ResEval mash: a mashup tool for advanced research evaluation

Authors:
Muhammad Imran;Felix Kling;Stefano Soi;Florian Daniel;Fabio Casati;Maurizio Marchese
Affiliations:
University of Trento, Trento, Italy;University of Trento, Trento, Italy;University of Trento, Trento, Italy;University of Trento, Trento, Italy;University of Trento, Trento, Italy;University of Trento, Trento, Italy
Venue:
Proceedings of the 21st international conference companion on World Wide Web
Year:
2012

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Abstract

In this demonstration, we present ResEval Mash, a mashup platform for research evaluation, i.e., for the assessment of the productivity or quality of researchers, teams, institutions, journals, and the like - a topic most of us are acquainted with. The platform is specifically tailored to the need of sourcing data about scientific publications and researchers from the Web, aggregating them, computing metrics (also complex and ad-hoc ones), and visualizing them. ResEval Mash is a hosted mashup platform with a client-side editor and runtime engine, both running inside a common web browser. It supports the processing of also large amounts of data, a feature that is achieved via the sensible distribution of the respective computation steps over client and server. Our preliminary user study shows that ResEval Mash indeed has the power to enable domain experts to develop own mashups (research evaluation metrics); other mashup platforms rather support skilled developers. The reason for this success is ResEval Mash's domain-specificity.