Nowadays, many R&I institutions are presently implementing mechanisms to measure and rate their scientific production so as to comply with current legislation and to support research management and decision making. In many cases, they rely on the implementation of current research information systems (CRIS). This is a challenging task that often requires major human intervention and supervision to manually include all scientific production, projects, patents, etc., in the system. In this paper, we present Ogmios, a system that aims to reduce the time and effort of this process. Ogmios is a CRIS that automatically extracts and combines information from different sources, such as academic social networks or academic search engines. This redundancy helps to reduce potential errors. Additionally, Ogmios relies on other sources, such as online subscription-based scientific citation indexing services, to add metadata to information collected for ranking purposes. We have assessed the performance of this system with a sample of 216 researchers from the University of Málaga; 815 profiles were retrieved and validated with an accuracy of over 90% in profile detection. The main contribution of this work is Ogmios’s autonomous capacity to retrieve and combine all necessary information on scientific profiles and production from different data sources and, also, its adaptability to any university or research institution.
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Ogmios is a project supported and funded by the Vice-Rectorate for Research and Knowledge Transfer of the University of Málaga, Spain.
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Verdugo, N., Guzmán, E. & Urdiales, C. Integrating researchers’ scientific production information through Ogmios. Knowl Inf Syst (2020). https://doi.org/10.1007/s10115-020-01479-8
- Research information system
- Data extraction
- Knowledge engineering
- Author disambiguation
- Research of research