A generic workflow for effective sampling of environmental vouchers with UUID assignment and image processing

Triebel, Dagmar; Reichert, Wolfgang; Bosert, Simone; Feulner, Martin; Okach, Daniel Osieko; Slimani, Abderachid; Rambold, Gerhard

doi:10.1093/database/bax096

Cited by 9 publications

(9 citation statements)

References 7 publications

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“…Ideally, taxonomic repositories should be able to handle universally unique identifiers to refer to specimens ( Guralnick et al 2015 ; Güntsch et al 2018 ; Nelson et al 2018 ; Triebel et al 2018 ). At present, however, a mandatory use of such identifiers for submission of taxonomic data is unrealistic because, as we have explained above, (i) they do not yet exist for many collections and (ii) the best way of numbering bulk collections is still unclear.…”

Section: Criteria For Taxonomic Data Repositoriesmentioning

confidence: 99%

Repositories for Taxonomic Data: Where We Are and What is Missing

et al. 2020

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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.]

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Section: Criteria For Taxonomic Data Repositoriesmentioning

confidence: 99%

Repositories for Taxonomic Data: Where We Are and What is Missing

et al. 2020

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“…This information should guarantee the repeatability of the conditions for observation and thus might allow—if all influential factors could be kept under control—for reproducibility of study results. This article supplements two preceding ones, which are also dedicated to the management of environmental research data ( 30 , 31 ).…”

Section: Introductionmentioning

confidence: 77%

“…The linkages between the segments within campaigns or along a whole workflow can be achieved by applying physical (or digital) object identifier relations, mainly parent identity relation. Object identifiers are identifiers used for defining the physical and digital object or unit identity ( 30 ). Further explanations are given in the chapter ‘Object Identity and Object Identifiers’ below and in Figure 1 .…”

Section: Abstract Model For Analysing and Describing Fair Digital Objmentioning

confidence: 99%

FAIR digital objects in environmental and life sciences should comprise workflow operation design data and method information for repeatability of study setups and reproducibility of results

et al. 2020

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Repeatability of study setups and reproducibility of research results by underlying data are major requirements in science. Until now, abstract models for describing the structural logic of studies in environmental sciences are lacking and tools for data management are insufficient. Mandatory for repeatability and reproducibility is the use of sophisticated data management solutions going beyond data file sharing. Particularly, it implies maintenance of coherent data along workflows. Design data concern elements from elementary domains of operations being transformation, measurement and transaction. Operation design elements and method information are specified for each consecutive workflow segment from field to laboratory campaigns. The strict linkage of operation design element values, operation values and objects is essential. For enabling coherence of corresponding objects along consecutive workflow segments, the assignment of unique identifiers and the specification of their relations are mandatory. The abstract model presented here addresses these aspects, and the software DiversityDescriptions (DWB-DD) facilitates the management of thusly connected digital data objects and structures. DWB-DD allows for an individual specification of operation design elements and their linking to objects. Two workflow design use cases, one for DNA barcoding and another for cultivation of fungal isolates, are given. To publish those structured data, standard schema mapping and XML-provision of digital objects are essential. Schemas useful for this mapping include the Ecological Markup Language, the Schema for Meta-omics Data of Collection Objects and the Standard for Structured Descriptive Data. Data pipelines with DWB-DD include the mapping and conversion between schemas and functions for data publishing and archiving according to the Open Archival Information System standard. The setting allows for repeatability of study setups, reproducibility of study results and for supporting work groups to structure and maintain their data from the beginning of a study. The theory of ‘FAIR++’ digital objects is introduced.

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“…Specimens were photographed alive and subsequently transferred to 96% ethanol or preserved in formaldehyde/seawater (1:5), after removing a small piece for barcoding. Detailed information on specimens with our internal identifiers and museum numbers will be available in Diversity Workbench (Triebel et al 2018) within the module Diversity Collection. Type material is stored in the Museum Zoologicum Bogoriense in Bogor, Java, Indonesia (MZB.…”

Section: Methodsmentioning

confidence: 99%