Contribute

We provide four different ways of contributing data to the repository:

  1. A highly recommended method of data submission is to submit your data to the VizieR service and then simply let us know your data exists by adding it to our to do list, under the VizieR heading. This way, your data is not just available via our website, but also to the broader community who may not know the OSC exists. For the benefit of the community, please make a habit of submitting your data to VizieR after publishing it!

  2. Small contributions of data can be provided manually by clicking the edit link (the pencil icon) next to each entry on the main catalog page. This will take you directly to a GitHub edit page where you can add data directly in the JSON format. When you click this link, the file will most likely be blank unless someone else has manually edited that event, this is completely normal, our scripts will combine your data with all the other sources we draw from.

    When you contribute data in this way, your JSON file should conform to the format we have adopted. After saving an edit, you should submit your changes as a pull request to our “internal” GitHub repository:

    This pull request will be reviewed for syntax/correctness, if everything looks good it will be merged and the changes will appear on the page within a day; if changes are required we will comment on the request indicating what’s necessary for the request to be merged.

  3. You can also choose to upload your data to this Dropbox file request. We are not picky about format, and only have a few requirements:

    • All uploads should include a README file that describes the data, with the README containing the basic contact info of the uploader.
    • The data should include at least once reference (preferably with an associated ADS bibcode) for source attribution.
    • Spectra can be donated directly as FITS files, but most other donated data should preferably be human-readable ASCII (CSV, JSON, XML, etc., are all fine), we highly recommend using the AAS’s MRT creator to create such files. If the data is in non-human-readable format, a Python script should be included that will read the data into memory.

    Data will be added to external repositories (see the links below under option #4) when it is contributed in this way, and the turn-around time may be a bit longer than options #1 and #2 as we’ll have to write additional code to incorporate your data. But this is preferable to not collecting the data at all, we do not intend unfamiliarity with git to be a barrier to contributing!

  4. If you are planning bulk contributions to the catalog but do not want to convert your data to the JSON format, the preferred way is to submit a pull request to one of our external data repositories, and optionally editing the import script itself to parse that data. Editing the import script itself might be a preferable solution if you are in charge of a data source that updates on a regular basis. Because of the GitHub repository size limits, the import script and the external data is split into a few different repositories:

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