WK 45 - The BIEN Database: Harnessing the Power of Botanical Big Data for Biodiversity and Global Change Science

Session Description: This workshop will provide an introduction to accessing the Botanical Information and Ecology Network (BIEN; https://bien.nceas.ucsb.edu/bien/ ) database via the BIEN R package. The BIEN database contains over 200 million georeferenced occurrence records and trait, community, and distribution information for over 300,000 land plant species. These data have been used in publications spanning disciplines as diverse as macroecology, conservation biology, paleoclimatology and phylogenetic systematics. In particular, they have been used extensively for modeling current and future plant species distributions. This workshop will provide potential users of BIEN data with a broad understanding of the database content and structure and best practices for accessing the data using the BIEN R package. In particular, we will review essential metadata fields of data provenance, and quality and how to use them to ensure that the data selected are appropriate for a specific application. We will also explore the significant BIEN data quality validations and standardizations and how to access these tools as stand-alone services for your research. Using the R BIEN package, we will work through practical examples of data selection, preparation, and attribution for applications such as species distribution modeling and spatial analysis of species co-occurrence.

Workshop Structure

Introduction to the BIEN database (30 minutes):
This introductory lecture will briefly introduce the BIEN database structure, contents, and workflow.

Introduction to the BIEN R package (15 minutes):
In this interactive session, the instructors will provide an overview of package structure and functions while participants are guided through installation and documentation.

Getting data from BIEN (30 minutes):
In this interactive session, participants will download data for various example use cases. These use cases will highlight how to download different types of data (e.g., plot vs. occurrence), how to use metadata to select the most appropriate data for a given question (e.g., including vs. excluding non-native observation), and different methods for selecting records (e.g., taxonomically vs. spatially).

Going further (15 minutes):
This final interactive session deals with what happens after data are downloaded, including how to automatically generate proper attributions, where to find more information, and how to submit issues and feature requests via Github.