[No Code] Discover new datasets
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- Python
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Description
We need people browsing the web to discover interesting datasets than could be added to the moabb.
You can comment on this issue.
What kind of datasets
We are interested in any datasets of time neural timeseries (EEG, MEG, ECOG, and fNIRS) with a minimum of 5 subjects, where we can apply machine learning algorithms and available online. It does not need to be a BCI dataset, but it must contains different condition/task, labelled and tagged.
How do I search for a new dataset ?
Many of the datasets of the BNCI index have not been reported. you can start here.
Researcher are making more and more datasets available. some database exists and might contains interesting things :
Finally, google is your friend
How much time does it takes ?
Entering a new dataset should took you 2 minutes.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the dataset requirements in this issue and search the BNCI index, GigaDb, Dataverse, or Zenodo. Verify that a candidate has at least five subjects, time neural timeseries, labelled task or condition data, and online availability; the work is done when a qualifying dataset is identified and its details are added to moabb.
Written by the indexing model from the issue text.
Assessment
- Domain
- data, machine-learning
- Issue type
- Feature
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Activity status
- Quiet
- Clarity
- Mostly clear
- Newbie friendliness
- 67/100