Open Data Editor user testing: feedback from the ACIJ team

The Open Data Editor (ODE) is the new Open Knowledge Foundation’s app that makes it easier for people with little to no technical skills to work with data. Since January, it’s been developed thanks to the kind support of the Patrick J. McGovern Foundation and has become a central product for putting our The Tech We Want vision into practice.

After the ODE pre-release last October, our team has been collaborating with data practitioners to gather feedback from potential tool users. To do this, we divided the process into two parts:

Individual and group testing sessionsto systematise quick insights on possible problems and potential improvements
Two pilots with organisations that work with data but with different expertise: StoryData (Barcelona, Spain) and Asociación Civil por la Igualdad y la Justicia – ACIJ (Buenos Aires, Argentina).

We wanted to learn how a tool like ODE integrates into everyday data workflows, what are the possible challenges when using it intensively, and know hands-on recommendations to unleash its full potential.

Based on real users’ feedback and insights, our team has already made some improvements to the app for its stable release. You can check more here. We are also systematising recommendations and suggested changes for next year.

About ACIJ

In this blog, you can read the feedback from ACIJ – Asociación Civil por la Igualdad y la Justicia, an Argentinian non-partisan, non-profit organisation founded in 2002. Their vision is a just and inclusive society, free from poverty and discrimination, where all individuals are guaranteed equal treatment, full access to their rights, and the genuine opportunity to participate in and influence decision-making on public matters within democratic and transparent institutions. Their mission is to contribute to the strengthening of democracy, promote respect for the rule of law, and defend the rights of vulnerable groups.

Why ACIJ?

ACIJ handles data from various sources, serving multiple purposes. This non-profit works with public databases, often in spreadsheet format, provided by the government, such as budget allocations, as well as datasets obtained through public information requests, like the distribution of students with disabilities in regular and special schools. The organisation also produces its own data, such as judicial employee statistics and mapping of informal neighborhoods in Buenos Aires. In this sense, ACIJ diverse work with data was key to seeing how ODE performs in different contexts.

Here’s their structured feedback:

StoryData team during the testing phase

Introduction

Testing the Open Data Editor (ODE) provided us with valuable insights into data management. Designed to streamline the detection and correction of errors in tables, the app generally lives up to its promise, though a few adjustments could enhance its accessibility and ease of use.

At Asociación Civil por la Igualdad y la Justicia we tested ODE with people from different teams across our organisation. This collaborative approach allowed us to examine ODE’s features from various angles, identifying areas where it could be made even more adaptable and user-friendly. Each participant brought unique insights that enriched our evaluation, helping us consider how the tool could serve diverse needs across our organisation and within the third sector.

Installation

Upon installation, the process was straightforward as we set up ODE across multiple Windows 11 systems. The guide was clear and anticipated issues like Windows security prompts, which was helpful. Still, adding a direct download link to the user guide could save time and streamline the process for users who are eager to start working with their data immediately.

Uploading files

Once the app was installed, the initial file upload was easy and intuitive, though we quickly noted that larger files would benefit from a progress bar. For substantial datasets, a visual indicator would reassure users that the app is actively processing rather than leaving them to wonder if the system has stalled. This would add a level of polish to the user experience, especially for files that may take longer to load.

We tested a variety of file types, primarily Excel, CSV, and PDF files, but found some limitations. While single-sheet Excel files displayed seamlessly, multi-sheet files were limited to only the first sheet. Additionally, comma-separated TXT files, even with a clear structure, didn’t load as expected. Expanding support for these file types would make ODE a more versatile tool, accommodating diverse data inputs that many organizations rely on.

Navigating and managing uploaded files required a bit of learning, as locating stored files on our devices wasn’t immediately obvious. Although there was an option to access each file’s location, a dedicated “View File Location” button at the top of the interface would make it easier for users to manage their data with confidence.

Exploration

Exploring data in ODE was generally intuitive, with features like column sorting providing utility. However, data exploration could be further enhanced by addressing pagination issues and improving metadata recognition. In some cases, the app misidentified data types, particularly with dates, geographic information, and numeric values. Improved accuracy in metadata recognition would enhance ODE’s reliability for structured data analysis. [Editor’s note: In Excel files, ODE loads the date column as a string because the date is not in ISO8601 format. For more context, check this discussion.]

Errors report panel

ODE’s error-handling system was clear and easy to navigate, with color-coded highlights that made it simple to identify problem areas. A minor adjustment to error visibility, such as allowing descriptions to be seen without extra clicks, would further streamline the troubleshooting process. Additionally, providing a way to jump directly to a cell with an error would be particularly useful for large datasets, saving users time and reducing the need to scroll through rows and columns to find specific issues.

Editing data in ODE was effective, though a few enhancements could make the experience smoother. For instance, enabling bulk editing for recurring errors and allowing for basic copy-pasting would make correcting repetitive data entry errors much easier. Folder uploads should also retain their structure in the sidebar to facilitate navigating complex datasets and maintain an organised workspace.

Conclusion

ODE has immense potential, and a few adjustments would elevate it even further. Minor improvements – such as a progress bar for uploads, expanded file support, enhanced error navigation, and better metadata accuracy – could make a significant difference. As ODE evolves, it has the potential to become an invaluable tool for data accessibility, supporting organisations in the third sector and beyond to work with open data more effectively and efficiently.