Konrad Hinsen's Blog

Posts tagged science

Some comments on AlphaFold

Many people are asking for my opinion on the recent impressive success of AlphaFold at CASP14, perhaps incorrectly assuming that I am an expert on protein folding. I have actually never done any research in that field, but it’s close enough to my research interests that I have closely followed the progress that has been made over the years. Rather than reply to everyone individually, here is a public version of my comments. They are based on the limited information on AlphaFold that is available today. I may come back to this post later and expand it.

The landscapes of digital scientific knowledge

Over the last years, an interesting metaphor for information and knowledge curation is beginning to take root. It compares knowledge to a landscape in which it identifies in particular two key elements: streams and gardens. The first use of this metaphor that I am aware of is this essay by Mike Caulfield, which I strongly recommend you to read first. In the following, I will apply this metaphor specifically to scientific knowledge and its possible evolution in the digital era.

Industrialization of scientific software: a case study

A coffee break conversion at a scientific conference last week provided an excellent illustration for the industrialization of scientific research that I wrote about in a recent blog post. It has provoked some discussion on Twitter that deserves being recorded and commented on a more permanent medium. Which is here.

The industrialization of scientific research

Over the last few years, I have spent a lot of time thinking, speaking, and discussing about the reproducibility crisis in scientific research. An obvious but hard to answer question is: Why has reproducibility become such a major problem, in so many disciplines? And why now? In this post, I will make an attempt at formulating an hypothesis: the underlying cause for the reproducibility crisis is the ongoing industrialization of scientific research.

Data science in ancient Greece

Data science is usually considered a very recent invention, made possible by electronic computing and communication technologies. Some consider it the fourth paradigm of science, suggesting that it came after three other paradigms, though the whole idea of distinct paradigms remains controversial. What I want to point out in this post is that the principles of data science are much older than most of today’s practitioners imagine. Let me introduce you to Apollonius, Hipparchus, and Ptolemy, who applied these principles about 2000 years ago.