Articles published in journals either in paper or PDF format can be read and understood by researchers, but not by machines. To enhance efficiency, accessibility, and reproducibility in the scientific ecosystem, research articles must be machine-readable allowing for automated data extraction, analysis, and integration, and also for advanced computational tools like AI to uncover new insights. As part of this machine readability rich metadata is crucial, as it provides structured information about the article’s content, making it easier to search, and to filter and organize research outputs. Persistent Identifiers (PIDs) add further value by ensuring that articles and their associated data can be reliably located and cited over time. Together, machine-readability, metadata, and PIDs enhance the discoverability, accuracy, and long-term impact of scientific work, making research more accessible and useful for the global community. This joint seminar with JST and STM will bring together speakers from Japan and the international community to explain some aspects of the current use of metadata and PIDs within the scholarly record, and to give some insight into the future of machine readability.
Event Date: October 31, 2024
Event Location: Online
Event Website: https://www.stm-assoc.org/events/7th-jst-stm-seminar-machine-readability-in-scholarly-communications/
