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|Title:||Crowdsourcing Opportunities for Research Information Systems||Authors:||Nevolin, Ivan||Keywords:||crowdsourcing;digital library;data quality;current research information systems||Issue Date:||11-Jun-2016||Publisher:||euroCRIS||Source:||"Communicating and Measuring Research Responsibly: Profiling, Metrics, Impact, Interoperability": Proceedings of the 13th International Conference on Current Research Information Systems (2016)
Procedia Computer Science 106: 19-24 (2017)
|Series/Report no.:||CRIS2016: 13th International Conference on Current Research Information Systems (St Andrews, June 9-11, 2016)||Conference:||CRIS2016 – St Andrews||Abstract:||
Research information systems provide data for scientific work valuation. An example of Russian system called Elibrary demonstrate that a number of errors could distort the data. An existing mechanism for data correction relies on the manual validation by the moderator of the system. Research organisations are allowed to reveal and report the data errors under a paid service. Manual moderation, however, increases the time of applications processing. One could speed up the moderation while enabling users to report the errors and to decide about the correction by means of voting. Converting only one of the variety of paid function is hardly to harm the business interests of the operator of the system. Meanwhile the simulation modelling demonstrate the weakness of internal motivation to restore missing citations. One should suggest an external motivation. As an example of external factor, the article suggests scoring system that prevents money transactions. The scores collected could be exchanged for paid service access. Nevertheless, the operator of the system benefits while choosing the parameters of the scoring system in order to ensure that crowdsourcing costs beat the full-time moderator.
Delivered at the CRIS2016 Conference in St Andrews; published in Procedia Computer Science 106 (Mar 2017).-- Contains conference paper (6 pages) and presentation (11 slides).
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