With a URL to an OPeNDAP server, you can browse datasets, perform subset operations, and open your selected data directly in a tool you already use: R, Matlab, Xarray, IDL, Panoply, and more. (Wondering about a specific tool? Here’s a list of OPeNDAP-compatible client software.)
PyDAP, a pure python implementation of the DAP protocol (and a backend engine of Xarray), has a recent collection of examples demonstrating basic remote access and subset to OPeNDAP URLs.
An interdisciplinary graduate student enrolled in a Climate and Society program explores the CMIP6 datasets that are available through a remote OPeNDAP server. She works to reproduce key figures in the newest IPCC report to better understand the scientific workflow when combining model output and observations.
An undergraduate major in biological oceanography works to identify geographically important regions of high primary productivity during springtime in the North Atlantic ocean. Primary productivity can be estimated from Chlorophyll A concentration [mg/m^3] measured by satellite imagery. They access freely available level 3 data products from the Suomi-NPP satellite hosted by OPeNDAP server.
As part of their senior year thesis, an undergraduate student compares sea surface height anomalies available from the ECCO (“Estimating the Circulation and Climate of the Ocean”) dataset and satellite Altimetry data from AVISO, to identify regions of low bias, i.e. regions where the ECCO data captures broad patterns of variability persistent in observations. Both datasets can be accessed and inspected remotely through diverse remote OPeNDAP servers simply with knowledge of each dataset’s URL.
A journalist writes an article about past occurrences of droughts across different cities in the continental United States, and potential correlations with air quality, pollution and rain precipitation changes. For that, he accesses gridded Palmer drought severity index data spanning since 1980, and all the relevant environmental data freely available from distributed OPeNDAP servers.
An oceanographer works to quantify and identify the dominant mechanisms driving high-frequency variability of cross-shelf transport across the Icelandic shelf break, as described in a peer-reviewed study that she recently read. She works to perform a high resolution regional simulation using realistic bathymetry and atmospheric forcing for the same time period as that of the study. She will use climatological data, like seawater temperature and salinity, to validate that her simulation reproduces the large-scale realistic features. Both climatology and observational data from the study can be found on distributed OPeNDAP servers.
A field campaign has successfully deployed surface instrumentation to sample the upper ocean along and across frontal regions, which are dynamically active regions with strong surface gradients in the temperature and/or salinity fields. This field campaign belongs to a multi-year project that resamples the same region and time of the year. The lead scientist uploads the data to an existing OPeNDAP server with all the necessary metadata and coordinate information so that anybody can reproduce their results.
OPeNDAP is well-suited to complex scientific phenomena that present multiple data types (beyond geographic maps alone) and have multidimensional, time-varying coordinates.
End users can retrieve data from within aggregate datasets with format translations and enriched metadata.
For this reason, OPeNDAP has been widely adopted in fields like meteorology, oceanography, geophysics, ecology, and other Earth and environmental sciences. At the same time, the protocol’s flexibility would work with virtually any domain dependent upon large, complex, and variable datasets.
Identify and access the URLs of OPeNDAP servers hosting the datasets you’re interested in. These could be provided by institutions like NASA, NOAA, or university research centers.
Use OPeNDAP client tools or web interfaces to explore the structure of the datasets you need, understand the variables available, and determine the specific subset of data you require.
Use your preferred tool to download your dataset in your preferred analysis environment (MATLAB, R, Jupyter notebook, etc.).
If you don’t yet have an OPeNDAP-compatible client software of choice, here’s a full list of client software with download links. Or start with our Data Access Tutorials.