Dear John,
thanks for the nice words! Yes, you correctly understood the message that I am trying to convey. My usual slogan is "Lensing of '69 -- use data not models". You are right, that system biology is definitely another good example for under-constrained problems and a lot of results are highly based on models (judging from my experience working on quality control for a special peptide array assembly method).
Although I am focussing on the data-driven way of science, I think, at early stages of research in a certain field, a courageous, bold assumption/model is needed to start out with. Without some concrete claim to test, it seems hard to establish a rough idea about a phenomenon and gain enough useful observational evidence, so that the data-driven approach can be set up. Maybe, system biology still needs some time to grow into this state. Luckily, in gravitational lensing, we are on the verge of being able to shift from the model-driven approach to the data-driven approach:
For galaxy-clusters as gravitational lenses, we are expecting a multitude of multiple images (about 1000 per cluster, as estimated to be observed by the JWST) in the near future, complemented by ongoing X-ray surveys that will also deliver a lot of additional data to break degeneracies.
For galaxies as gravitational lenses, the number of multiple images per galaxy is not expected to grow so much, but, on the other hand, the multiple images we already have, already give us a lot of information about such lenses. The lens morphology of one galaxy is much simpler than the one of an entire cluster of galaxies. For these lenses, increasing the resolution of the telescopes to resolve small-scale features in the multiple images will allow us to infer small-scale properties on sub-galaxy scale on top of the knowledge we already have e.g. about masses enclosed by the giant arc images on the scale of the entire galaxy lens.
Best regards,
Jenny