Wow, apparently I’ve already done 15 interviews and one of the most intimidating things is that I only have a couple transcribed so far. Transcription is the worst thing EVER. I can’t use cloud services (ethics, remember) and Siri offline on my mac is….. bad. Just bad.

Some thoughts and notes on what’s happened so far.

  1. I think there are indeed clusters of some sort in how people create their models. This is based on my personal observation rather than data analysis.
    • There’s the data-centric cluster, which sees data and biology as inherently intertwined - a gene is simply a data object which has attributes such as names, identifiers, etc. - and then there are links between data objects, with a clearly defined relationship, perhaps a “is-a” or “has-a” relationship.
    • There’s also a Biology vs Data cluster - these people sit down, form a nice blob of biology terms, and a second blob of
  2. For most people, mental models of biological data are squishy. Asking questions will often result in “well, I could have done it this way!” - and some people will then adjust the cards, but not everyone will.
  3. Many people want to draw lines between items. I provided paper so people could sketch relationships if they wished, but no one actually did for the first few. Eventually, someone did. This person, hilariously, claims little computer programming / computer science experience but created the most clearly defined schema I’ve seen so far. After seeing them put paper behind the cards, I realised that if I’d had better foresight, I could have prepared a flipchart and allowed people to write underneath. After fifteen interviews, I definitely do not wish to change things around this much, but it would have made transcription a heck of a lot easier.
  4. While many people added a few cards, mostly people didn’t feel the need to add much. The model we started with seems to be reasonably complete.
  5. I’m glad I decided to alternate the order of tasks A and B - one participant worried that the ordering had affected their performance, and I think it possibly does as well.
  6. Some other possible codes: some people made clusters of related things, some people made hierarchic piles, and some people made trees of data.
  7. Some card values were too generic to be clear to most people - e.g. “name”, “accession”. Others were potentially applicable to many different places - e.g. “length”, “molecular weight”.