While it may take a little work to learn, understand, or format data using the BMDE, there are good reasons to do so. Using a standard schema for all data in NatureCounts makes the data interoperable, allowing data from various sources, or data collected with varying protocols, to be easily compared and examined using the same workflows and analyses. 

Photo by Kris Cu

A consistent schema also ensures the data retain their meaning long after they are collected. For a dataset collected 50 years ago, for example, there may be nobody today who remembers or understands the way those data were formatted. If there are fields in the dataset that can’t be understood, the meaning of the data is lost. By formatting the data using the BMDE, we can continue to understand and interpret the data long after a project is over or the original collectors are gone.

Though it may not seem so at first, using the BMDE helps to make life easier for data users too. Once a data user is familiarized with the schema, they can quickly understand and work with any of the diverse datasets available through NatureCounts. In this way, a user learns one schema up front, saving them the time and hassle of learning a different schema for each project as they use the data.

To explore the data available in NatureCounts, visit the data exploration tools on the NatureCounts website.

Next section: BMDE Versions & Extensions