Inspired by a couple of great posts by Michael Gibson, I want to talk about what robustness means to me, as someone coming from a science background.

I started working in a “wetlab” doing benchwork cancer research when I was in high school (I was 16). I learned early on that mistakes are:

• normal
• avoidable
• necessary.

That may sound paradoxical, so I’ll explain. Some failures will always happen: the phone rings and you drop something. That can happen to anybody. But you can take safeguards to prevent disaster, like making sure all your tubes are labeled and capped tightly, so if you drop them, nothing gets lost. And some failures are informative, like when (notice I don’t say ‘if’) an experiment doesn’t work out the way you expected. Mistakes will be always educational if you designed your experiment correctly.

Thanks to a friend who wants to help more women get into tech careers, last year I attended Developer Week, where I was impressed by a talk about Neo4j.

Graph databases excited me right away, since this is a concept I’ve used for brainstorming since 3rd grade, when my teachers Mrs. Nysmith and Weaver taught us to draw webbings as a way to take notes and work through logic puzzles.

In Biochemistry, we used this kind of non-linear flowchart all the time to keep track of mechanistic models and signal transduction pathways.

So let’s say you’re thinking about attending a conference in tech, or some STEM field.

Maybe you’ll be going alone. Maybe you’ve never been to a conference before, or this conference has a reputation for having, shall we say, “a higher risk of harassment”.

Here’s a ‘game plan’ for things to keep in mind. I’m not saying anyone should ever have to do this, I’m saying this is more or less what I did when I was younger and had to go to STEM meetings, usually alone, and didn’t always feel safe.