Research Data Archive (USFS)

The Research Data Archive (RDA) application, provided by the U.S. Forest Service, is a comprehensive platform designed to give researchers, students, and the general public access to high-quality, citable research data focused on forest and grassland ecosystems. This repository houses a vast collection of scientific datasets generated by researchers supported by the U.S. Forest Service, including those from experimental forests and ranges, alongside contributions from the Aldo Leopold Wilderness Research Institute and the Joint Fire Science Program.

By utilizing the RDA app, users gain the ability to delve into over 150 meticulously documented data sets that adhere to the Biological Data Profile metadata standards. These data sets are not only curated but also undergo rigorous review by both the authors and the archive staff, ensuring the highest level of accuracy and reliability. The app's robust features allow users to perform full-text searches, explore the geographical context of data collection through interactive maps, and export search results directly to Excel for further analysis or sharing via email.

One of the standout capabilities of the RDA app is its user-friendly interface, which includes an easy share action allowing users to disseminate detailed information about specific data sets via email. Additionally, users can effortlessly navigate to the web version of any dataset by clicking on the "ID" field within the data set detail view, making it convenient to access additional resources or deeper insights into the data.

For those who encounter issues or wish to provide valuable feedback, the app offers a send feedback feature accessible through the menu options. This direct line of communication enables users to contribute to the ongoing improvement of the data products, thereby enhancing the overall experience for all community members.

Should you have any inquiries or suggestions, feel free to reach out to us at fsrda@fs.fed.us. Your feedback is highly valued, as it helps us refine the metadata and improve the quality of our data offerings, ensuring that others can benefit from the enhanced data products and datasets.