Repositories for Taxonomic Data: Where We Are and What is Missing. (16th April 2020)
- Record Type:
- Journal Article
- Title:
- Repositories for Taxonomic Data: Where We Are and What is Missing. (16th April 2020)
- Main Title:
- Repositories for Taxonomic Data: Where We Are and What is Missing
- Authors:
- Miralles, Aurélien
Bruy, Teddy
Wolcott, Katherine
Scherz, Mark D
Begerow, Dominik
Beszteri, Bank
Bonkowski, Michael
Felden, Janine
Gemeinholzer, Birgit
Glaw, Frank
Glöckner, Frank Oliver
Hawlitschek, Oliver
Kostadinov, Ivaylo
Nattkemper, Tim W
Printzen, Christian
Renz, Jasmin
Rybalka, Nataliya
Stadler, Marc
Weibulat, Tanja
Wilke, Thomas
Renner, Susanne S
Vences, Miguel - Editors:
- Friedman, Matt
- Abstract:
- Abstract: Natural history collections are leading successful large-scale projects of specimen digitization (images, metadata, DNA barcodes), thereby transforming taxonomy into a big data science. Yet, little effort has been directed towards safeguarding and subsequently mobilizing the considerable amount of original data generated during the process of naming 15, 000–20, 000 species every year. From the perspective of alpha-taxonomists, we provide a review of the properties and diversity of taxonomic data, assess their volume and use, and establish criteria for optimizing data repositories. We surveyed 4113 alpha-taxonomic studies in representative journals for 2002, 2010, and 2018, and found an increasing yet comparatively limited use of molecular data in species diagnosis and description. In 2018, of the 2661 papers published in specialized taxonomic journals, molecular data were widely used in mycology (94%), regularly in vertebrates (53%), but rarely in botany (15%) and entomology (10%). Images play an important role in taxonomic research on all taxa, with photographs used in >80% and drawings in 58% of the surveyed papers. The use of omics (high-throughput) approaches or 3D documentation is still rare. Improved archiving strategies for metabarcoding consensus reads, genome and transcriptome assemblies, and chemical and metabolomic data could help to mobilize the wealth of high-throughput data for alpha-taxonomy. Because long-term—ideally perpetual—data storage is ofAbstract: Natural history collections are leading successful large-scale projects of specimen digitization (images, metadata, DNA barcodes), thereby transforming taxonomy into a big data science. Yet, little effort has been directed towards safeguarding and subsequently mobilizing the considerable amount of original data generated during the process of naming 15, 000–20, 000 species every year. From the perspective of alpha-taxonomists, we provide a review of the properties and diversity of taxonomic data, assess their volume and use, and establish criteria for optimizing data repositories. We surveyed 4113 alpha-taxonomic studies in representative journals for 2002, 2010, and 2018, and found an increasing yet comparatively limited use of molecular data in species diagnosis and description. In 2018, of the 2661 papers published in specialized taxonomic journals, molecular data were widely used in mycology (94%), regularly in vertebrates (53%), but rarely in botany (15%) and entomology (10%). Images play an important role in taxonomic research on all taxa, with photographs used in >80% and drawings in 58% of the surveyed papers. The use of omics (high-throughput) approaches or 3D documentation is still rare. Improved archiving strategies for metabarcoding consensus reads, genome and transcriptome assemblies, and chemical and metabolomic data could help to mobilize the wealth of high-throughput data for alpha-taxonomy. Because long-term—ideally perpetual—data storage is of particular importance for taxonomy, energy footprint reduction via less storage-demanding formats is a priority if their information content suffices for the purpose of taxonomic studies. Whereas taxonomic assignments are quasifacts for most biological disciplines, they remain hypotheses pertaining to evolutionary relatedness of individuals for alpha-taxonomy. For this reason, an improved reuse of taxonomic data, including machine-learning-based species identification and delimitation pipelines, requires a cyberspecimen approach—linking data via unique specimen identifiers, and thereby making them findable, accessible, interoperable, and reusable for taxonomic research. This poses both qualitative challenges to adapt the existing infrastructure of data centers to a specimen-centered concept and quantitative challenges to host and connect an estimated $ \le $ 2 million images produced per year by alpha-taxonomic studies, plus many millions of images from digitization campaigns. Of the 30, 000–40, 000 taxonomists globally, many are thought to be nonprofessionals, and capturing the data for online storage and reuse therefore requires low-complexity submission workflows and cost-free repository use. Expert taxonomists are the main stakeholders able to identify and formalize the needs of the discipline; their expertise is needed to implement the envisioned virtual collections of cyberspecimens. [Big data; cyberspecimen; new species; omics; repositories; specimen identifier; taxonomy; taxonomic data.] … (more)
- Is Part Of:
- Systematic biology. Volume 69:Number 6(2020)
- Journal:
- Systematic biology
- Issue:
- Volume 69:Number 6(2020)
- Issue Display:
- Volume 69, Issue 6 (2020)
- Year:
- 2020
- Volume:
- 69
- Issue:
- 6
- Issue Sort Value:
- 2020-0069-0006-0000
- Page Start:
- 1231
- Page End:
- 1253
- Publication Date:
- 2020-04-16
- Subjects:
- Biology -- Classification -- Periodicals
Biology -- Periodicals
Biologie -- Classification -- Périodiques
Biologie -- Périodiques
578.012 - Journal URLs:
- http://ukcatalogue.oup.com/ ↗
- DOI:
- 10.1093/sysbio/syaa026 ↗
- Languages:
- English
- ISSNs:
- 1063-5157
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 8589.180700
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 15046.xml