The importance of digitized biocollections as a source of trait data and a new VertNet resource

Abstract

For vast areas of the globe and large parts of the tree of life, data needed to inform trait diversity is incomplete. Such trait data, when fully assembled, however, form the link between the evolutionary history of organisms, their assembly into communities, and the nature and functioning of ecosystems. Recent efforts to close data gaps have focused on collating trait-by-species databases, which only provide species-level, aggregated value ranges for traits of interest and often lack the direct observations on which those ranges are based. Perhaps under-appreciated is that digitized biocollection records collectively contain a vast trove of trait data measured directly from individuals, but this content remains hidden and highly heterogeneous, impeding discoverability and use. We developed and deployed a suite of openly accessible software tools in order to collate a full set of trait descriptions and extract two key traits, body length and mass, from >18 million specimen records in VertNet, a global biodiversity data publisher and aggregator. We tested success rate of these tools against hand-checked validation data sets and characterized quality and quantity. A post-processing toolkit was developed to standardize and harmonize data sets, and to integrate this improved content into VertNet for broadest reuse. The result of this work was to add more than 1.5 million harmonized measurements on vertebrate body mass and length directly to specimen records. Rates of false positives and negatives for extracted data were extremely low. We also created new tools for filtering, querying, and assembling this research-ready vertebrate trait content for view and download. Our work has yielded a novel database and platform for harmonized trait content that will grow as tools introduced here become part of publication workflows. We close by noting how this effort extends to new communities already developing similar digitized content.Database URL: http://portal.vertnet.org/search?advanced=1

The history and impact of digitization and digital data mobilization on biodiversity research

“…the Darwin Core Standard [48]) [96][97][98]. The critical need for enhancing data quality has led to procedures, research methods and best practices for improving and confirming accuracy and fitness [97,99], including the combining of GBIF and GenBank data to identify potential identification anomalies in mycology [100], address pressing data quality challenges in entomology [96,101], mining and analysing palaeobiology data [102], discovering research uses for vertebrate trait data [103], reviewing and critiquing the efficacy and potential bias in species distribution models using natural history museum specimen data [52], combining El Niñ o-Southern Oscillation and 100 years of museum specimen data for the prediction of cicada emergence in Western North America [81] and the use of images to detect new ant host species for a common parasite [104]. Issues with data completeness have been documented in several studies (e.g.…”

A global catalog of primary reptile type specimens

“…Several projects around the world have started to digitize and unite museum collection data into more comprehensive digital catalogues of specimens (not just types). In the US, the National Science Foundation (NSF) has supported efforts such as VertNet (Guralnick et al 2016) and iDigBio (https://www. idigbio.org) for many years.…”

Digitization and the future of natural history collections

“…The aggregation of traits from 286 both the initial collecting event and new annotations will stimulate a wealth of questions 287 and generate a better understanding of global biodiversity through the development of 288 standardized trait vocabularies (Kissling et al 2018). For example, recently developed 289 data-processing tools for the data aggregator VertNet standardized more than 1.5 million 290 measurements for vertebrates using digital data from collections (Guralnick et al 2016). 291…”