Revisit the use of "dataset"

[danielballan]

We use "dataset" to group all the NMC data, but elsewhere we use it to group different batches of data (iss, iss-raw). It seems like we need mechanisms for grouping data by its {source, origin, contributor, batch?} and other for grouping data that we are interested in analyzing together (NMC).

[danielballan]

Decision (discussion with @jmaruland and @danielballan):

• Stick to using dataset to mean "batch of data we were given to ingest", as it was originally used for heald and newville and aimm_core and so on.
• Introduce the key projects, with the value being a list that may contain "nmc" for example.

At some point, take the nodes that currently have dataset="nmc" and edit their dataset (probably directly in a mongo shell at this point) to refer to a batch and add {"projects": ["nmc"]} to everything that relates to NMC.

[danielballan]

We also want to capture measurement type, like hard XAS or soft XAS or a simulated version of those....