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The Data Studios are a different way of organizing geospatial and remote sensing resources. Instead of starting with a dataset and asking people to figure out what to do with it, we start with the real-world questions and work backwards from the use case.
A little over 2 years ago, DevGlobal and NASA launched the Lifelines Initiative with a simple belief: Earth science and geospatial data should be easier to use where the stakes are highest. Lifelines is a long-term effort to build community across scientists, technologists, and humanitarians, and to turn the incredible range of available data into better decisions on the ground.
The need is not abstract. Humanitarian teams respond to crises that rarely arrive one at a time. A storm becomes a displacement event. Displacement strains water systems. Strained water systems can trigger disease. Food insecurity can rise at the same time that access routes are washed out or unsafe. The questions decision makers face are practical and urgent: Which communities are most vulnerable right now? Which facilities are likely to be cut off? Where can assistance be delivered quickly and with confidence?
And yet, even when the data exists, using it can be complicated and overwhelming.
Over the past year, we heard the same pattern from partners again and again. Many people do not know which datasets are relevant to their work. If they do, they may not know what is available, where it lives, or how to access it. If they manage to find and download it, the data often needs extra processing and technical knowhow before it can be combined with other layers. Then comes the hardest step of all: turning a pile of files into actionable insight.
This is why the Data Studios exist.
The Data Studios are a different way of organizing geospatial and remote sensing resources. Instead of starting with a dataset and asking people to figure out what to do with it, we start with the real-world questions and work backwards from the use case.
That shift matters because geospatial value is often unlocked through combinations. Satellite imagery alongside road networks. Rainfall anomalies alongside crop health. Population surfaces alongside access to health services. Humanitarian crises are systems problems, and the data needs to be usable as a system.
Just as importantly, the Data Studios do not try to become yet another place where data is hosted. Many trusted platforms already do that well. Our job is to connect the dots across them, add the missing context, and help people move from “I know this data exists” to “I can use it today.”
A Data Studio package is a purpose-built bundle of resources for a specific humanitarian use case. Think of it as a field guide that points you to the right ingredients and shows you how to work with them together.
In every package you will find a curated set of datasets and tools, pulled from the best existing sources rather than duplicated. You will also find practical instructions: where to get the data, what formats to expect, how to process it, and what common pitfalls to avoid. Finally, each package includes guidance on how the pieces fit together to answer the questions that matter for that scenario, with workflows that have already been used in practice.
We are starting with high-priority, high-impact use cases where the need for better data intersects with the likelihood that better data will change outcomes. Early priorities were shaped in part by the Beyond Borders work from Caribou Space, then sharpened through a year of listening closely to humanitarian partners. In practice, this points us toward compounding risks like flooding, conflict, displacement, food security, and access to essential services.
If you have ever tried to build a workflow from scattered links, outdated documentation, and half-working scripts, you already understand the goal. When you are responding to a crisis, you do not have time to chase five portals, decode five file formats, and stitch together a method from scratch. A Data Studio package is meant to reduce that friction.
