This text shows a real case of how the Open Data Editor (ODE) impacted the workflow of an organisation working to serve the public good.

An extension officer collecting data from farmers during the Harvesting season at Tibung, Kumbungu district, Ghana

Organisation: Open Science Community Ghana (OSCG) **Location: **Accra, Ghana 🇬🇭 **Knowledge Area: **Open Science, Academic Research **Type of Data: **Agricultural Research Data

In the heart of Ghana’s agricultural regions, researchers and extension officers work tirelessly to collect vital data from farmers. This information is crucial for improving crop yields and combatting plant diseases, but it often arrives in the form of a tangled mix of local languages, handwritten notes and digital forms. The Open Science Community Ghana (OSCG) stepped in to help, but they too were overwhelmed by the chaotic state of this field data. Their transition from manual data management to efficient cleaning and analysis using the Open Data Editor demonstrates the tool’s effectiveness in a practical, non-technical setting.

The Challenge

The OSCG’s partners, including agriculture students from the University for Development Studies and extension officers from research institutions such as the Crops Research Institute (CRI), proved to be excellent data collectors. However, turning the data into something clean and usable was a real challenge.

Data was collected through conversations, printed questionnaires and mobile apps such as KoboToolbox, often in challenging conditions with no electricity. This resulted in deeply ‘messy’ datasets:

• Mixed Languages: Critical information such as crop names was recorded in local languages (e.g. Ban) alongside English, creating consistency issues.
• Formatting Inconsistencies: Dates and other key fields were incorrectly formatted during manual digitisation from paper forms, such as misspellings of words and the representation of scientific names of plants and animal species.
• Missing Metadata and Structure: There was zero knowledge about metadata or proper labelling of columns, resulting in jumbled, incomprehensible spreadsheets.
• Data Privacy Concerns: Some partners demanded entirely offline processing to ensure that sensitive farmer information never left their local machines, which ruled out cloud-based tools. Again, some of the researchers want to complete their research findings before anybody gets to see their work, which often compelled the OSCG’s team to work on cleaning the data offline and using a manual approach.

Prior to ODE, the OSCG resorted to an arduous combination of manual cleaning (extremely time-consuming), advanced tools such as OpenRefine (too technical for most) and prompt engineering with AI chatbots (risking data privacy and producing unreliable, occasionally multilingual outputs).

A sample questionnaire from an extension officer for farmers to assess their farming

Sample of trees species distribution per location in Ghana

The Solution

The Open Data Editor has become the central hub for transforming raw field data into information ready for analysis. The OSCG’s process is straightforward: import disparate CSV files received from partners directly into the ODE.

• Instant Data Profiling: Upon import, the ODE tool immediately highlights errors, blank cells and formatting inconsistencies. This visual feedback is invaluable for quickly identifying problems that would take hours to find manually.
• Schema Standardisation: The ODE interface enables the team to easily define and enforce a standard data structure, ensuring that every dataset adheres to a consistent format. This directly solved their core problem of harmonising the data that they receive from different sources.
• Offline-First Assurance: ODE’s ability to function entirely offline is a critical feature that meets the strict data privacy and integrity requirements of their research partners. Some of OSCG’s partners opt to keep their data confidential until they release it, so they clearly avoid online tools or AI that could leak their unpublished works. An example of errors detected by ODE in a research dataset: blank cells and wrong formats. Above, ODE flags wrongly formatted cells based on the declared data types

The Results

The Open Data Editor has accelerated research and empowered communities. Adopting the ODE has directly impacted the efficiency of the OSCG and the quality of support they can provide.

• Dramatic Time Savings: The laborious process of manual cleaning has been significantly streamlined. What was once a tiring and error-prone task has become a streamlined, efficient workflow within a single tool.
• Enhanced Data Integrity: By using ODE’s validation features, the OSCG now produces reliable, standardised datasets. This improves the basis for critical research into crop diseases and farming practices, ultimately helping farmers obtain accurate, actionable insights more quickly.
• Democratisation of Data Skills: ODE’s greatest strength is its accessibility. This lowers the barrier to entry, enabling students and extension officers to engage with data directly, regardless of their technical background.
• A Model for Ethical Data Handling: The OSCG successfully navigates data privacy concerns by offering a tool that respects the need for local, offline processing, thereby building trust with their community partners. This is a sample of the distribution of tree species per location in Ghana; the data quality was ensured by ODE

Quote

Mohammed Kamal-Deen Fuseini, Project manager

“The main problem was harmonising the data that we received from different people. You don’t need to have any technical background to use the Open Data Editor. Our researchers are shocked as to how it works. The whole agenda was for non-technical people. We are very positive that most of our students, researchers and extension officers can easily adapt the tool for their day-to-day activities because of its simple nature.”

About the Open Data Editor

The Open Data Editor (ODE) is Open Knowledge’s 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. In October 2025, ODE was recognised as a digital public good by the Digital Public Goods Alliance.

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.

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