UC Santa Barbara Scientists Launch New Ocean Data Tool

A new software tool, `oceandatr`, developed by researchers including scientists at UC Santa Barbara, is set to significantly simplify how scientists access and organize critical ocean data. This innovation aims to free up researchers to focus on answering complex questions about marine environments, rather than spending extensive time on data preparation.

Historically, scientists studying the ocean have faced the challenge of gathering vast amounts of information—such as seafloor depth, the location of underwater mountains, or sea surface temperatures—from disparate sources. This often requires considerable time and complex computer coding to consolidate data into a usable format. The `oceandatr` package was created to streamline this process.

Developed in R, a widely used programming language for data analysis, `oceandatr` allows users to access and organize a broad spectrum of global ocean datasets with a single command. The software then prepares this information for analysis and mapping. The development team described the new package in a paper published in *Ecology and Evolution*.

Jason Flower, a project scientist at UC Santa Barbara’s Environmental Markets Lab (emLab) and lead author, highlighted the tool’s primary benefit. He stated that it helps anyone seeking geospatial ocean data to obtain the information they need, in the desired format, quickly and easily. Co-author Echelle Burns, also a project scientist at emLab, noted that the team built the tool for marine scientists who repeatedly use similar data-pulling and organizing workflows.

Flower and his colleagues developed `oceandatr` partly through their work with the Waitt Institute, focusing on marine spatial planning in small island nations like Vanuatu and Fiji. Planning the future of ocean spaces necessitates comprehensive data, including seafloor maps, temperature readings, and details on human activities such as fishing. Before `oceandatr`, researchers frequently had to collect this data from multiple sources and write custom code to combine these diverse datasets. The new package simplifies this by transforming commonly used programming scripts into ready-made functions.

The R package organizes code specifically for accessing frequently used ocean datasets, enabling researchers to prepare data for mapping and analysis efficiently. Housed in GitHub, the software is freely available to any researcher globally. The package can retrieve various spatial ocean datasets, offering information on seafloor depth, seamount locations, and sea surface temperature, among others.

In their published paper, the researchers illustrate two practical applications of `oceandatr`. One example shows how ocean data can guide the planning of marine protected areas. Another demonstrates its use in modeling and mapping where fishing activity is likely to occur. These examples represent only a fraction of the tool's potential uses, with Flower indicating its applicability in "any marine science project that requires spatial data."

A particularly valuable feature of `oceandatr` is its ability to standardize data from different origins. Scientists often need to combine datasets that may be stored using varying spatial formats or scales. For instance, the bathymetry data accessible through `oceandatr` has a resolution of 15 arc seconds, while fishing effort data might be much finer, at 0.01 or 0.1 degrees. `oceandatr` harmonizes these differences behind the scenes, allowing users to focus on analytical tasks.

While the tool accesses global datasets, it also proves useful for researchers concentrating on smaller areas, such as individual islands or coastal regions. Burns affirmed that users can supply their own datasets, and `oceandatr` will ensure they are saved at the appropriate spatial scale.

The research team plans ongoing expansion and improvement of `oceandatr`. Future enhancements could include the addition of daily sea surface temperature data, complementing the average sea surface temperature information already available. Flower is also working to boost the software's speed and efficiency, ensuring it remains accessible to researchers using older or slower computing systems. Burns described `oceandatr` as a "living package" that will continuously evolve and be refined in the coming years.

The developers hope that by automating and simplifying the repetitive aspects of data discovery and preparation, `oceandatr` will ultimately empower scientists to dedicate more time and resources to the fundamental research questions that propel marine science forward.