. In fact, most PG studies so far either consider only a small number of manually selected books, leading to potential biased subsets, or employ vastly different pre-processing strategies (often specified in insufficient details), raising concerns regarding the reproducibility of published results. In order to address these shortcomings, here we present the Standardized Project Gutenberg Corpus (SPGC), an open science approach to a curated version of the complete PG data containing more than 50,000 books and more than word-tokens. Using different sources of annotated metadata, we not only provide a broad characterization of the content of PG, but also show different examples highlighting the potential of SPGC for investigating language variability across time, subjects, and authors. We publish our methodology in detail, the code to download and process the data, as well as the obtained corpus itself on three different levels of granularity (raw text, timeseries of word tokens, and counts of words). In this way, we provide a reproducible, pre-processed, full-size version of Project Gutenberg as a new scientific resource for corpus linguistics, natural language processing, and information retrieval.

Open Systems Pharmacology Community-An Open Access, Open Source, Open Science Approach to Modeling and Simulation in Pharmaceutical Sciences.

Systems pharmacology integrates structural biological and pharmacological knowledge and experimental data, enabling dissection of organism and drug properties and providing excellent predictivity. ...

Abstract 4457: Open science medicinal chemistry: Towards a treatment for DIPG

Abstract Meds4Kids Pharma (M4K)1 is pioneering an open science approach to drug discovery, focussed on the discovery and development of small molecule therapeutics for orphan paediatric cancers. M4K seeks to test the hypothesis that an open science framework can be successfully applied not only to accelerate basic science, using the collective knowledge of the scientific community at large, but also to take an innovative new drug candidate all the way from discovery and clinical proof-of-concept through to product registration, by making use of regulatory data protections and market incentives. Since late 2017, Charles River Early Discovery has been providing in kind drug discovery services to help progress these efforts, including medicinal and synthetic chemistry. The first M4K project aims to generate an orally-available, brain-penetrant therapeutic to treat the diffuse intrinsic pontine glioma (DIPG). DIPG is a rare, aggressive and uniformly fatal childhood brain cancer with a median survival time of 9-12 months and for which there are currently no effective drug treatments. The disease has been shown to be associated with mutations in the ACVR1 gene (activin A receptor, type 1) also known as ALK2 kinase. Early support for the therapeutic hypothesis that an inhibitor of ALK2 kinase would have clinical benefit in DIPG, came from in vivo studies with non-selective ALK2 kinase inhibitors, which both killed DIPG cell lines harbouring the ALK2 mutation and extended lifespan in xenograft mouse models.2 Working collaboratively with M4K and their open science partners, we have made excellent progress towards the identification of potent, selective, brain penetrant ALK2 inhibitors starting from the known inhibitor LDN-214117, previously described for FOP (fibrodysplasia ossificans progressiva).3 Our current lead compound has an excellent in vitro and in vivo profile showing high oral bioavailability and brain penetration in a mouse PK study and is progressing to proof of concept studies. In addition we are progressing with the identification of a back-up series.

Plant health emergencies demand open science: Tackling a cereal killer on the run.

Outbreaks of emerging plant diseases and insect pests are increasing at an alarming rate threatening the food security needs of a booming world population. The role of plant pathologists in addressing these threats to plant health is critical. Here, we share our personal experience with the appearance in Bangladesh of a destructive new fungal disease called wheat blast and stress the importance of open-science platforms and crowdsourced community responses in tackling emerging plant diseases. Benefits of the open-science approach include recruitment of multidisciplinary experts, application of cutting-edge methods, and timely replication of data analyses to increase the robustness of the findings. Based on our experiences, we provide some general recommendations and practical guidance for responding to emerging plant diseases.

An Open Science Approach to Artificial Intelligence in Healthcare.

Summary Objectives : Artificial Intelligence (AI) offers significant potential for improving healthcare. This paper discusses how an “open science” approach to AI tool development, data sharing, education, and research can support the clinical adoption of AI systems. Method : In response to the call for participation for the 2019 International Medical Informatics Association (IMIA) Yearbook theme issue on AI in healthcare, the IMIA Open Source Working Group conducted a rapid review of recent literature relating to open science and AI in healthcare and discussed how an open science approach could help overcome concerns about the adoption of new AI technology in healthcare settings. Results : The recent literature reveals that open science approaches to AI system development are well established. The ecosystem of software development, data sharing, education, and research in the AI community has, in general, adopted an open science ethos that has driven much of the recent innovation and adoption of new AI techniques. However, within the healthcare domain, adoption may be inhibited by the use of “black-box” AI systems, where only the inputs and outputs of those systems are understood, and clinical effectiveness and implementation studies are missing. Conclusions : As AI-based data analysis and clinical decision support systems begin to be implemented in healthcare systems around the world, further openness of clinical effectiveness and mechanisms of action may be required by safety-conscious healthcare policy-makers to ensure they are clinically effective in real world use.

Big Data Needs Big Governance: Best Practices From Brain-CODE, the Ontario-Brain Institute's Neuroinformatics Platform.

The Ontario Brain Institute (OBI) has begun to catalyze scientific discovery in the field of neuroscience through its large-scale informatics platform, known as Brain-CODE. The platform supports the capture, storage, federation, sharing, and analysis of different data types across several brain disorders. Underlying the platform is a robust and scalable data governance structure which allows for the flexibility to advance scientific understanding, while protecting the privacy of research participants. Recognizing the value of an open science approach to enabling discovery, the governance structure was designed not only to support collaborative research programs, but also to support open science by making all data open and accessible in the future. OBI’s rigorous approach to data sharing maintains the accessibility of research data for big discoveries without compromising privacy and security. Taking a Privacy by Design approach to both data sharing and development of the platform has allowed OBI to establish some best practices related to large-scale data sharing within Canada. The aim of this report is to highlight these best practices and develop a key open resource which may be referenced during the development of similar open science initiatives.

Knowledge and Perceptions of Open Science among Researchers—A Case Study for Colombia

Open science can provide researchers diverse opportunities to collaborate, disseminate their research results, generate important impacts in the scientific community, and engage in effective and efficient science for the benefit of society. This study seeks to analyse and evaluate researchers’ knowledge of open science in Colombia using a survey to determine adequate instruments with which to improve research in the framework of open science. The aim of the study is to determine researchers’ current awareness of open science by considering demographic characteristics to analyse their attitudes, values, and information habits as well as the levels of institutionalism and social appropriation of open science. A representative sample of Colombian researchers was selected from the National Research System. An anonymous online survey consisting of 34 questions was sent to all professors and researchers at Colombian universities and research institutes. Sampling was random and stratified, which allowed for a representative sample of different categories of researchers, and principal component analysis (PCA) was used for the sample design. A total of 1042 responses were received, with a 95% confidence level and a margin of error of 3%. The majority of respondents knew about open science, especially in relation to open science tools (software, repositories, and networks) and open data. Researchers consider open science to be positively impacted by factors such as the rise of digital technologies, the search for new forms of collaboration, the greater availability of open data and information, and public demand for better and more effective science. In contrast, a lack of resources to develop research activities within the open science approach and the limited integration between traditional and open science are identified as the most important barriers to its use in research. These results are important for building adequate open science policy in Colombia.

Open Science approaches at the University of Edinburgh

Watch the VIDEO.The University of Edinburgh is a large, research-intensive, civic university at the heart of Scotland’s capital. As a member of the League of European Research Universities (LERU), the Universitas 21 consortium and the Russell Group, we value and cultivate partnerships and collaborations as second nature, and seek to be recognised among the world’s top universities. These are interesting times for us, not least from Open (and data-driven) Science perspectives. In May 2018 the LERU Rectors Assembly assembled in Edinburgh, where they collectively endorsed LERU’s Roadmap for Open Science; a movement which requires considerable alterations to traditional researcher behaviours, and increasingly balancing intellectual investment and ownership of research with “the common good.” More recently, in August the UK Prime Minister and the Scottish First Minister met at the University to launch the Edinburgh and South East Scotland City Region Deal, a £1.3bn investment package designed to increase the contribution of research, data analytics expertise and graduate skills to the region’s economy, ultimately aiming to make Edinburgh “the data capital of Europe.” The timing of these developments provides a challenge, however, as Edinburgh, Scotland and the rest of the UK prepare to leave the European Union in the Spring of 2019. In an ideal world Science and Scholarship would be independent of political shifts, focused as they are on ideals of universal truth, but the means via which research is funded, performed and disseminated are necessarily grounded in political reality. Edinburgh’s default responses to the changes and challenges we face are to influence them positively – or mitigate them proactively – wherever we can, and to prepare ourselves for their impact where we cannot do otherwise. The University’s newly integrated Research Data Support (RDS) team is a cornerstone of our institutional Digital Research Services. We aim to provide holistic, responsive, tailored and researcher-focused support to the University community, helping collectively meet contemporary expectations in scholarly communications, including Open Science requirements to make data (and code) available alongside publications to enable their conclusions to be reproduced. The RDS has published a Roadmap for ongoing development, and alongside other infrastructural and support units such as the Scholarly Communications and Research Information Systems functions – and together with the externally focused infrastructure, advocacy and skills development centres that Edinburgh hosts, such as the Digital Curation Centre and the Software Sustainability Institute – we are a key component of the University’s broader Open Science strategy. In this presentation we will describe and discuss Edinburgh’s Open Science environment and approaches, within the broader landscape of changing expectations, political risks and scientific and societal opportunities. We will discuss the benefits and challenges of Open approaches within and beyond the Sciences, and the challenges involved in turning the European Commission’s “as open as possible, as closed as necessary” dictum into reality, including outreach and skills development activities. Finally we will look at the University’s current RDS Roadmap, and consider how this might develop and adapt in the exciting (and potentially turbulent) years ahead.

Exploring the single-cell RNA-seq analysis landscape with the scRNA-tools database.

As single-cell RNA-sequencing (scRNA-seq) datasets have become more widespread the number of tools designed to analyse these data has dramatically increased. Navigating the vast sea of tools now available is becoming increasingly challenging for researchers. In order to better facilitate selection of appropriate analysis tools we have created the scRNA-tools database (www.scRNA-tools.org) to catalogue and curate analysis tools as they become available. Our database collects a range of information on each scRNA-seq analysis tool and categorises them according to the analysis tasks they perform. Exploration of this database gives insights into the areas of rapid development of analysis methods for scRNA-seq data. We see that many tools perform tasks specific to scRNA-seq analysis, particularly clustering and ordering of cells. We also find that the scRNA-seq community embraces an open-source and open-science approach, with most tools available under open-source licenses and preprints being extensively used as a means to describe methods. The scRNA-tools database provides a valuable resource for researchers embarking on scRNA-seq analysis and records the growth of the field over time.

Scalable Open Science Approach for Mutation Calling of Tumor Exomes Using Multiple Genomic Pipelines.

The Cancer Genome Atlas (TCGA) cancer genomics dataset includes over 10,000 tumor-normal exome pairs across 33 different cancer types, in total >400 TB of raw data files requiring analysis. Here we describe the Multi-Center Mutation Calling in Multiple Cancers project, our effort to generate a comprehensive encyclopedia of somatic mutation calls for the TCGA data to enable robust cross-tumor-type analyses. Our approach accounts for variance andbatch effects introduced by the rapid advancement of DNA extraction, hybridization-capture, sequencing, and analysis methods over time. We present best practices for applying an ensemble of seven mutation-calling algorithms with scoring and artifact filtering. The dataset created by this analysis includes 3.5 million somatic variants and forms the basis for PanCan Atlas papers. The results have been made available to the research community along with the methods used to generate them. This project is theresult of collaboration from a number of institutes and demonstrates how team science drives extremely large genomics projects.

Forecasting the ongoing invasion of Lagocephalus sceleratus in the Mediterranean Sea

Invasive species from the Suez Canal, also named “Lessepsian species”, often have an ecological and financial impact on marine life, fisheries, human well-being and health in the Mediterranean Sea. Among these, the silver-cheeked toad-fish Lagocephalus sceleratus (Gmelin, 1789) has rapidly colonised the eastern Mediterranean basin and is currently moving westwards. This pufferfish has a highly opportunistic behaviour, it attacks fish captured in nets and lines and seriously damages fishing gears and catch. It is a highly-toxic species with no immediate economic value for the Mediterranean market, although it currently represents 4% of the weight of the total artisanal catches. Consequently, the possible effects on Mediterranean fisheries and health require to enhance our understanding about the future geographical distribution of this pufferfish in the whole basin.In this paper, an overall habitat suitability map and an effective geographical spread map for L. sceleratus at Mediterranean scale are produced by using cloud computing-based algorithms to merge seven machine learning approaches. Further, the potential impact of the species is estimated for several Mediterranean Sea subdivisions: The major fishing areas of the Food and Agriculture Organization of the United Nations, the Economic Exclusive Zones, and the subdivisions of the General Fisheries Commission for the Mediterranean Sea. Our results suggest that without an intervention, L. sceleratus will continue its rapid spread and will likely have a high impact on fisheries. The presented method is generic and can be applied to other invasive species. It is based on an Open Science approach and all processes are freely available as Web services.

Reproducibility in the Field: Transparency, Version Control and Collaboration on the Project Panormos Survey

Abstract Archaeological fieldwork is rarely considered reproducible in the sense of the ideal scientific method because of its destructive nature. But new digital technology now offers field practitioners a set of tools that can at least increase the transparency of the data-collection process as well as bring other benefits of an Open Science approach to archaeology. This article shares our perspectives, choices and experiences of piloting a set of tools (namely: ODK, Git, GitLab CE and R) which can address reproducibility of fieldwork in the form of an intensive survey project in western Turkey, and highlights the potential consequences of Open Science approaches for archaeology as a whole.

Open science in the Two!Ears project—Experiences and best practices

Two!Ears was an EU funded project for binaural auditory modeling with ten international partners involved. One of the project goals was to follow an Open Science approach in all stages. This turned out to be a challenging task as the project involved huge amounts of software, acoustical measurements, and data from listening tests. On the other hand, it was obvious from the positive experience with the Auditory Modelling Toolbox that an Open Science approach would have a positive impact and foster progression afterwards. As there existed no ready solution to achieve this goal at the beginning of the project, different paths for data management were tested. It was especially challenging to provide a solution for data storage. Here, the goal was not only the long term accessibility of the data, but also the revision control of public and private data for the development inside the project. In the end, the project was able to make most of its software and data publicly available, but struggled to apply the re...

Toward an integrative approach to numerical cognition.

In response to the commentaries, we have refined our suggested model and discussed ways in which the model could be further expanded. In this context, we have elaborated on the role of specific continuous magnitudes. We have also found it important to devote a section to evidence considered the "smoking gun" of the approximate number system theory, including cross-modal studies, animal studies, and so forth. Lastly, we suggested some ways in which the scientific community can promote more transparent and collaborative research by using an open science approach, sharing both raw data and stimuli. We thank the contributors for their enlightening comments and look forward to future developments in the field.

OpenUP’s Open Science Pilots. Designing innovative peer review and dissemination pilot studies

The review-disseminate-assess cycle is a multifaceted process involving different stakeholders: researchers, publishers, research institutions and funders, private companies, industry, and citizens. The H2020 project OpenUP aspires to bring all these stakeholders into an open dialogue to consensually identify and spread the review-disseminate-assess mechanisms advancing evolving practices of RRI in an Open Science context. OpenUP will actively engage research communities and implement a series of hands-on pilots to validate OpenUP’s proposed (open) peer review, innovative dissemination, and impact indicator frameworks. The pilots will be carried out in close cooperation with selected, devoted research communities from four scientific areas: arts and humanities, social sciences, life sciences, and energy. This poster visualises UpenUP’s pilot design exemplified by two of the seven Open Science Pilots to be conducted by the project: 1) Open Peer Review for Conferences, and 2) Addressing and Reaching Businesses and the Public with Research Output.The first pilot will evaluate the feasibility and acceptance of open peer reviewing in a conference setting. The specific implementation of the applied schema will be determined by the results from the state of the art study as well as the user questionnaire answers from other work packages of OpenUP. In comparison to the traditional way (double-blind evaluation of submitted papers by assigned reviewers chosen by the conference organisers) the new schema should allow for a more open and fair process as well as give additional incentives to reviewers. The actual pilot study will be conducted at a medium sized conference in consultation with the conference organisers. Follow-up questionnaires and interviews will show if the stakeholders preferred the new process and can provide constructive feedback for improvements and policy decisions.The second pilot will test existing and potential alternative forms, formats, and channels of open science communication, and explore how the targeted audiences, in particular businesses and the public, can be best reached via these channels. In a preparatory phase the team will map open science communication formats/channels and their targeted audiences. The team will conduct a workshop to elicit the targeted stakeholders’ requirements and expectations towards a useful and appealing communication of scientific contents. This will be the basis of the second pilot presented here. It will actively involve one or more energy research community projects beyond the OpenUP consortium. The goals are to test the previously established communication standards and channels for the energy area, and evaluate the impact and resonance at the targeted audiences.By actively involving research communities and other relevant stakeholders into the pilots, OpenUP will not only evaluate the practicability of the identified open peer review, innovative dissemination, and impact measurement methods in particular settings. It also intends to create and disseminate success stories, best/good practices, and policy recommendations, which will help further communities to implement working Open Science approaches in their research evaluation and communication strategies.

AN OPEN SCIENCE APPROACH TO GIS-BASED PALEOENVIRONMENT DATA

Abstract. Paleoenvironmental studies and according information (data) are abundantly published and available in the scientific record. However, GIS-based paleoenvironmental information and datasets are comparably rare. Here, we present an Open Science approach for creating GIS-based data and maps of paleoenvironments, and Open Access publishing them in a web based Spatial Data Infrastructure (SDI), for access by the archaeology and paleoenvironment communities. We introduce an approach to gather and create GIS datasets from published non-GIS based facts and information (data), such as analogous maps, textual information or figures in scientific publications. These collected and created geo-datasets and maps are then published, including a Digital Object Identifier (DOI) to facilitate scholarly reuse and citation of the data, in a web based Open Access Research Data Management Infrastructure. The geo-datasets are additionally published in an Open Geospatial Consortium (OGC) standards compliant SDI, and available for GIS integration via OGC Open Web Services (OWS).

AN OPEN SCIENCE APPROACH TO GIS-BASED PALEOENVIRONMENT DATA

Paleoenvironmental studies and according information (data) are abundantly published and available in the scientific record. However, GIS-based paleoenvironmental information and datasets are comparably rare. Here, we present an Open Science approach for creating GIS-based data and maps of paleoenvironments, and Open Access publishing them in a web based Spatial Data Infrastructure (SDI), for access by the archaeology and paleoenvironment communities. We introduce an approach to gather and create GIS datasets from published non-GIS based facts and information (data), such as analogous maps, textual information or figures in scientific publications. These collected and created geo-datasets and maps are then published, including a Digital Object Identifier (DOI) to facilitate scholarly reuse and citation of the data, in a web based Open Access Research Data Management Infrastructure. The geo-datasets are additionally published in an Open Geospatial Consortium (OGC) standards compliant SDI, and available for GIS integration via OGC Open Web Services (OWS).

Can Open Science save us from a solar-driven monsoon?

Numerous studies have been published claiming strong solar influences on the Earth’s weather and climate, many of which include documented errors and false-positives, yet are still frequently used to substantiate arguments of global warming denial. Recently, Badruddin & Aslam (2015) reported a highly significant relationship between the Indian monsoon and the cosmic ray flux. They found strong and opposing linear trends in the cosmic ray flux during composites of the strongest and weakest monsoons since 1964, and concluded that this relationship is causal. They further speculated that it could apply across the entire tropical and sub-tropical belt and be of global importance. However, examining the original data reveals the cause of this false-positive: an assumption that the data’s underlying distribution was Gaussian. Instead, due to the manner in which the composite samples were constructed, the correlations were biased towards high values. Incorrect or problematic statistical analyses such as this are typical in the field of solar-terrestrial studies, and consequently false-positives are frequently published. However, the widespread adoption of Open Science approaches, placing an emphasis on reproducible open-source analyses as demonstrated in this work, could remedy the situation.