Idea: use ontology for easier selection process?

[Brilator]

The selection options for

Where will you submit your data as endpoints?

2. What kind of data will you handle:
3. Are there any standards that are relevant for you?

are currently (a) somewhat arbitrary and (b) inconsistently leveled. E.g. RNAseq, other NGS (genomics), metabolomics, proteomics, targeted assays, (phenotypic, genetics) are ~ assay types, whereas models, code, excel, cloned DNA (?), image are rather data / file type.

I think for most data types these topics actually go well together. So, I would suggest an iterative selection process starting from user perspective, e.g.

Assay type
└ Data type
  ├ (suggested) repository
  └ relevant metadata standard 

Assay type	Data type	(suggested) repository	relevant metadata standard(s)
mRNA-Seq	(sequences stored as) .fastq	GEO	MIAME, MINSEQE
Phenotyping	(weight, height stored as) .txt, .csv	PGP	MIAPPE

...

[Brilator]

Next step could then be to actually offer actions based on those decisions:

• Build (example) ARCs with suitable SWATE templates (https://github.com/nfdi4plants/Swate/issues/188, issue not really directly link, but similar direction)

[xiaoranzhou]

This could a long term plan for sure.