OPRM: Challenges to Including Open Peer Review in Open Access Repositories

Perakakis, Pandelis and Ponsati-Obiols, Agnès and Bernal, Isabel and Sierra, Carles and Osman, Nardine and Mosquera-de-Arancibia, Concha and Lorenzo, Emilio OPRM: Challenges to Including Open Peer Review in Open Access Repositories. Code4Lib Journal, 2017, n. 35. [Journal article (Unpaginated)]

Preview

Text The Code4Lib Journal – OPRM_ Challenges to Including Open Peer Review in Open Access Repositories.pdf Download (149kB) | Preview

English abstract

The peer review system is the norm for many publications. It involves an editor and several experts in the field providing comments for a submitted article. The reviewer remains anonymous to the author, with only the editor knowing the reviewer´s identity. This model is now being challenged and open peer review (OPR) models are viewed as the new frontier of the review process. OPR is a term that encompasses diverse variations in the traditional review process. Examples of this are modifications in the way in which authors and reviewers are aware of each other’s identity (open identities), the visibility of the reviews carried out (open reviews) or the opening up of the review to the academic community (open participation). We present the project for the implementation of an Open Peer Review Module in two major Spanish repositories, DIGITAL.CSIC and e-IEO, together with some promising initial results and challenges in the take-up process. The OPR module, designed for integration with DSpace repositories, enables any scholar to provide a qualitative and quantitative evaluation of any research object hosted in these repositories.

Item type:	Journal article (Unpaginated)
Keywords:	Repositories, Dspace, Open Peer Review
Subjects:	H. Information sources, supports, channels. > HS. Repositories.
Depositing user:	Emilio Lorenzo
Date deposited:	31 Jul 2017 17:45
Last modified:	31 Jul 2017 17:45
URI:	http://hdl.handle.net/10760/31478

References

Sabater-Mir, J. and Sierra, C. (2005) Review on computational trust and reputation models. Artificial Intelligence Review, 24:33–60.

Osman, N., Provetti, A., Riggi, V., and Sierra, C. (2014) MORE: Merged Opinions Reputation Model. In Proceedings of the 12th European Workshop on Multi-agent Systems (EUMAS 2014). Springer.

Callaway, E. (2016) Open peer review finds more takers. Nature 539, 343. doi:10.1038/nature.2016.20969

Downloads

Actions (login required)

View Item