awesome-data-catalogs VS opendatadiscovery-specification

Check out this GitHub awesome list of Data Catalogs.

Maybe what you want i some specification from which you can build something? In that way, perhaps this can help you https://github.com/opendatadiscovery/awesome-data-catalogs. Airflow uses OpenLineage as a way to send their metadata, and Marquez collects them to show them in their UI (https://openlineage.io/docs/guides/airflow), so I suppose you would want to do something similar? But maybe in that GitHub you can find other specifications that can help you better.

In order to gain a understanding of the tables and their contents in our company, I have implemented one of the existing [data discovery platforms](https://github.com/opendatadiscovery/awesome-data-catalogs) (in my case [Amundsen](https://www.amundsen.io/))). Unfortunately, Amundsen can only display the tables it has access to.

I got nice data catalog summary in case anyone would be interested - https://github.com/opendatadiscovery/awesome-data-catalogs. It is probably biased since author is also author of one of the data catalogs, but still can be quite useful :)

Hi, I would like to know is there any opensource data catalog systems that targets machine learning applications (datasets (unstructral, e.g., text, image, and video) and models) as the citizen?

I have read the awesome-data-catalogs ([1]) list but found none of them is treating ML as 1st cizten and the support for datasets and models are not specific enough.

[1]: https://github.com/opendatadiscovery/awesome-data-catalogs

Thank you!

Actually everything is working on a push basis in ODD now. ODD Platform implements ODD Specification (https://github.com/opendatadiscovery/opendatadiscovery-speci...) and all agents, custom scripts and integrations, Airflow/Spark listeners, etc are pushing metadata to specific ODD Platform's endpoint (https://github.com/opendatadiscovery/opendatadiscovery-speci...). ODD Collectors (agents) are pushing metadata on a configurable schedule.

ODD Specification is a standard for collecting and gathering such metadata, ETL included. We gather metadata for lineage on an entity level now, but we plan to expand this to the column-level lineage at the end 2022 — start 2023. Specification allows us to make the system open and it's really easy to write your own integration by taking a look in what format metadata needs to be injected in the Platform.

ODD Platform has its own OpenAPI specification (https://github.com/opendatadiscovery/odd-platform/tree/main/...) so that the already indexed and layered metadata could be extracted via platform's API.

Also, thank you for sharing links with us! I'm thrilled to take a look how BMW solved a problem of lineage gathering from Spark, that's something we are improving in our product right now.