Area A: sample preparation data

Keywords:

Electronic Lab Notebook (ELN) / Application definition / Schemes / Data structures

Full documentation (in preparation) at: https://fairmat-nfdi.github.io/AreaA-Documentation/

Base Classes Hierarchy:

These base section have got an a priori inheritance structure. The user can further decide how to put together this bricks by means of referencing.

About this repo:

This is a collection of blueprint schemes that include several kinds of experiment.

The schemes here implemented are compliant to the NOMAD data structure: the hierarchy is composed by Sections, Subsections and Quantities (data fields).

The users can follow the info in this repo to build their own schema for their experiment 👍.

Some further explanation on NOMAD Metainfo and Archive here

Each folder contains four categories of files, the user can try to drag and drop all of them in the upload page in Nomad, they will be automatically parsed to create an "Entry" containing the experimental data in a structured fashion:

schema file: it defines the structure that will host your data. The schema file has .schema.archive.yaml extension.

Sections, subsections and quantities are the elements that compose the hierarchical structure of data.

An important part in the schema is the annotations section, enabling the available ELN features such as:
- editability of quantities
- automatic plot of quantities
- inheritance from specific Nomad base classes (ReferenceEditQuantity, AuthorEditQuantity)
- drag and drop features for file upload (RawFileAdaptor)
- more (overview: True, repeats: True, hide: ['..', '..'], template)
data file: based on the schema file, it contains the actual data or links to metadata files, logfiles, dataset from instrument that will be parsed into your experiment Entry. The data file has .data.archive.yaml extension.

It lacks the "infrastructural" lines such as the sections and subsections labels or the annotations, types and units of quantities, pesent in the schema file. It is used to avoid manual filling of data into ELN when they are repeated among multiple experiments. It also points to data files, metadata files, log files etc. where the actual number are stored.
data set: depending on the outcomes of the experiment, the user will have one or more files where the monitored parameters and metadata are stored. The data set files have .txt., .dat, .csv or .xlsx extension.
base classes: sections with fixed structure collected in base_classes folder, the user will find a copy of this base_classes file that must be included in the upload.

In the subfolders, a dedicated README documents the file set for each use case.

The Structured Use Cases: