I would like a chance to jump into this point because this problem is a function of two things. The throughput that you can make your Tigger (Data acquisition s

I would like a chance to jump into this point because this problem is a function of two things. The throughput that you can make your Tigger (Data acquisition system) save the data and transfer it to permanent storage. This is usually invlove multiple steps and most of them happens in real-time. The other problem is the storage itself and how it would be kept (duplicated and distributed to analysts) which at the scale of operation we are doing is insanely costly. If we are to say save 20% of the generated collision data then we would fill the entire cloud storage in the world in a couple of runs . Also the vasr majority of data is background and useless so you would do a lot of work to clean that and apply your selections which we do anyway but now you are dealing with another problem. The analysts will need to handle much more data and trying new things (ideas and searches) becomes more costly which will be discouraged. So you work in a very constrained way. You improve your capabilities in computing and storage and you present a good physics case of what data (deploy trigger line which is to pick this physics signal) that the experiment is sensitive to and then lets the natural selections take place (metaphorically of course). Most of the experiments cannot because of the data acquisition problems.