Define basic data classes / structures that specreduce will operate on

We should outline the data structures that specreduce procedures will operate on, e.g. images, slits, traces, apertures, identify / wavelength calibration structures. And we should look at other spectro reduction packages (eg PypeIt, DRAGONS) to see if we can make the structures compatible or at least translatable if possible. @eteq and I worked on a document suggesting a set of structures during the April 2020 sprint, which is attached, in text form.

[Spectroscopic data reduction data structures and procedure architecture.txt](https://github.com/astropy/specreduce/files/4463532/Spectroscopic.data.reduction.data.structures.and.procedure.architecture.txt)

Start by reading the attached “Spectroscopic data reduction data structures and procedure architecture” document, then compare its proposed structures with PypeIt and DRAGONS. Done means the project has an agreed outline for images, slits, traces, apertures, and identify/wavelength-calibration structures, with compatibility or translation considered.

Written by the indexing model from the issue text.