Laboratory automation

Computers have been used for automating laboratory experiments since before there were computers!  In fact, at the University of Illinois, while cleaning out an old laboratory, I found a old “black paper tape” system (a long spool of black paper with little holes punched into it) used for automating a laboratory, which I cleaned up an donated to a birthday party held in honor of the HAL computer:

I first started working in this area in the late 1980’s. Since then, it isn’t clear to me that anything has really changed.  The challenges back then were:

  • How do you collect and store massive amounts of data?
  • How do you ensure your networks and data collection are faster than your experiments?
  • How do you organize and post-process this data?

As far as I can tell, these are still the challenges today — only the letters have changed: in 1988 we struggled with K (kilobytes per second) and today they struggle with G (gigabytes per second) or even T (terabytes per second).

I’ll add some interesting stories of laboratory automation as time permits.

The Use of MindManager as a Scientific Data Management Tool

There is an interesting topic that many people have overlooked or never seen.  There are excellent tools for dealing with highly structured data (HSD), such as relational databases like Oracle or MySQL.  And there are excellent tools for dealing with completely unstructured data (CUD), such as Microsoft Powerpoint, or even your computer’s file system (where you store unrelated data together in folders).

But generally, data that is essential for scientific research falls into the semi-structured data category (SSD): perhaps collections of structured data measured with different instruments at different times, bundled together with analyses and calculations and speculations and back-of-the-envelope calculations, etc.  There are some software packages in use for managing this data (see here), particularly in cases that are more structured than unstructured.

But one of the most powerful, practical, and low-cost tools for managing this type of data is often overlooked: MindManager. In what follows I’ll give a very simple example of how MindManager can help an engineer or scientist add some organization to what otherwise might be clutter.

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