Using Open Data Editor (ODE) has been incredibly beneficial in my data work. It helped me identify the necessary tasks to align with FAIR principles and implement frictionless standards for consistent data quality. As a tool, ODE made navigating through metadata much easier and significantly accelerated the process of extracting tabular data directly from other sources via URLs. This efficiency greatly reduced the time needed for ingesting the data. It also improved our shared understanding of best practices regarding open data.
The ODE pilot highlighted the significance of open-source software development and the benefits of co-creating open-source software with the community of open data developers, publishers, and users.
After everyone on my team that were involved in the pilot completed the Quality and Consistent Data with the Open Data Editor course, our meetings became much more cohesive as we all started to speak the same data language, and that’s FAIR.
To make ODE even better, I would love to see a deeper integration with AI tools, allowing ODE users to utilize more agnostic AI agents and non-proprietary LLMs. Incorporating the Model Context Protocol (MCP) would enable AI agents to access external tools and data sources more effectively. I believe that Open Data Editor can become a comprehensive solution for open data publishers. So I’m eagerly anticipating the resolution of CKAN instances so that we can start using ODE for publishing tabular data directly on the CKAN platform.
Collaborating with the OKFN team during this 3-month pilot was an incredible journey of discovery. We didn’t just analyze data errors, validate assumptions; we exchanged experiences. The coaching process was centered around the mentioned course, but also included bi-weekly cohort meetings and additional sessions as needed. This course not only served as a user guide for the Open Data Editor but also covered FAIR data principles, frictionless standards, and other open data-related topics.
I particularly valued the cohort meetings, where we received updates on app development, new functionalities, UX/UI improvements, shared our experiences, and received guidance for resolving issues. I’m excited to see some of our recommendations integrated into ODE and will continue contributing to the development and promotion of the Open Data Editor in the future.
Read more
Open Data Editor in Action: Streamlining data governance and unlocking the potential value of urban data in Croatia
Bioinformatics Hub of Kenya initiative (BHKi) was able to find errors in over-complex spreadsheets and use ODE’s metadata panel to standardise schemas for future surveys.
About the Open Data Editor
The Open Data Editor (ODE) is Open Knowledge’s new open source desktop application for nonprofits, data journalists, activists, and public servants, aiming at helping them detect errors in their datasets. It’s a free, open-source tool designed for people working with tabular data (Excel, Google Sheets, CSV) who don’t know how to code or don’t have the programming skills to automatise the data exploration process.
Simple, lightweight, privacy-friendly, and built for real-world challenges like offline work and low-resource settings, ODE is part of Open Knowledge’s initiative The Tech We Want — our ambitious effort to reimagine how technology is built and used.
And there’s more! ODE comes with a free online course that can help you improve the quality of your datasets, therefore making your life/work easier.
↪ Take the course: Learn how to use ODE
All of Open Knowledge’s work with the Open Data Editor is made possible thanks to a charitable grant from the Patrick J. McGovern Foundation. Learn more about its funding programmes here.
