New perspectives for the Annelida collection (National Museum/UFRJ) database: using data visualization to analyze and manage biological collections - Camila Simões Martins de Aguiar Messias; Carlos Cesar de Oliveira Fonseca; Monique Cristina dos Santos; Asla M. Sá; Joana Zanol (Ocean and Coastal Research)
Collection management faces many challenges in keeping stored items preserved and the information associated with them accurate and organized. It is essential for the expansion and use of this biodiversity repository that the database is unambiguous and that errors are quickly identified and corrected. This work aims to show the use of interactive visual representations (IVRs) of the collection’s metadata as tools to inspect the data and help solve these challenges. To do this, we used the Annelida collection database from the National Museum (MN) of the Federal University of Rio de Janeiro (UFRJ). Interactive graphs of the metadata within this database (catalog date, taxonomic identification and determiners, sampling, depth, geographic localization, and collector data) were created with the Altair library in the Python 3 language. Data analyses using these graphs made it possible to identify anomalous patterns in the data and fill in missing records. They also provided an understanding of the spatial and bathymetric distribution of the specimens deposited over time, and the growth rate of the collection in each family, thus projecting future growth and solutions for the physical organization of vials. Graphs are an ally in the management of collections with digital entry forms and aim to facilitate the availability of metadata associated with cataloged specimens. Likewise, IVRs can even be used to give credit to the researchers involved in building biological collections. Thus, visualization tools are efficient in recognizing global patterns present in databases and solving biological collection management tasks.