Schlagwort: FAIR Data Principles

Microsoft Academic – a major data source dries up

Microsoft has announced that the Microsoft Academic Graph will be discontinued at the end of 2021. What does this mean? Why is this important for researchers and research institutions? The Microsoft Academic Graph is the database behind Microsoft Academic, one of the most comprehensive academic search engines. However, Microsoft does not only use the data for this in-house search service. In contrast to its well-known competitor Google Scholar, it has decided to make the data available to third parties. And this has been used many times in recent years. One reason for this is certainly the size of Microsoft Academic. In a recent study by the Centre for Science and Technology Studies (CWTS), various bibliographic data sources were examined, and the following figure speaks for itself – irregardless of some limitations put forward by the authors regarding comparability. Microsoft Academic is thus a huge data source that is also available via an interface and as a dump. In addition, it is prepared and documented for bibliometric analyses. The relevance of this data for science is readily apparent. The two publications describing this service have been cited (according to Microsoft Academic) more than 500 and 1700 times respectively. In the announcement of the discontinuation of the service, Microsoft mentions some alternatives. If you take a closer look at them, you will see that some of them are at least partly based on Microsoft Academic, e.g. Semantic Scholar or The Lens. The existing data will presumably continue to be used, also thanks

Rückblick auf unseren “FAIR Data and Software”-Workshop

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.