Das Blog der TIB – Leibniz-Informationszentrum Technik und Naturwissenschaften und Universitätsbibliothek
As part of the National Research Data Infrastructure for Chemistry NFDI4Chem has developed the Search Service for an overarching search across various chemistry and chemistry-related repositories.
➔
The monthly NFDI InfraTalk opened up an interesting question regarding the potential of Wikidata to be used as an application for science and research. In this 2-part post series, we expand on the differences between Wikidata and Wikibase instances, and their potential applications in academic contexts.
➔
Protoype allows visualisation, customization and configuration of indicators – feedback welcome
➔
An interview with Britta Dreyer on ten years of DataCite: a success story around the Digital Object Identifier (DOI) The foundation of the association DataCite celebrated it’s 10th anniversary in the beginning of December 2019, a reason to look back and peak into the future. In the interview Britta Dreyer,
➔
In an interview, Professor Dr. (Univ. Simón Bolívar) Maria-Esther Vidal discusses the use of big data technologies in the health sector
➔
End of January, TIB hosted three librarians from Kyoto who were on a journey in Europe to learn about university libraries‘ efforts to implement Open Science and research data management at their universities.
➔
Mitte Juli versammelten sich knapp 25 junge Wissenschaftler*innen und 4 externe Lehrende an der TIB, um gemeinsam die Anwendung der FAIR-Prinzipien auf Datensätze und selbst-geschriebene, wissenschaftliche Software zu üben. Das experimentelle Format kombinierte theoretischen Unterricht über die FAIR-Prinzipien und ihre Bedeutung für die Wissenschaftler, mit praktischen Live-Programmier- und Datenanalyse-Übungen nach dem Modell der Software, Data & Library Carpentries.
➔
In September 2017, we were in Beijing and held a seminar for employees of the Chinese National Science and Technology Library (NSTL) over several days.
➔
Scientific data should be findable, accessible, interoperable and reusable according to the FAIR Data Principles. Our detailed checklist provides recommendations for action for scientists and operators of information infrastructures.
➔
