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Is it possible for an artist to respond to the current state of scientific research and manifest it artistically? This is one of the questions that I have been repeatedly asked while working on my project Beneath the Sea. I will give my answer to this question straightaway: “Yes, I believe this is possible!”. It all starts with finding and building a community dedicated to working towards a shared purpose – for instance, the purpose of meaningfully contributing towards coral reef rehabilitation. 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
Global environmental changes pose a serious threat to natural ecosystems. Responding to these threats with effective conservation efforts depends critically on the accurate historical records that are digitised and published by natural history collections. Despite increasing demand for digital access to physical specimens, the number of taxonomic experts working on this process has been declining for several decades. New technologies have the potential for natural history collections to compensate for this shortage of taxonomic expertise and can accelerate the publication of accurate biodiversity data. As a cooperation of ETH Library Lab and the Entomological Collection of ETH Zurich, our Automated Species Identification project aims to develop a practical solution for the classification of specimens based on artificial intelligence and computer vision. Read on
In the second part of a series of four articles, I will give an overview of the digital fabrication and additive manufacturing work environment. Sharing the most important steps in my learning process may help others to acquire similar knowledge and put it into practice more easily. I also describe how my research on 3D clay printing led me to create an accessible model collection for the Material-Archiv at ZHdK. Read on
It is projected that every day humans produce approximately 2.5 quintillion bytes of data each day. With this insane amount of new data, surely some of it must be redundant, right? For data science, analytics, and machine learning, this increase in the amount of data available leads to previously unthinkable new avenues for research. But while more and more data is being harvested for a variety of reasons, could better curation of the data we have already collected lead to better outcomes for research? Read on
Since March 2019, the ETH Library Lab Innovator Fellowship has given me the opportunity to advance my research on an already existing project called Beneath the Sea, a new Form of Reef. Throughout four articles, we will discover how I am evolving in an interdisciplinary structure, where knowledge flows from different sources. Read on
In my last post, I suggested that the principle of crowdsourced intelligence might help establish a beneficial synergy between learners and programmers by providing documentation for open source code. Now that the project has reached an advanced state, the question comes up how to identify the best out of those user-generated solutions in order to systematically improve the output. Again, I'm drawing on existing principles to solve this optimisation problem. Read on
Strategic Foresight
Predicting the future – along with building a perpetual motion machine, the quadrature of the circle, or finding a cup of good coffee in the university cafeteria – is one of the unsolved mysteries that have been bothering scientists over centuries. While most have given up on the latter three, a method called strategic foresight offers a serious scientific approach to the challenge of predicting the future, or at least limiting the possibilities to a set of plausible scenarios that organizations can prepare for. Read on
A Beneficial Synergy
Although an automated test to distinguish humans from computers and a language-learning software might not have much in common at first glance, ReCAPTCHA's and Duolingo's business models share an underlying synergetic principle. Inspired by existing cases of interactive knowledge transfer like these, we suggest a beneficial collaboration between code sharing and learning platforms. Read on
Identifying new scientific datasets can be a time consuming, but necessary, step to perform complex machine learning tasks. Why not apply machine learning methods to automate the indexing of datasets itself? Read on

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