It turns out that I am a member of a new Institute the Johns Hopkins Institute for Data Intensive Science and Engineering (IDIES). This is alternately pronounced ideas or eye-dee-ess. I prefer the latter and will do everything in my power (admittedly limited) to influence the organization in this direction. As of now, the institute has exactly zero Web presence. Compare this with some of the other JHU institutes, e.g. inbt or jhuisi with popups of some of our favorite people. I am sure that this will be remedied as time passes. I thought that we would start this process in as small a way as possible…..with my blog.
The good news is that IDIES has got the right mix of people and projects and has developed organically from existing projects. These include:
This group amounts to my research friends (i.e. my brffs).
The mission of the Institute is to develop novel HPC architectures and the scientific data systems that support data intensive science, i.e. scientific discovery through data mining, feature extraction, correlation, and other forms of knowledge discovery through the search of petascale data sets. That may actually be my CS take on the mission, the scientists themselves may be more application focused. In either case, interdisciplinary teams work together to create scientific data systems according to Jim Gray's data laws.
I'll write another entry on the laws themselves, maybe. But, Alex Szalay is promoting the “Jim Gray” process of making big data systems that work and codifying this as a best practice. It will be awesome when we speak of Gray's laws with the same breeziness with which we talk about Moore's or Amdahl's.
Discussion