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Data Science
Algorithms, Artificial Intelligence (AI), Machine Learning (ML) – when I read about these subjects in the media, it always sounds a bit like magic to me: “human resources use machine learning” or “artificial intelligence can diagnose Parkinson’s disease earlier than specialists”. For me, these statements suggest something superhuman, incomprehensible – magic. However, it is not magic at all. Facial recognition algorithms are not “black boxes” and we do not pull self-driving cars out of a magician’s hat. Read on
© Phillip Ströbel
In science and research, there is an increasingly strong need to create, collect, federate and process ever larger amounts of data. Alongside this rapid development due to the digitalisation of information environments in research, scientific libraries are seeking to adapt and reframe their roles. On the one hand, they strive to grow into facilitators of scientific knowledge work in all its facets. On the other hand, they look for ways to better leverage the power of scientific data for the collective good. But can libraries move fast enough to realise these roles? This blog article attempts to find answers to this question by investigating and presenting both the researchers’ and the libraries’ perspectives. Read on
One for all and all for one. In these times of COVID-19, we are experiencing the true meaning of this phrase, maybe a little more than most of us are comfortable with. The containment measures related to COVID-19 have changed our daily lives. For example, for my fellowship at the ETH Library Lab the impact has been twofold: On one hand, I can no longer work side by side with my talented colleagues at Technopark and on the other hand it has shifted my perspective on the purpose of my project. And while the phrase ‘one for all and all for one’ is traditionally attributed to Alexandre Dumas’s novel ‘The Three Musketeers’, I recently learned that it is also known as ‘the unofficial motto of Switzerland’ [1]. So, what better way to introduce my project at the ETH Library Lab? Read on

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