Discuss whether support canonical datasets w/o dataset_infos.json and/or dummy data
About dummy data, please see e.g. this PR: https://github.com/huggingface/datasets/pull/3692/commits/62368daac0672041524a471386d5e78005cf357a
- I updated the previous dummy data: I just had to rename the file and its directory
  - the dummy data zip contains only a single file: `pubmed22n0001.xml.gz`

Then I discover it fails: https://app.circleci.com/pipelines/github/huggingface/datasets/9800/workflows/173a4433-8feb-4fc6-ab9e-59762084e3e1/jobs/60437
```
No such file or directory: '.../dummy_data/pubmed22n0002.xml.gz'
```
- it needs dummy data for all the 1114 files: 
  `_URLs = [f"ftp://ftp.ncbi.nlm.nih.gov/pubmed/baseline/pubmed22n{i:04d}.xml.gz" for i in range(1, 1115)]`
- this confirms me that it never passed the test: these dummy data files were not present before my PR
- therefore, is it really useful the data test if we just ignore it when it does not pass?

In relation with JSON metadata, I'm generating the file for `pubmed` (see above) in a GCP instance: it's running for more than 3 hours and only 9 million examples generated so far (before my PR, it had 32 million, now it has more).
I open this PR to have a public discussion about this topic and make a decision.

As previously discussed, once we have the metadata in the dataset card (README file, containing both Markdown info and YAML tags), what is the point of having also the JSON metadata (dataset_infos.json file)?

On the other hand, the dummy data is necessary for testing (in our CI suite) that the canonical dataset loads correctly. However:
- the dataset preview feature is already an indirect test that the dataset loads correctly (it also tests it is streamable though)
- we are migrating canonical datasets to the Hub
Do we really need to continue testing them in out CI?

Also note that for generating both (dataset_infos.json file and dummy data), the entire dataset needs being downloaded. This can be an issue for huge datasets (like WIT, with 400 GB of data).

Feel free to ping other people for the discussion.

CC: @lhoestq @mariosasko @thomwolf @julien-c @patrickvonplaten @anton-l @LysandreJik @yjernite @nateraw 
Discuss whether support canonical datasets w/o dataset_infos.json and/or dummy data 
 I open this PR to have a public discussion about this topic and make a decision.

As previously discussed, once we have the metadata in the dataset card (README file, containing both Markdown info and YAML tags), what is the point of having also the JSON metadata (dataset_infos.json file)?

On the other hand, the dummy data is necessary for testing (in our CI suite) that the canonical dataset loads correctly. However:
- the dataset preview feature is already an indirect test that the dataset loads correctly (it also tests it is streamable though)
- we are migrating canonical datasets to the Hub
Do we really need to continue testing them in out CI?

Also note that for generating both (dataset_infos.json file and dummy data), the entire dataset needs being downloaded. This can be an issue for huge datasets (like WIT, with 400 GB of data).

Feel free to ping other people for the discussion.

CC: @lhoestq @mariosasko @thomwolf @julien-c @patrickvonplaten @anton-l @LysandreJik @yjernite @nateraw  
 About dummy data, please see e.g. this PR: https://github.com/huggingface/datasets/pull/3692/commits/62368daac0672041524a471386d5e78005cf357a
- I updated the previous dummy data: I just had to rename the file and its directory
  - the dummy data zip contains only a single file: `pubmed22n0001.xml.gz`

Then I discover it fails: https://app.circleci.com/pipelines/github/huggingface/datasets/9800/workflows/173a4433-8feb-4fc6-ab9e-59762084e3e1/jobs/60437
```
No such file or directory: '.../dummy_data/pubmed22n0002.xml.gz'
```
- it needs dummy data for all the 1114 files: 
  `_URLs = [f"ftp://ftp.ncbi.nlm.nih.gov/pubmed/baseline/pubmed22n{i:04d}.xml.gz" for i in range(1, 1115)]`
- this confirms me that it never passed the test: these dummy data files were not present before my PR
- therefore, is it really useful the data test if we just ignore it when it does not pass?

In relation with JSON metadata, I'm generating the file for `pubmed` (see above) in a GCP instance: it's running for more than 3 hours and only 9 million examples generated so far (before my PR, it had 32 million, now it has more).