I think I know a lot about interdisciplinary collaborations, so I’ve been planning to write down some notes for a long time. Tongue in cheek, but also serious. Take time to get to know each other Yes, it will take time. It might feel like you understand each other from the moment you met; that […]
Category: Skills
That ole Illustrator magic
After making a figure with your favorite software—matplotlib, R, Matlab, gnuplot, etc.—there are usually many details that could need a touch-up. In collaborations, somehow that’s usually my job. Maybe partly because I’ve been using Illustrator since I-forgot-when, so I acquired some speed. I also love graphic design and am teaching scientific visualization (two areas with […]
The network scientist’s survival kit
Throughout the scientific disciplines, core values, methodologies, and worldviews vary to a frustrating degree. Network scientists are interdisciplinary. Through years of catching up with our disciplinary colleagues, we have learned to understand other disciplines better than many scientists of those disciplines understand us. Such a fundamental thing as who a scientific result should benefit, and […]
When storytelling enters, science leaves. Or?
A lighthearted post about whether or not it is right to market your scientific output—a topic I am neutral about because there are great arguments on both sides, canceling each other. So, my inner dialogue could go like: Hey! Did you see César Hidalgo tweeting that storytelling is an American thing? Isn’t it anthropology 101 […]
Common mistakes in network code
This is not really a blog post, but rather a checklist of more or less painful mistakes in networks-science programs by me, or my students or teachers. (As a side note, computer scientists tend to be better a this, but are by no means immune to it.) This list is incomplete. I plan to fill […]
The importance of being earnest about the importance of nodes
One of the problems network science sets out to solve is to find important nodes. Of course, what is important depends on the context, but an applied scientist coming to network science for an answer probably has a clear idea of what it means in her study system. There is no shortage of methods in […]
Petter Holme 