Clean dataset on terrestrial plants occuring in Brazil

We have made available two databases of the Brazilian flora. The “raw database” contains data on terrestrial plant species after excluding records with invalid or missing taxonomic and georeferenced information, records outside Brazil, or from uncertain sources (i.e., the pre-filter step of the workflow). The results of each test used to flag data quality are appended in separate fields in this database and retrieved as TRUE or FALSE, in which the former indicates correct records and the latter potentially problematic or suspect records. It is worth noting that the “raw” database contains records with names not found in the Flora do Brasil and with taxonomic, spatial, and temporal issues.<br>The “fitness-for-use” database is a filter of the “raw” database and only contains valid records that passed all data quality tests. Consequently, the result of each cleaning test is not shown. This database includes verified and standardized data on species taxonomy, geolocation, and date of collection. The databases contain data on conservation status, distribution, and establishment retrieved directly from the Brazilian Flora 2020 and accessed through the flora R package (Carvalho, 2017). Importantly, records lacking information on collecting date were not removed because they are fit-for-use for some biodiversity applications even when date information is missing.<br>We have made available two databases of the Brazilian flora. First, a “raw” database (n = 12,762,595 records) containing the results of data quality tests appended in separate fields. This database includes records of algae and fungi species, records of species with non-accepted names, and records with taxonomic, spatial, and temporal issues. Second, a “fit-for-use” or “cleaned” database, containing 4,070,313 records of 38,207 species from 432 families. This database includes data on land plants occurring in Brazil (angiosperm, gymnosperm, ferns and lycophytes, and bryophyte), except algae and fungi species and records lacking information on collecting data.