Who Controls the Data, Controls the Future:Why the Global South must rethink access, equity, and digital sovereignty.

Last week, I discussed that every time we click “accept” on a digital service, there’s an invisible value exchange happening. But when that same dynamic plays out at a national level, where entire populations are mined for data without equitable return, it’s no longer just a tech issue. It becomes a question of sovereignty.

Data Colonialism is a modern form of resource extraction where data takes the place of land, labor, and raw materials. In the book Data Grab by Nick Couldry and Ulises Mejias, the authors argue that the Global South must nationalize data, treating it as a national asset, just like oil or minerals.

That idea felt immediately familiar.

A Precedence from the Oil & Gas Sector

A few years ago, I was working with an oil and gas company on seismic survey data stored in SEG-Y files. These surveys are given to exploration companies as part of licensing agreements. We built a tool called SEG-Y Cutter that partitions the files to ensure companies only access the parts they’ve paid for. If subsurface data about rocks can be protected and licensed, why not above-surface data about people, communities, and ecosystems?

Technologies like remote sensing, precision agriculture, and digital forestry are driving this shift. On the surface, they promise efficiency and sustainability. But in practice, they often funnel vast volumes of high-resolution environmental and behavioral data to large tech firms, bypassing the people who generate the data in the first place.

A small farmer in the Global South doesn’t stand a chance in this setup. They become a data point in someone else’s predictive model. Their land becomes a source of insights for external agritech platforms. They’re nudged toward platform dependence, without ever benefiting from the intelligence generated.

As this article pointed out in "Why the Global South Should Nationalise Its Data", this isn’t just about privacy or consent. It’s about value capture and control. Data is being quietly extracted, privatized, and commercialized at a global scale.

We’re witnessing the rise of digital capitalism, where profit extraction is no longer bound to factories or oil fields. It now happens wherever data flows. Precision agriculture is one of its sharpest tools, not just for growing crops, but also for accumulating data and monetizing insights.

As my colleague Winston C. argues in the CDO Magazine , public data must be treated like public infrastructure. The real value of data emerges when it is accessible, governed, and invested in as a national resource, not just uploaded into the cloud for someone else to analyze and monetize. His idea around revenue sharing between the government and the industry sounds very practical. He proposes the following simple data flow:

• Public datasets are made freely accessible to all users, including commercial entities.
• If the data is used in a product or service that generates revenue, the company shares a fixed percentage (e.g., 40%) of revenue attributed to the government data’s contribution.
• Attribution will be based on technical metrics, rather than subjective judgments.

Closing Thoughts

So what does this mean for countries in the Global South? It means asking harder questions:

• Who is collecting data from our land, our people, our public services?
• What are the terms of access and usage?
• Can we build local innovation capacity on top of our own data, instead of being reduced to raw input providers?

Because in the end, who controls the data will shape the future of agriculture, infrastructure, finance, even national policy. And if that control lies outside the borders, the Global South risks repeating an all-too-familiar story: rich in resources, but excluded from the value chain. Data has a supply chain, just like with all other natural resources, to deliver the most value, we need to move up the value chain.

For far too long, the Global South has been providing the raw materials but has little control over the final product, thereby losing out on the premium. As I have discussed in a previous blog post on different types of data products, you increase the value of data products by evolving and making them readily consumable. Global South shouldn't just be delivering raw wheat grains; they should also get a share of the pie (Pizza in this analogy) by monetizing the final data product.

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