New step-by-step submission guidelines

Posted by Andrew Hufton | Categories: ,

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

Posted by Andrew Hufton | Categories:

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

Author’s corner: Providing incentives and ensuring quality in citizen science

Posted by Andrew Hufton | Categories: ,

Guest post by Steffen Fritz, Linda See & Ian McCallum of the International Institute for Applied Systems Analysis, Laxenburg, Austria

author-corner-photos-june-2017

Steffen Fritz, Linda See & Ian McCallum

Citizen science, the collection or analysis of research data by the general public, has existed in one form or another for centuries, with contributions ranging from plant and animal observations to weather phenonmena1. In the field of land cover and land use, however, its application is relatively new2. Previously this was a task left largely to governments, research institutes and global bodies. With the recent availability of high resolution satellite imagery, this has changed, opening up new possibilities for citizen participation3. In our recent article in Nature Research’s Scientific Data4, we have made available a global dataset of crowdsourced land cover and land use reference data, containing the results of our first four citizen-science campaigns. Read more

Research data policy going back to basics in Barcelona

Posted by Iain Hrynaszkiewicz | Categories:

This blog was written by Iain Hrynaszkiewicz, Head of Data Publishing.
IMG_0004

This week the Springer Nature research data team are exploring how our research data policy initiative can help facilitate wider adoption of clear, consistent policies for publishing research data.

We are attending the Research Data Alliance (RDA) 9th Plenary meeting in Barcelona where, amongst other things, we are chairing the inaugural Interest Group meeting on standardisation of policy for publishing research data.

At a hastily organised unofficial meeting at the RDA 8th Plenary it became clear there is a lot of interest in addressing the problems researchers face in understanding and complying with data policies. We are now – officially – working via the RDA to do this. Read more

Call for submissions: Open research data resources

Posted by Varsha Khodiyar | Categories: ,

UPDATE: In parallel with a recent Nature Genetics Editorial, we are now extending this call to encourage submissions on compelling resources or technologies that advance the use of open linked data models in promoting the FAIR Principles. In particular, we are inviting submissions that present compelling applications of open linked data models, which promote the use of, compliance to, and validation against existing community data standards.  The deadline for submissions has been extended to 30th September 2017.
Read more

Data sharing recommendations to the NIH

Posted by Varsha Khodiyar | Categories:

This blog was written by Iain Hrynaszkiewicz, Head of Data Publishing.

Springer Nature has responded to the US National Institutes of Health’s request for information (RFI) on Strategies for NIH Data Management, Sharing, and Citation.  Our detailed response covers a multitude of issues on barriers to and incentives for sharing data and software that support published research. Read more

Expanding our generalist data repository options

Posted by Andrew Hufton | Categories: ,

Since our launch in 2014, we have published descriptions of datasets archived at more than 45 different repositories. This diversity is a key part of the Scientific Data philosophy; we aim to support as wide a range of data repositories as possible, within the constraints of our strong policies on data preservation and openness (learn more). So our authors find the right repository for their data, we maintain and regularly update a list of recommended open data repositories, which is also used more widely by the Nature Research journals and our publisher Springer Nature. Last year we also improved our support for institutional repositories. Read more

An open approach to Huntington’s disease research

Posted by Andrew Hufton | Categories: ,

Guest post by Rachel Harding, postdoctoral fellow at the Structural Genomics Consortium, University of Toronto, Canada

Rachel Harding

Rachel Harding

Huntington’s disease (HD) is a fatal neurodegenerative disorder caused by a mutation in the huntingtin gene1. The progressive break down of brain neuronal cells in HD patients leads to deteriorating mental and physical abilities over a 10-20 year period prior to death, the symptoms often described as having Parkinson’s disease, Alzheimer’s disease and amyotrophic lateral sclerosis (ALS) simultaneously2. At the start of the huntingtin gene there is a CAG trinucleotide repeat region that encodes a stretch of poly-glutamine residues in the amino-terminus of the encoded protein. This repeat tract is expanded in HD patients. The repeat length of this region correlates with the age of symptom onset3. Affecting approximately 1 in 10,000 of the population4, rare juvenile forms of the disease exist in patients with the longest CAG expansions, although adult-onset HD patients typically have between 40-50 CAG repeats with symptom onset beginning between the ages of 35-50. Read more

Data Matters: Interview with Ben Lehner

Posted by Andrew Hufton | Categories: ,

Ben Lehner

Ben Lehner

Ben Lehner is a group leader at the EMBL/CRG Systems Biology Research Unit, in Barcelona, Spain.

Could you briefly introduce your own research?

My lab works on genetics, essentially. It’s a mixture of producing our own data, and using other people’s data. We’re a combined wet and dry lab, and we work with organisms and data from bacteria, through yeast, worms, all the way up to human clinical genetic data.

Broadly, how open do you think the human genomics community has been to sharing data?

I think there is a cultural history here that’s important. You can divide the human genomics community into two groups. Read more

Author’s corner: A testbed for reproducible and standardized human MRI connectomics

Posted by Varsha Khodiyar | Categories: ,

Guest post by Xi-Nian Zuo, Project Coordinator and Co-Founder of Consortium for Reliability and Reproducibility (CoRR), Professor of Psychology and Director of the Magnetic Resonance Imaging Research Center in the Institute of Psychology at Chinese Academy of Sciences, China.

XI-NIAN ZUO

Xi-Nian Zuo

About a decade ago (2006), as a PhD student graduating from the School of Mathematics at Beijing Normal University, I stepped into the field of neuroimaging of the human brain by way of a short job interview offered by Dr. Yu-Feng Zang, my postdoc mentor in China. The most important thing that I learned and developed during my post doc training was how to question a study, an indication likely of my somewhat different background (mathematics versus brain sciences). Probability and statistics became my major tools in bridging new learning experiences with my existing knowledge, pushing me to further pursue research training offered by Dr. Michael Peter Milham at New York University. Ongoing work in his laboratory really interested me, particularly test-retest reliability of resting-state functional connectivity1, the first study of test-retest reliability in the nascent field of functional connectivity. However, an obvious limitation existed to that study, and a series of test-retest reliability studies I carried out subsequently2; the small sample size. This directly motivated me to seek and build up a truly big data set for test-retest reliability in connectomics. Read more