Marta Poblet – InfoDoc MicroVeille

Authors : Amir Aryani, Marta Poblet, Kathryn Unsworth, Jingbo Wang, Ben Evans, Anusuriya Devaraju, Brigitte Hausstein, Claus-Peter Klas, Benjamin Zapilko, Samuele Kaplun

This paper describes the open access graph dataset that shows the connections between Dryad, CERN, ANDS and other international data repositories to publications and grants across multiple research data infrastructures.

The graph dataset was created using the Research Graph data model and the Research Data Switchboard (RD-Switchboard), a collaborative project by the Research Data Alliance DDRI Working Group (DDRI WG) with the aim to discover and connect the related research datasets based on publication co-authorship or jointly funded grants.

The graph dataset allows researchers to trace and follow the paths to understanding a body of work. By mapping the links between research datasets and related resources, the graph dataset improves both their discovery and visibility, while avoiding duplicate efforts in data creation.

Ultimately, the linked datasets may spur novel ideas, facilitate reproducibility and re-use in new applications, stimulate combinatorial creativity, and foster collaborations across institutions.

URL : A Research Graph dataset for connecting research data repositories using RD-Switchboard

Alternative location : https://www.nature.com/articles/sdata201899

Authors : Jonathan P. Tennant, Jonathan M. Dugan, Daniel Graziotin, Damien C. Jacques, François Waldner, Daniel Mietchen, Yehia Elkhatib, Lauren B. Collister, Christina K. Pikas, Tom Crick, Paola Masuzzo, Anthony Caravaggi, Devin R. Berg, Kyle E. Niemeyer, Tony Ross-Hellauer, Sara Mannheimer, Lillian Rigling, Daniel S. Kat, Bastian Greshake Tzovaras, Josmel Pacheco-Mendoza, Nazeefa Fatima, Marta Poblet, Marios Isaakidis, Dasapta Erwin Irawan, Sébastien Renaut, Christopher R. Madan, Lisa Matthias, Jesper Nørgaard Kjær, Daniel Paul O’Donnell, Cameron Neylon, Sarah Kearns, Manojkumar Selvaraju, Julien Colomb

Peer review of research articles is a core part of our scholarly communication system. In spite of its importance, the status and purpose of peer review is often contested. What is its role in our modern digital research and communications infrastructure?

Does it perform to the high standards with which it is generally regarded? Studies of peer review have shown that it is prone to bias and abuse in numerous dimensions, frequently unreliable, and can fail to detect even fraudulent research.

With the advent of Web technologies, we are now witnessing a phase of innovation and experimentation in our approaches to peer review. These developments prompted us to examine emerging models of peer review from a range of disciplines and venues, and to ask how they might address some of the issues with our current systems of peer review.

We examine the functionality of a range of social Web platforms, and compare these with the traits underlying a viable peer review system: quality control, quantified performance metrics as engagement incentives, and certification and reputation.

Ideally, any new systems will demonstrate that they out-perform current models while avoiding as many of the biases of existing systems as possible. We conclude that there is considerable scope for new peer review initiatives to be developed, each with their own potential issues and advantages.

We also propose a novel hybrid platform model that, at least partially, resolves many of the technical and social issues associated with peer review, and can potentially disrupt the entire scholarly communication system.

Success for any such development relies on reaching a critical threshold of research community engagement with both the process and the platform, and therefore cannot be achieved without a significant change of incentives in research environments.

URL : A multi-disciplinary perspective on emergent and future innovations in peer review

DOI : http://dx.doi.org/10.12688/f1000research.12037.1