By Stephen Jackson, Director, Content and Communications, TechSoup
This story is also published in Spanish. Click here to read the translated version.
Google’s Data Commons presents a unique opportunity for civil society organizations to leverage publicly available data to inform their work, measure their progress, and contribute their own data to present a comprehensive picture of their communities and inform decision makers.
Recently, TechSoup hosted two virtual briefings to showcase the potential of Data Commons.
On November 7, 2023, civil society organizations shared their experience in exploring data and sharing insights regarding economic and social growth in Colombia, the Development Landscape in Nigeria, and Hunger and Gender in Mexico. You can watch the whole virtual briefing below.
Why This Matters
Data is critical to understanding and addressing key local and global challenges. Finding and organizing the necessary data is difficult. Google’s Data Commons consists of three main elements:
- Google’s Public Data Commons, which aggregates data from over 200 sources. This data has been normalized by Google engineers so that it can be queried via AI, allowing for faster exploration of the available datasets.
- A framework for publishing data that includes a set of schemas based on Schema.org and a set of APIs. Use of these schemas and APIs allows data to be joined across multiple instances of Data Commons.
- A suite of tools that allow people to access and publish data from the site. They also allow people to set up their own instance of Data Commons.
With funding from Google.org and in collaboration with the Data Commons team, TechSoup is working to ensure that civil society organizations can access and use the data in Google’s Public Data Commons, publish data using the framework, and use the associated suite of tools to work with the data. Much of this work is visible in TechSoup’s Data Commons instance.
Data Stories Presented from Nigeria, Colombia, and Mexico
Nigeria Network of NGOs (Nigeria), found that Data Commons provides the ability to assemble evidence of development, advocate for change with critical stakeholders, and engage in diplomacy. Executive Director Oyebisi Babatunde Oluseyi and his team used Data Commons to investigate Nigeria’s progress in relation to its Sustainable Development Goals (SDGs) commitments.
“The beauty of this platform is that you know, for the shadow voluntary national reports that we write as civil society organizations, we can now evidence data from civil society, evidence data from private sector, evidence data from the UN system and also from other organizations, that are full of data that say ‘what exactly is happening with education, what is happening with health, what is happening with population, and what is happening with our sustainability,’” said Oluseyi. “And, What future does this tell us?”
Because the data had already been pulled from a variety of sources, NNNGO was able to better spend its time asking questions of the data and using the knowledge of the local context to assemble a topic page that provided additional insights. View NNNGOs’ topic page.
MAKAIA (Colombia) used Data Commons to access previously hard-to-use data in order to gain valuable insights into social problems in its region. Senior Coordinator Ingrid Espitia demonstrated how Data Commons normalized relevant data in order to help MAKAIA draw on available sources to create data-driven stories that were comprehensible to everyone. She said that sharing data with grassroots organizations also helps them to see how their work connects to progress being made for economic growth overall, helping them to see their contributions to civil society in a wider context.
“Data Commons actually helped us to understand the information that was already available and in some different sources,” said Espitia. “And it was very, very good for us to start … asking ourselves how we can tell a story that can be comprehensive for everyone.”
The normalization of datasets in Google’s Public Data Commons also enabled MAKAIA to compare variables that aren’t typically weighed against each other. For example, Espitia and her team learned that increased gross domestic product (GDP) was associated with a decrease in the homicide rate. Previously, this comparison would have required first finding the different datasets, normalizing them, and revealing them as a comparable timeline view. In this case, Data Commons performed these tasks so that the team at MAKAIA was able to access these insights without the need for a data scientist. View MAKAIA’s topic page.
Cemefi (Mexico), used data from Google’s Public Data Commons and other sources to build a visually rich story connecting hunger and gender in Mexico. Research Director Romina Farías and Data and Research Analyst Julio Casas said that, while they had much qualitative evidence highlighting a correlation between a decrease in hunger with a decrease in violence, there was no data to back it up.
“In this story we really wanted to make more visible the work that organizations are doing,” said Farías. “Because based on their experience, they have designed integral solutions in their models of attention that allow them to not only attack one problem, but also to a set of conditions that led to more visible effects on food and security.”
Data Commons made it possible for Cemefi to examine data from various sources to demonstrate a direct relationship between domestic violence and hunger. It was able to use this framework to develop and publish a visually rich data story revealing its findings. Cemefi used outside datasets and community-sourced data to further validate these findings. They added the community-sourced data collected during this project to missing datasets, becoming contributors to Data Commons. View Cemefi’s visual story on hunger and gender in Mexico.
TechSoup and Cemefi partnered with Plotree Info Design to produce this story.
Data Commons Presents Opportunities for CSOs
When CSOs gain the opportunity to meaningfully access data, they gain the opportunity to interrogate it. This means validating it with local communities, understanding how or why it may be differentiated, and learning which sources to trust.
Civil society can be an authoritative source of data. CSOs can be important contributors to datasets because of their strong connection with local communities that, in some cases, may have been omitted from government data during periods of civil unrest. But beyond that, these strong bonds with local communities can be leveraged to help fill in data gaps of all kinds. As Espitia pointed out, there are entire regions in certain countries on which governments have, generally speaking, little data.
Data Commons offers a suite of tools to help CSOs use data in their own stories, as we saw with Cemefi. This, in coordination with the normalization of data provided by Data Commons, can produce a network effect in which more civil society data is produced as the number of CSOs telling these data stories increases.
- Ingrid Espitia, MAKAIA, Senior Coordinator
- Oyebisi Babatunde Oluseyi, Nigeria Network of NGOs, Executive Director
- Julio Casas, Centro Mexicano Para La Filantropía, Data and Research Analyst
- Romina Farías, Centro Mexicano Para La Filantropía, Research Director
Interested? Connect with us and others who care about public data, and share relevant projects you’re aware of in your region. Reach out to us at DataCommons@techsoup.org.
Want to support this work more broadly? Consider donating to TechSoup.