Yep. Money is strangely spent. Incentives and historical attitudes of the field regarding money are hard to change.
$500k for a new microscope, no problem! It's a fancy, four channel live microscope. So it takes four 1Mb images each frame, and you're running a 10min long experiment taking an image 5 times per second. So that's like 12Gb per imageset. And you take like 10/15 replicates per experiment under 3-5 different conditions. That data for that experiment which under-girds a 6-7 figure grant is now stored on a $100 3TB USB disk from Best Buy. Oh, and trying to process that 12Gb image over USB2.0 using MatLab on a student's personal macbook air is horribly inefficient - but there is no other option for the student really.
The students collecting the data and storing it on their local HD or laptop hard drive have no place to archive their data even if they wanted to. There are no repositories capable of generically storing that kind of huge data that needs to be frequently accessed at the price the students/labs are willing to pay (nothing).
And this speaks nothing about the code every student reinvents in MatLab to do basic scientific analysis. Or worse, does not reinvent and instead reuses 20-year old code written by some long-forgotten student who wanted to try their hand at a 'new' programming language like IDL.
The 'students' and postdocs are paid nearly minimum wage to do the high-tech biomedical research. There are no computer-scientists to be seen because they would be fools to give up making 5-8x money across the street at Twitter.
On the other hand, the scientists know their work really well, and it will take a truly integrated team to solve these issues. A computer scientist can't just come over for a day and write up an app to help out. The code will have to make scientific assumptions and must be custom for many/most projects. But it's very hard to build a capable team when the market salary for certain kinds of team members is multiples of another on the same team.
$500k for a new microscope, no problem! It's a fancy, four channel live microscope. So it takes four 1Mb images each frame, and you're running a 10min long experiment taking an image 5 times per second. So that's like 12Gb per imageset. And you take like 10/15 replicates per experiment under 3-5 different conditions. That data for that experiment which under-girds a 6-7 figure grant is now stored on a $100 3TB USB disk from Best Buy. Oh, and trying to process that 12Gb image over USB2.0 using MatLab on a student's personal macbook air is horribly inefficient - but there is no other option for the student really.
The students collecting the data and storing it on their local HD or laptop hard drive have no place to archive their data even if they wanted to. There are no repositories capable of generically storing that kind of huge data that needs to be frequently accessed at the price the students/labs are willing to pay (nothing).
And this speaks nothing about the code every student reinvents in MatLab to do basic scientific analysis. Or worse, does not reinvent and instead reuses 20-year old code written by some long-forgotten student who wanted to try their hand at a 'new' programming language like IDL.
The 'students' and postdocs are paid nearly minimum wage to do the high-tech biomedical research. There are no computer-scientists to be seen because they would be fools to give up making 5-8x money across the street at Twitter.
On the other hand, the scientists know their work really well, and it will take a truly integrated team to solve these issues. A computer scientist can't just come over for a day and write up an app to help out. The code will have to make scientific assumptions and must be custom for many/most projects. But it's very hard to build a capable team when the market salary for certain kinds of team members is multiples of another on the same team.