Global Views Monthly (GVM) and Elsevier, the global information analytics business specialising in science and health, commemorated their three-year collaboration at a signing ceremony to provide data for Taiwan and GVM's Taiwan University Ranking.
The three-year annual ranking exercise – from 2019 to 2021 – will use the most comprehensive and balanced performance indicators to evaluate Taiwanese universities on: research achievement, teaching performance, internationalization, academic-industry collaboration, societal impact, and financial management.
Drawing data from Elsevier's Scopus, the industry-leading abstract and citation database of peer-reviewed academic literature, GVM will be able to analyse in detail research activity from Taiwan's higher education institutions. Elsevier's SciVal analytics tool was used to perform research metrics analysis to provide Taiwanese universities a broader view of their research performance that includes economic impact and international collaboration.
At the ceremony, GVM also launched the 2019 Taiwan University Ranking, the first from its three-year collaboration with Elsevier following a successful pilot ranking exercise in 2018 by the two companies.
The quality, breadth and reliability of Scopus data and the power of SciVal performance metrics is the leading reason ranking organisations choose Elsevier to underpin their evaluations and reports.
Launched in 1986, Global Views Monthly has emerged to become Taiwan's leading business magazine specializing in macro-economics, management, technology and humanities that is read by industry visionaries, opinion leaders and corporate executives. The magasine features outstanding corporations, in-depth analysis of events and issues, perspectives from corporate and government leaders, discussions of management models and strategies, executive profiles and curated articles from business journals.
Brought to you by Scope e-Knowledge Center, a trusted global partner for digital content transformation solutions - Abstracting & Indexing (A&I), Knowledge Modeling (Taxonomies, Thesauri and Ontologies), and Metadata Enrichment & Entity Extraction.
