We wish you a very happy August This month, we decided to share the most relevant and helpful OpenRefine July 2022 releases, tutorials, videos, and academic publications with you. Read on to discover them!
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We wish you a very happy July! This month, we decided to share the most relevant and helpful OpenRefine June 2022 releases, tutorials, videos, and academic publications with you. Read on to discover them!
We wish you a happy June! This month, we decided to share the most relevant and helpful OpenRefine May 2022 releases, tutorials, videos, and academic publications with you. Read on to discover them!
Every year, I need to compile metrics regarding OpenRefine community, either for presentation or grant submission. Every year, I have to go back and check what I did and how I got those number. This year will be the last. Here are the metrics I track, and how I compile them.
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| Slide from a presentation from August 2020 |
Happy May! For this month, we decided to share the most relevant and helpful OpenRefine April 2022 releases, tutorials, videos, and academic publications with you. Read on to discover them!
Hosting OpenRefine is a long-asked feature from the community. Natively, OpenRefine is designed to run on the user's local machine. Therefore, the software does not include user management, permission, or sharing the compute resources (CPU, RAM) with other users.
Hosting OpenRefine allows access to multiple users. Use cases include
Back in 2014, at RefinePro we built a service to manage users and instances of OpenRefine hosted using AWS EC2 instances. Our platform was basically
We used htpasswd to protect the instance from being publicly available. At the time, we found a way to hide the extra logging from our users, but things remained hacky and not suitable for the long run. Therefore, we decided to stop the service in 2017.
In the last two years, we have seen an increasing number of hosted OpenRefine deployments based on Jupyter and JupyterHub (with Kubernetes). In those deployments, OpenRefine is one of the applications hosted via JupyterHub as part of a larger data science workbench. OpenRefine benefits from JupyterHub user and environments management.
As of April 2022, there are several publicly advertised JupytherHub deployments, including:
Following on the idea from Felix Lohmeier and Tony Hirch on OpenRefine wiki ; I think it would be interesting to develop an official OpenRefine package for JupyterHub. Such package will include docker configuration specific to JupyterHub, dedicated OpenRefine extensions (like the local file extension) along with best practices.
The creation and maintenance of the package will provide the community with an official way to host OpenRefine. It will also offer a point of contact for potential contributors to improve the package or OpenRefine itself.
I am interested in your thoughts and potential interest in building this package.
The RefinePro team is thrilled to release under the Apache License 2.0 two new extensions for the OpenRefine ecosystem. The extensions have been funded and developed in partnership with Novartis, with the technical help of Aridhia Informatics. They are released under the FAIRplus program.
Thank you to Jiangbo Dang, Andrea Splendiani, and Rodrigo Barnes for your help.
Feel free to reach out if you have questions. You can also open issue in each respective repository