I found this topic both intriguing and believable, in the sense that it's not the fact that software applications exist and are being used but the output of those applications and what it ultimately means for the present and future of usage and how we interact with them.
I remember well the days before the Internet, when I was working (barely) as a musician and my whole computer life resided on three floppy disks. That's not an exaggeration. I had three disks; one for WordPerfect and writing, one with Lotus 123 and my band's financial data, and one with Dbase III+ with my band's database/mailing list. Those three disks were indeed precious but literally, everything that mattered to us, including the actual software programs to run them, resided on these disks. This was back in 1990. Less than a year later I would be working in a company where I would be using network-based systems, interacting with USENET newsgroups, and other entities where I was generating a lot more data than my original three floppy disk example could contain. Nowadays, those three disks couldn't even hold the equivalent of a single photo I would take today at our standard resolution.
The Data that we produce today is staggering. Trying to make sense of it is and to have actionable processes come out of that data is a challenge. Some companies make this easier than others. Some details are easier to track than others. Some data points are simple to keep track of, others are much more difficult simply because the volume and types of data being collected are disparate and hard to correlate/quantify.
Data that gets produced by applications can come from many sources and unless we can set parameters around it, we will struggle to make sense of it. Additionally, in some cases, the applications we use may make getting that data harder than it needs to be or should be. Let's take a simple example from a popular application today, TikTok. While I can see which videos I posted in the last week are doing compared to others, I can't see longer trends beyond 60 days. What are my top ten all-time most viewed videos? I have no clue short of scanning my output and getting the view counts for all of the videos and then ranking them. It seems this would/could be a valuable metric but they don't make it easy for me to figure that out. Granted, TikTok is perhaps a trivial example but I'm showing here that there is a ton of data that would be interesting to me and helpful to know about but I do not have a clear path as to how to get to that information or make it useful for me.
The point of scientific experiments is to be able to collect data and analyze it. Many apps allow us to create a variety of interactions but what are those interactions for? What is our output of those interactions? How can we leverage them? These questions matter from each user all the way up to the largest organizations. In short, before we can have data be useful and informative, we have to be able to access the data in the first place (and prevent access to those who should not have it). More to the point, data has to be reliable, repeatable, and usable in the capacity that we are able to make sense of it and put actions in motion based on the data we have received.