We invite you to the webinars prepared by Clarivate Analytics, which will take place in May 2026, and their main topic is Metadata quality. Webinars are free, but advance registration is required.
Web of Science Basics – Your tool for discovering and analyzing the most important publications
May 22, 2026, 11:00-12:00 | Sign up
Modern science is evolving rapidly, and the growing number of publications and interdisciplinary research make it difficult to find reliable and relevant information. Researchers must navigate the data overload, assess the credibility of sources, and analyze trends and research impact. During this webinar, we will introduce the Web of Science Core Collection and demonstrate how to effectively search for literature, analyze citations, and utilize bibliometric data in research and evaluation. We will also discuss key features such as account personalization, search strategies, results management, and available support resources. The webinar is intended for researchers, doctoral students, librarians, and anyone supporting the analysis and evaluation of scientific output who want to more efficiently navigate the world of scientific literature and make decisions based on reliable data. Presenter: Viktor Curasev, Customer Success Consultant.
The Importance of Structured Data in Science: From Search to Trustworthy Analysis
May 26, 2026, 10:00-11:00 AM | Sign up
As the volume and complexity of scientific research worldwide grows, the way data is organized and classified becomes crucial for reliable analyses and sound decisions. Poorly organized or inconsistently classified data can lead to incomplete results, erroneous conclusions, and misleading comparisons—even when the analyses themselves are performed correctly. Drawing on the findings of the Institute for Scientific Information (ISI) report "Research Categorization and the Value of Structured Data," this webinar explains the importance of well-prepared data, consistent classifications, and rich metadata. We will present specific examples of how poor data quality can undermine citation analysis, benchmarking, collaboration evaluation, and research results. We will also explain how appropriate approaches—such as domain normalization and time-based analysis—can help mitigate these issues. Presenter: Marcin Kapczynski, Strategic Customer Success Consultant.
