Fideslang: a taxonomy for privacy engineering
Some data is more private than others.
For instance, users typically expect a digital application to treat their social security numbers differently than it treats their zip codes. Most jurisdictions even legally enforce this now.
Since both users and regulators regard certain kinds of data as more private than others, developers have a responsibility to handle the data they collect and process accordingly.
The privacy engineering team at Ethyca created Fideslang to help software developers meet this fundamental need.
What is Fideslang?
Fideslang (pronounced “Fidēs” + “lang” as in “language”) is an open-source, standardized privacy taxonomy developed by our team at Ethyca.
We created a privacy taxonomy for developers to describe the privacy-related data types, behaviors, and usages involved in developing a software application.
As a standardized privacy taxonomy, Fideslang simplifies compliance with global privacy regulations for developers. Using Fideslang, developers know what pieces of data their application processes and for what purpose.
Fideslang can also be adapted to serve the privacy needs of any application, and its open-source and extensible bones have allowed it to grow to accommodate evolving privacy regulations across the world.
Using Fideslang as a foundation for privacy engineering
We often see privacy patched on top of existing software systems—a deficient approach that our CEO Cillian Kieran calls “privacy as an afterthought.” In contrast, one of the key goals of privacy engineering is to embed privacy principles deep into applications.
At Ethyca, we’ve taken this approach while developing our suite of privacy engineering features on top of Fideslang’s rock-solid foundation of privacy concepts.
With the core of Fideslang as a common framework, we have expanded our privacy engineering toolset organically to help solve a wide range of digital privacy use cases.
From Fides’ data mapping support, augmented by Fides Compass, to its automated privacy request processing engine, Fideslang is at the basis of all we build here at Ethyca.
Whether you use Fideslang directly, or take advantage of the tooling we’ve built with it, know that you are working with a strong foundation of privacy principles to meet your privacy engineering goals.
Get started with Fideslang today
To learn more about Fideslang, visit our documentation on GitHub. Or, schedule some time with one of our privacy engineers to see how the taxonomy can help solve your privacy challenges.