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|Title:||Enriching metadata of an institutional research repository: Mining grey literature/technical reports for research funding-related information||Authors:||Zschocke, Thomas||Keywords:||research information management
|Issue Date:||15-Jun-2018||Publisher:||euroCRIS||Series/Report no.:||CRIS2018: 14th International Conference on Current Research Information Systems (Umeå, June 13-16, 2018)||Conference:||CRIS2018 – Umeå||Abstract:||Funding acknowledgements in research papers are an important resource not only for studying the impact of funding on research, but they also present a utility for mapping the funding landscape, co-funding activities,
the portfolios of certain funding agencies as well as the research performance of scientists and institutions. Even though the major literature databases Scopus and Web of Science have indexed funding
acknowledgements for a number of years, the presence of funding acknowledgements varies in depth and lacks consistency in its usage and detail in research papers.
As it becomes increasingly important for research organizations to show the impact of their research to donor agencies, grey literature/technical reports can serve as a valuable source of information of an organization to complement the missing or incomplete funding acknowledgements in their research information management systems (RIMs). In addition, grey literature can serve as a means to bridge the delay between the research activities and their publication or even the possibility that some research may never be published.
The purpose of this paper is to demonstrate how funding-related information can be extracted from grey literature through text mining and incorporated into the corresponding field of MARC 21 bibliographic records of an institutional research repository of an international agricultural research and development organization for further analysis of its funding and research trends. Enriching the metadata with additional bibliographic notes (funding information) provides additional information about the resource that can be parsed and utilized in a linked open data environment.
|Description:||Extended abstract accepted at the CRIS2018 Conference.-- See event programme at http://www.cris2018.se/schedule/||URI:||http://hdl.handle.net/11366/652|
|Appears in Collections:||Conference|
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checked on May 25, 2018
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