Open Data Editor in Action: Democratising housing data analysis in Argentina

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.

Presentation of the VivienDATA tool to the press in Buenos Aires in November 2024 (source)

Organisation: Civil Association for Equality and Justice (ACIJ)
Location: Buenos Aires, Argentina 🇦🇷
Knowledge Area: Human rights
Type of Data: Housing

ACIJ is a leading organisation in the defence of social rights in Argentina. Through its Data Unit and the Right to the City programme, ACIJ develops tools such as VivienDATA, an interactive dashboard that monitors housing conditions, particularly for vulnerable groups such as tenants.

The Challenge

Problem:

In order to analyse inequalities in access to housing, the team needed to process data from the Permanent Household Survey (‘Encuesta Permanente de Hogares’, EPH). This presented multiple challenges.

Massive volume: 18 years of quarterly data (approximately 80 CSV files), each with over 200 columns.
Inconsistencies: Variables that changed names between years; missing values coded as ‘N’; lack of clear metadata.
Technical complexity: Cross-referencing variables such as tenure type (rental/ownership), income, gender, quality of materials, and geographical location.

Impact:

Without the right tools:

Preliminary analysis took weeks to identify problems in the data.
Undetected errors could distort key findings on housing inequalities.
This limited the ability to respond quickly to changes in public housing policies.

The EPH spreadsheets are organised by year or by periods of several years in which changes in methodology occurred. They contain coded values, as in the previous example, which makes them very difficult to navigate and consolidate.

INDEC, the public agency responsible for data collection, offers Redatam (above) as a tool for viewing and cross-referencing data, but it is not as easy to read as the VivienDATA platform.

The Solution

The ACIJ team used ODE at two critical stages.

Initial exploration:
- Clear visualisation of large CSV files (with over 200 columns) and unlimited horizontal scrolling.
- Automatic detection of missing values (e.g. ‘N’ in numeric fields) and inconsistency patterns between years.
Post-processing:
- Metadata documentation for the final datasets in VivienDATA.
- Generation of summary tables ready for interactive visualisation.

In this huge spreadsheet, ODE identified 1,998 inconsistencies and errors in the dataset.

The ACIJ team could upload multiple CSV files to the ODE at once and switch between them via the menu on the left.

Here, ODE is used to identify and document the various types of metadata applied to each column.

The Results

Time saving: The time taken for the data cleaning and validation phase is reduced from weeks to hours.
Key findings:
- An increase in the percentage of tenants in different urban areas of the country in recent years.
- Differences in housing quality between tenants and owners.
Amplified impact:
- The successful launch of VivienDATA, with coverage in the national media.
- The tool is used by journalists and legislators to inform debates on housing policies.

Home page of the VivienDATAtool, whose data has been verified by Open Data Editor.

Quote

Camilo D’Aloisio, Data Analyst at ACIJ

“ODE provided us with a clear way to visualise CSV files, which I could not find in any other tool. We were able to quickly identify how variables changed between years and the relationships between columns.”

Eduardo Ferreyra, Co-Director of ACIJ

“The leap in quality that ODE enabled us to make was fundamental. In a country where access to housing is critical, the ability to analyse this data quickly strengthens our impact.”

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.

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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.