What is the benefit of building a circular data economy?

Over the years we’ve become accustomed to reusing, recycling, and upcycling a wide variety of different products and materials. At the same time, a greater awareness of the health and environmental impacts of practices such as fast food and fast fashion have also led calls for more sustainable ways of living. Collectively, this opens discussions about moving away from a linear economy – where products are created, used, and then discarded – to a circular economy. But how does this relate to a circular data economy?

 

What is a circular data economy?

A circular economy aims to keep resources circulating for as long as possible. We breathe new life into them in different ways before they become terminal. It’s possible to apply this same model of thinking to the  data we use and capture. And here of course, I’m thinking about drone based Earth observation data.

 

So what do you do with your data when you’re finished with it?

Are you as diligent with reusing and recycling it as you might be with paper and cardboard, bottles and cans?

 

Or – tell the truth – do you leave it sitting on hard drive in the bottom drawer or on an obsolete computer?

 

What if we thought about our data differently? What if it became a building block to create new knowledge from different perspectives?

The circular data economy concept flowchart with arrows and icons
The circular data economy concept
What if we took the ‘Marie Kondo’ approach with our data? 

We can pass it on to others to whom its reuse will bring joy through scientific discovery and application.

How does it work?

The open satellite data archives already encourage this circularity. For example, in 2008 when the United States government agreed to open the entire archive of 30 years of Landsat satellite data, they started a trend in open Earth observation. In doing so, they unlocked a multibillion-dollar industry. 

 

Fifteen years on, we have seen the European Space Agency follow suit with their Earth observation data, and many more state and federal governments around the world let loose their data shackles. As the value of Government open satellite data grows, the number of alternative remote sensing platforms (including drones) is also increasing.

 

However, the increased data acquisition options have not necessarily followed suit with open data availability. Circularity is less evident with data captured in a more distributed manner as with drones. 

What about drones in the circular data economy?

At GeoNadir, we’re passionate about putting the circular data economy into action for drone based Earth observation. We’ve proven that we can harness the democratized data capture capability of thousands of drone operators to create a findable, accessible, interoperable, and reusable (FAIR) global drone data repository (check it out here!).

 

We’ve curated more than 400,000 drone mapping images from across 51 countries. People from every single country in the world are already taking advantage of what our community is building.

 

Clearly the circular economy for Earth observation data is no longer limited to tax-payer funded satellite programs. 

Two women on a boat to capture drone mapping data
Capturing imagery is the first stage of the circular drone data economy
GeoNadir's FAIR global repository is the basis of the circular drone data economy

The benefits of the Landsat, Sentinel, and MODIS archives (to name a few) are indisputable. Similarly, we believe that the growing drone community can contribute important and relevant Earth observation data to science and society. 

 

We know that there are challenges with metadata and standardized data capture methods. But we also know that advanced computing techniques and image recognition algorithms provide new opportunities to process datasets that may have been captured in a sub-optimal manner or conditions. 

 

In this way, the sheer volume of high-fidelity data captured by drones offers us the ability to reimagine the way we process data, and the types of information we can extract from it. Having access to a wide variety of global datasets in a central FAIR repository now allows us to collectively grow our insights, while building the most detailed map of the world to save at-risk ecosystems.

Yunbenun land and sea rangers learning drone mapping on country

What are the benefits?

In developing a circular drone data economy, we build opportunities to continually add value and repurpose our data for ourselves and others to develop new insights. Here’s our top five examples where people are benefiting from our circular data economy model:

 

  1. Reduced cost to store, process, and share drone data;
  2. Access to drone data to calibrate and validate global satellite models;
  3. Testing algorithm transferability using drone data from different locations;
  4. Scaling deep learning algorithms across geographic regions; and
  5. Learning and developing data processing skills without the overhead of data capture.

Are you ready to join the circular data economy?

Over the years, my colleagues and I have amassed many hundreds of thousands of drone images around the world. But until recently, these highly valuable data have been siloed. They were unavailable for collective use, and drastically underused. By contrast, I’ve seen firsthand the global impact that central repositories and open data can make, driving collective wisdom and igniting innovation. So I created GeoNadir as a globally unique cloud platform designed to build the best map of the world, using crowd sourced drone data to save at-risk ecosystems.

 

In order to work, data must be findable, accessible, interoperable, and reusable (FAIR), and people within the open data economy must participate beyond their consumption. Are you ready to embrace a circular data economy, a FAIR mindset, and erase single-use data?

 

It’s super easy to get started with GeoNadir. Upload your first dataset today!

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Topographic map with dots displaying data points of environmental drone mapping data. Three drone mapping overlays in different environments

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