The layered cake of FAIR coordination: how many is too many?

Guest post by Alastair Dunning1, Susanna-Assunta Sansone2, Marta Teperek1

(authors listed alphabetically by surname)

1 Delft University of Technology, the Netherlands; 2 Oxford e-Research Centre, Department of Engineering Science, University of Oxford, UK

Science is living in the era of data – the reuse of other people’s data can drive new research questions and products, and inspire new scientific discoveries. This was the motivation behind the FAIR Principles (published in 2016), which provide researchers with a framework to improve the quality of their research: making their data more Findable, Accessible, Interoperable and Reusable. To turn these aspirational principles into reality, however, we need to provide researchers with FAIR-enabling tools and services that make frictionless the (complex) technical machinery of (meta)data standards and identifiers that underpins FAIR. Service providers, librarians, journal publishers and funders, among others, are actively working to deliver the next generation framework for FAIR data, which is collaborative, interdisciplinary and sustainable. FAIR has also become the (core) mission of a growing number of initiatives – especially in Europe, USA and Australia – encompassing R&D projects and programmes, institutional, national and global service provision, alliances and societies, training and educational efforts. In particular, numerous policy makers from around the world have articulated a vision of global open science and embraced FAIR as the driving principles. In Europe, for example, the vision is being realised through the ambitious European Open Science Cloud (EOSC) programme, across all disciplines. Read more

Call for submissions: High-throughput 3D screening

Call for Submissions

High-throughput 3D Screening

Organizer: Dr. Kaylene Simpson (Peter Mac)

Scientific Data is inviting submissions releasing and describing data from high-throughput screens employing cutting-edge 3D cell or tissue culture systems. Screens using a wide range of perturbations will be considered, including chemical libraries or functional genomic screens. Priority will be given to submissions that employ high-content imaging techniques, and which have particular value for methods development in this growing area.

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Announcing the first members of our new Senior Editorial Board

Today, we are pleased to announce the formation of a new Senior Editorial Board, the members of which will guide our larger Editorial Board membership and will play a lead role in setting standards for papers submitted to Scientific Data.
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Call for submissions: Reproducible data processing

Call for Submissions

Special Article Collection on
Reproducible data processing

In collaboration with Harvard Dataverse

Scientific Data is inviting submissions that provide compelling examples of how portable computing technologies can be used to create transparent, reproducible descriptions of data processing workflows. Submissions considered for this collection should describe valuable research datasets that involve some form of computational processing in their production. Authors should provide source code for all data processing steps in a way that would allow others, including referees, to easily understand and execute all processing steps. Read more

Call for submissions: Multiomics data

Call for Submissions

Special Article Collection on
Multiomics data

Organizers: Ana Conesa, Sonia Tarazona

Scientific Data is inviting submissions that release and describe datasets from studies that employed multiple ‘omic’ profiling technologies, including, but not limited to, genomics, epigenomics, transcriptomics, proteomics and metabolomics. Submitted articles may be considered for inclusion in a special article collection to be published at the journal. Read more

New checklist for ‘complementary’ Data Descriptors

Today, we are releasing a new checklist for authors drafting Data Descriptors that build or expand on other publications. It is now available on our Editorial & Publishing Policies page and from the link below.

Complementary Data Descriptor Checklist

Data Descriptors are designed to be complementary to traditional research articles. Researchers can describe and release their data in a more complete manner, and may be able to reduce their reliance on supplementary material, which can be hard to find and poorly accessible during peer-review, and which offers authors little additional credit. About half of the Data Descriptors published at Scientific Data so far are linked to one or more research articles at other journals. Read more

Author’s Corner: Open data, open review and open dialogue in making social sciences plausible

Guest post by Quan-Hoang Vuong of Centre for Interdisciplinary Social Research, Western University Hanoi, Vietnam

A growing awareness of the lack of reproducibility has undermined society’s trust and esteem in social sciences. In some cases, well-known results have been fabricated or the underlying data have turned out to have weak technical foundations.

Dr Quan Hoang Vuong

Quan Hoang Vuong

Many researchers have investigated the plausibility of findings in the social sciences and humanities. A typical example is the mysterious Critical Minimum Positivity Ratio 2.9013 by Fredrickson and Losada (2005), which claimed to show that there exists such a positivity ratio and that “an individual’s degree of flourishing could be predicted by that person’s ratio of positive to negative emotions over time”. This ratio had once been a well-known, highly influential and greatly admired psychological “constant” until it was shown by Brown, Sokal and Friedman (2013) to be an unfounded, arbitrary and meaningless number.

To address the plausibility problem, I suggest that a combination of open data, open peer-review and open community dialogue, could serve as a feasible option for the social sciences.

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Author’s Corner: Revisiting the personalities of wild chimpanzees

NIK_7884-small

Alexander Weiss

Guest post by Alexander Weiss of the University of Edinburgh, United Kingdom

Early on in her behavioural observations of the chimpanzees at what is now known as Gombe National Park, Jane Goodall was struck by their personalities, which were as distinct as our own1. However, upon sharing her observations with a ‘respected ethologist’, she was told that, yes, animals differed in their behaviour, but that this was best ‘swept under the carpet’ (pp 11-12)2. Read more

New step-by-step submission guidelines

Today, we released a thoroughly revised and improved version of our Submission Guidelines, making submitting to Scientific Data easier than ever before.

The process of drafting and submitting a manuscript to the journal is now organized into seven clear steps. In Step 1, we provide a simple summary of the journal’s four main content-types (Data Descriptor, Article, Analysis and Comment), so authors can be sure they have selected the most appropriate format before beginning to draft their manuscript. In the next steps, we provide detailed information on depositing data, and on drafting and submitting a manuscript to the journal. These steps focus centrally on the Data Descriptor – the journal’s main content-type and the one that differs most from formats at other journals – but we have also improved the information we provide for authors drafting other content-types. Read more

Call for submissions: Rescue your data

Scientific Data is inviting submissions that release data underlying influential research papers published three or more years ago, for potential inclusion in a special collection to be launched in 2018. In particular, we are encouraging submissions that describe important datasets that were not practical to share online with the original publication, due to technical constraints or a lack of appropriate data repositories at the time.

To be considered for publication among the first papers in this collection, manuscripts should be submitted to the editorial office by 1st December 2017. Read more