Elsevier releases report "Research Futures: drivers and scenarios for the next decade"

Elsevier has released a report explaining its part in improving “the information system supporting research” over the next decade...

https://www.elsevier.com/connect/elsevier-research-futures-report

Nature now requires data availability statements

NATURE | EDITORIAL

Sharing

Announcement: Where are the data?

07 September 2016

Starting this month, all research papers accepted for publication in Nature and an initial 12 other Nature titles will be required to include information on whether and how others can access the underlying data.

A Bridge from Publishing Words to Publishing Data

December 4, 2014

http://datascience.iq.harvard.edu/blog/bridge-publishing-words-publishing-data

As data publishing technology and data management policies have evolved over the past decade, more academic journals are working with data repositories to disseminate the data associated with published articles. The Dataverse Project at Harvard University’s Institute for Quantitative Social Science (IQSS)recently received a two year grant (2015-2017) from the Sloan Foundation, in partnership with the Odum Institute at the University of North Carolina at Chapel Hill, to collaborate with a variety of publishers, repositories and the international scientific community in order to integrate and automate data publication with more traditional scholarly communication, thus helping make data sharing and preservation an intrinsic and transparent part of the scholarly publication process.

Data Access and Research Transparency (DA-RT): A Joint Statement by Political Science Journal Editors

From the “Workshop on Data Access and Research Transparency (DA-RT) in Political Science.” Convened by the American Political Science Association (APSA) and hosted by the Inter-university Consortium for Political and Social Research (ICPSR), with support from Syracuse University’s Center for Qualitative and Multi-Method Inquiry (CQMI), and the University of Michigan’s Center for Political Studies (CPS).

September 18-19, 2014, Ann Arbor, MI

October 6, 2014

In this joint statement, journal editors commit their respective journals to the principles of data access and research transparency, and to implementing policies requiring authors to make as accessible as possible the empirical foundation and logic of inquiry of evidence-based research.

http://media.wix.com/ugd/fa8393_da017d3fed824cf587932534c860ea25.pdf

Bulletin of the American Meteorological Society 2014 ; e-View

doi: http://dx.doi.org/10.1175/BAMS-D-13-00083.1

Peer Review of Datasets: When, Why, and How

Peer review holds a central place within the scientific communication system. Traditionally, research quality has been assessed by peer review of journal articles, conference proceedings, and books. There is strong support for the peer review process within the academic community, with scholars contributing peer reviews with little formal reward. Reviewing is seen as a contribution to the community as well as an opportunity to polish and refine understanding of the cutting edge of research. This paper discusses the applicability of the peer review process for assessing and ensuring the quality of datasets. Establishing the quality of datasets is a multifaceted task that encompasses many automated and manual processes. Adding research data into the publication and peer review queues will increase the stress on the scientific publishing system, but if done with forethought will also increase the trustworthiness and value of individual datasets, strengthen the findings based on cited datasets, and increase the transparency and traceability of data and publications.

This paper discusses issues related to data peer review, in particular the peer review processes, needs, and challenges related to the following scenarios: 1) Data analyzed in traditional scientific articles, 2) Data articles published in traditional scientific journals, 3) Data submitted to open access data repositories, and 4) Datasets published via articles in data journals.

Capsule Summary

Devising methods for data peer review, if done with forethought, can increase the trustworthiness and value of individual datasets and strengthen research findings.

Journal Article: Nine simple ways to make it easier to (re)use your data

Nine simple ways to make it easier to (re)use your data

Ethan P. White, Elita Baldridge, Zachary T. Brym, Kenneth J. Locey, Daniel J. McGlinn, and Sarah R. Supp

https://peerj.com/preprints/7v1.pdf

Abstract
17 Sharing data is increasingly considered to be an important part of the scientific process. Making your
18 data publicly available allows original results to be reproduced and new analyses to be conducted.
19 While sharing your data is the first step in allowing reuse, it is also important that the data be easy
20 understand and use. We describe nine simple ways to make it easy to reuse the data that you share
21 and also make it easier to work with it yourself. Our recommendations focus on making your data
22 understandable, easy to analyze, and readily available to the wider community of scientists.