The OpenDX data model is the heart and soul of the system. In fact, the user interface we will be learning in this workshop is only one of a universe of possible user interfaces (yet unrealized) that can be used to manipulate the DX data model. We will spend a considerable time studying the data model in this workshop, since a good understanding of it unlocks the real power of OpenDX, and a lack of understanding will leave you staring at a blank programming canvas wondering what to do next.

The data model is all about structure: how do we organize and describe data and its relationship to sampling positions (spatial and temporal reference frames) as well as to other data sets or data fields (different parameters measured in the same or similar spatial or temporal frames).

Even if you decide not to use OpenDX, exposure to the concepts of data structuring may help you organize your own data in the future. Since many scientists invent their own ad hoc structuring schemes, the hardest part of using OpenDX is often describing such schemes in a way that OpenDX can interpret them. We have had remarkable success in using the flexibility of OpenDX to read in data sets without resorting to changing the actual data. However, every now and then, someone invents such a contorted scheme that even OpenDX can't deal with it. We'll spend some time discussing some of the most common ways to get data into OpenDX so you explore your own (hopefully uncontorted) data sets.