We want to hear from you! Take our short OPeNDAP User Survey!
What Is OPeNDAP?
OPeNDAP is the commonly used name for a discipline-neutral data access protocol (DAP) that’s widely utilized both to access and to provide data over the internet.
OPeNDAP was originally developed by and designed for oceanographers, but today the protocol is applied across many diverse domains in which large, complex, distributed datasets are used.
In a nutshell, OPeNDAP allows end users to immediately access specific subsets of data in a form they can easily use—all while using their preferred data analysis applications.
“OPeNDAP” also refers to the nonprofit organization that created and supports the OPeNDAP protocol.
Photo by NASA
Client-Server Model
OPeNDAP utilizes a client/server model:
- Server software deployed by hundreds of data providers including NASA
- Client software employed for data retrieval in:
- Many data analysis applications, including all that utilize NetCDF
- Bespoke programs/notebooks/etc. in many languages including PythonOpen access protocol & software for data exchange
The OPeNDAP team supports our own modular data server called Hyrax, which was developed with funding from NSF, NASA, and NOAA and is freely available for anyone to use.
How It Works
1. OPeNDAP Server Set-Up
OPeNDAP serves as a “translator” for a wide variety of data formats and types. All that’s required is for the data provider and the end user to both have an OPeNDAP server (such as Hyrax set up); our protocol handles the rest.
And for especially complex needs, developers can build custom servers by modifying our open source code.
2. Data Inspection & Retrieval
Thanks to the DAP, the end user can inspect datasets remotely through a web URL or a number of data tools.
They can also perform subsetting operations to download only the specific pieces they want—eliminating massive file transfers and the related costs.
3. Discovery & Collaboration
OPeNDAP serves data in a format that works well with most end users’ preferred data analysis applications (e.g. R, Python, MATLAB, and other applications using NetCDF libraries).
This makes it easier for researchers, scientists, and other end users to leverage data in their work.