Simple search and citation of occurrences

Hannah L. Owens

Cory Merow

Brian Maitner

Jamie M. Kass

Vijay Barve

Robert Guralnick



We have entered the age of data-intensive scientific discovery. As data sets increase in complexity and heterogeneity, we must preserve the cycle of data citation from primary data sources to aggregating databases to research products and back to primary data sources. The citation cycle keeps science transparent, but it is also key to supporting primary providers by documenting the use of their data. The Global Biodiversity Information Facility (GBIF), Botanical Information and Ecology Network (BIEN), and other data aggregators have made great strides in harvesting citation data from research products and linking them back to primary data providers. However, this only works if those that publish research products cite primary data sources in the first place. We developed occCite, a set of R-based tools for downloading, managing, and citing biodiversity data, to advance toward the goal of closing the data provenance cycle. These tools preserve links between occurrence data and primary providers once researchers download aggregated data, and facilitate the citation of primary data providers in research papers.

The occCite workflow follows a three-step process. First, the user inputs one or more taxonomic names (or a phylogeny). occCite then rectifies these names by checking them against one or more taxonomic databases, which can be specified by the user (see the Global Names List). The results of the taxonomic rectification are then kept in an occCiteData object in local memory. Next, occCite takes the occCiteData object and user-defined search parameters to query BIEN (through rbien) and/or GBIF(through rGBIF) for records. The results are appended to the occCiteData object, along with metadata on the search. Finally, the user can pass the occCiteData object to occCitation, which compiles citations for the primary providers, database aggregators, and R packages used to build the dataset.

Future iterations of occCite will track citation data through the data cleaning process and provide a series of visualizations on raw query results and final data sets. It will also provide data citations in a format congruent with best-practice recommendations for large biodiversity data sets. Based on these data citation tools, we will also propose a new set of standards for citing primary biodiversity data in published research articles that provides due credit to contributors and allows them to track the use of their work. Keep checking back!


If you plan to query GBIF, you will need to provide them with your user login information. We have provided a dummy login below to show you the format. You will need to provide actual account information. This is because you will actually be downloading all of the records available for the species using occ_download(), instead of getting results from occ_search(), which has a hard limit of 100,000 occurrences.

#Creating a GBIF login
GBIFLogin <- GBIFLoginManager(user = "occCiteTester",
                              email = "****",
                              pwd = "12345")