Latest News from the Lab Non-Textual Materials

Individual assistance with researching and publishing scientific films in the TIB AV-Portal


Over 30,000 videos are now available on the TIB AV-Portal


German-language forum for exchange for practitioners: agile working in libraries


In the TIB-Blog we introduce the most important milestones and features of the AV-Portal that have been realised since September 2018


From scholarly communication to data treasures, digital preservation of species and personalised medicine to Open Access


The TIB AV-Portal offers thousands of scientific films, which can be easily viewed and reused thanks to free licensing


Part 3 of the Open Access Talk series deals with the various ways of sharing educational resources on 24 September 2020 (in German)


How do researchers currently see scholarly communication? That is what the TIB wanted to know in a survey – now the first results are available


3 days, more than 100 contributions from over 200 active persons make up a 70-hour programme for 1,200 participants – a first positive conclusion


TIB present with webinars and digital dialogue


Most of the videos are now available in the TIB AV-Portal: long-term archived, provided with licenses for reuse and a DOI


TIB's AV-Portal successfully accredited by the Europeana Aggregator Forum


OER-Portal Niedersachsen starts beta test at www.oernds.de


Lower Saxony as partner state of the largest foreign cultural festival in Estonia


The current issue of the TIB-News informs about Digital Object Identifier, ten years of DataCite and the TIB activities in the field of research data


21st International Conference on Grey Literature: Experts discuss grey literature in Hannover


Project partners discuss milestones and tasks at kick-off meeting


An interview with Prof. em. Dr. Georg Rüppell from Braunschweig


The 21st International Conference on Grey Literature (GL21) will take place on 22 and 23 October 2019 in Hannover


Best Paper Award for the paper "Understanding, Categorizing and Predicting Semantic Image-Text Relations"


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