scholarly journals Best practices for connecting genetic records with specimen data

2018 ◽  
Vol 2 ◽  
pp. e26369
Author(s):  
Michael Trizna
Keyword(s):  
Best Practices ◽  
Good News ◽  
Sequencing Technology ◽  
Global Biodiversity Information Facility ◽  
A Value ◽  
Darwin Core ◽  
High Quality Sequence ◽  
Voucher Specimens ◽  
Tight Connection ◽  
Biodiversity Information

As rapid advances in sequencing technology result in more branches of the tree of life being illuminated, there has actually been a decrease in the percentage of sequence records that are backed by voucher specimens Trizna 2018b. The good news is that there are tools Trizna (2017), NCBI (2005), Biocode LLC (2014) to enable well-databased museum vouchers to automatically validate and format specimen and collection metadata for high quality sequence records. Another problem is that there are millions of existing sequence records that are known to contain either incorrect or incomplete specimen data. I will show an end-to-end example of sequencing specimens from a museum, depositing their sequence records in NCBI's (National Center for Biotechnology Information) GenBank database, and then providing updates to GenBank as the museum database revises identifications. I will also talk about linking records from specimen databases as well. Over one million records in the Global Biodiversity Information Facility (GBIF) Trizna (2018a) contain a value in the Darwin Core term "associatedSequences", and I will examine what is currently contained in these entries, and how best to format them to ensure that a tight connection is made to sequence records.

scholarly journals Furthering Genomic Research Infrastructures: The Global Genome Biodiversity Network

2019 ◽  
Vol 3 ◽  
Author(s):  
Katharine Barker ◽  
Jonas Astrin ◽  
Gabriele Droege ◽  
Jonathan Coddington ◽  
Ole Seberg
Keyword(s):  
Natural History ◽  
Best Practices ◽  
Genomic Research ◽  
Benefit Sharing ◽  
Global Biodiversity Information Facility ◽  
Access And Benefit Sharing ◽  
Culture Collections ◽  
Data Standard ◽  
Research Infrastructures ◽  
Biodiversity Information

Most successful research programs depend on easily accessible and standardized research infrastructures. Until recently, access to tissue or DNA samples with standardized metadata and of a sufficiently high quality, has been a major bottleneck for genomic research. The Global Geonome Biodiversity Network (GGBN) fills this critical gap by offering standardized, legal access to samples. Presently, GGBN’s core activity is enabling access to searchable DNA and tissue collections across natural history museums and botanic gardens. Activities are gradually being expanded to encompass all kinds of biodiversity biobanks such as culture collections, zoological gardens, aquaria, arboreta, and environmental biobanks. Broadly speaking, these collections all provide long-term storage and standardized public access to samples useful for molecular research. GGBN facilitates sample search and discovery for its distributed member collections through a single entry point. It stores standardized information on mostly geo-referenced, vouchered samples, their physical location, availability, quality, and the necessary legal information on over 50,000 species of Earth’s biodiversity, from unicellular to multicellular organisms. The GGBN Data Portal and the GGBN Data Standard are complementary to existing infrastructures such as the Global Biodiversity Information Facility (GBIF) and International Nucleotide Sequence Database (INSDC). Today, many well-known open-source collection management databases such as Arctos, Specify, and Symbiota, are implementing the GGBN data standard. GGBN continues to increase its collections strategically, based on the needs of the research community, adding over 1.3 million online records in 2018 alone, and today two million sample data are available through GGBN. Together with Consortium of European Taxonomic Facilities (CETAF), Society for the Preservation of Natural History Collections (SPNHC), Biodiversity Information Standards (TDWG), and Synthesis of Systematic Resources (SYNTHESYS+), GGBN provides best practices for biorepositories on meeting the requirements of the Nagoya Protocol on Access and Benefit Sharing (ABS). By collaboration with the Biodiversity Heritage Library (BHL), GGBN is exploring options for tagging publications that reference GGBN collections and associated specimens, made searchable through GGBN’s document library. Through its collaborative efforts, standards, and best practices GGBN aims at facilitating trust and transparency in the use of genetic resources.

scholarly journals An audit of some processing effects in aggregated occurrence records

ZooKeys ◽  
2018 ◽  
Vol 751 ◽  
pp. 129-146 ◽  
Author(s):  
Robert Mesibov
Keyword(s):  
Data Loss ◽  
Global Biodiversity Information Facility ◽  
Australian Museum ◽  
Darwin Core ◽  
Species Groups ◽  
Processing Effects ◽  
Global Biodiversity ◽  
Name Changes ◽  
Biodiversity Information ◽  
Occurrence Records

A total of ca 800,000 occurrence records from the Australian Museum (AM), Museums Victoria (MV) and the New Zealand Arthropod Collection (NZAC) were audited for changes in selected Darwin Core fields after processing by the Atlas of Living Australia (ALA; for AM and MV records) and the Global Biodiversity Information Facility (GBIF; for AM, MV and NZAC records). Formal taxon names in the genus- and species-groups were changed in 13–21% of AM and MV records, depending on dataset and aggregator. There was little agreement between the two aggregators on processed names, with names changed in two to three times as many records by one aggregator alone compared to records with names changed by both aggregators. The type status of specimen records did not change with name changes, resulting in confusion as to the name with which a type was associated. Data losses of up to 100% were found after processing in some fields, apparently due to programming errors. The taxonomic usefulness of occurrence records could be improved if aggregators included both original and the processed taxonomic data items for each record. It is recommended that end-users check original and processed records for data loss and name replacements after processing by aggregators.

scholarly journals Biodiversity Information Services: A (not-so-) little knowledge that acts

2018 ◽  
Vol 2 ◽  
pp. e25738 ◽  
Author(s):  
Arturo Ariño ◽  
Daniel Noesgaard ◽  
Angel Hjarding ◽  
Dmitry Schigel
Keyword(s):  
Critical Mass ◽  
The Body ◽  
Global Biodiversity Information Facility ◽  
Entire List ◽  
Darwin Core ◽  
Biogeographical Regions ◽  
Continuous Presence ◽  
Set Up ◽  
Taxonomic Groups ◽  
Biodiversity Information

Standards set up by Biodiversity Information Standards-Taxonomic Databases Working Group (TDWG), initially developed as a way to share taxonomical data, greatly facilitated the establishment of the Global Biodiversity Information Facility (GBIF) as the largest index to digitally-accessible primary biodiversity information records (PBR) held by many institutions around the world. The level of detail and coverage of the body of standards that later became the Darwin Core terms enabled increasingly precise retrieval of relevant records useful for increased digitally-accessible knowledge (DAK) which, in turn, may have helped to solve ecologically-relevant questions. After more than a decade of data accrual and release, an increasing number of papers and reports are citing GBIF either as a source of data or as a pointer to the original datasets. GBIF has curated a list of over 5,000 citations that were examined for contents, and to which tags were applied describing such contents as additional keywords. The list now provides a window on what users want to accomplish using such DAK. We performed a preliminary word frequency analysis of this literature, starting at titles, which refers to GBIF as a resource. Through a standardization and mapping of terms, we examined how the facility-enabled data seem to have been used by scientists and other practitioners through time: what concepts/issues are pervasive, which taxon groups are mostly addressed, and whether data concentrate around specific geographical or biogeographical regions. We hoped to cast light on which types of ecological problems the community believes are amenable to study through the judicious use of this data commons and found that, indeed, a few themes were distinctly more frequently mentioned than others. Among those, generally-perceived issues such as climate change and its effect on biodiversity at global and regional scales seemed prevalent. The taxonomic groups were also unevenly mentioned, with birds and plants being the most frequently named. However, the entire list of potential subjects that might have used GBIF-enabled data is now quite wide, showing that the availability of well-structured data has spawned a widening spectrum of possible use cases. Among them, some enjoy early and continuous presence (e.g. species, biodiversity, climate) while others have started to show up only later, once a critical mass of data seemed to have been attained (e.g. ecosystems, suitability, endemism). Biodiversity information in the form of standards-compliant DAK may thus already have become a commodity enabling insight into an increasingly more complex and diverse body of science. Paraphrasing Tennyson, more things were wrought by data than TDWG dreamt of.

BiGe-Onto: An ontology-based system for managing biodiversity and biogeography data1

2020 ◽  
Vol 15 (4) ◽  
pp. 411-437 ◽  
Author(s):  
Marcos Zárate ◽  
Germán Braun ◽  
Pablo Fillottrani ◽  
Claudio Delrieux ◽  
Mirtha Lewis
Keyword(s):  
Data Sources ◽  
Biodiversity Data ◽  
Global Biodiversity Information Facility ◽  
Sparql Endpoint ◽  
Darwin Core ◽  
Metadata Standards ◽  
Great Progress ◽  
Global Biodiversity ◽  
Research Domains ◽  
Biodiversity Information

Great progress to digitize the world’s available Biodiversity and Biogeography data have been made recently, but managing data from many different providers and research domains still remains a challenge. A review of the current landscape of metadata standards and ontologies in Biodiversity sciences suggests that existing standards, such as the Darwin Core terminology, are inadequate for describing Biodiversity data in a semantically meaningful and computationally useful way. As a contribution to fill this gap, we present an ontology-based system, called BiGe-Onto, designed to manage data together from Biodiversity and Biogeography. As data sources, we use two internationally recognized repositories: the Global Biodiversity Information Facility (GBIF) and the Ocean Biogeographic Information System (OBIS). BiGe-Onto system is composed of (i) BiGe-Onto Architecture (ii) a conceptual model called BiGe-Onto specified in OntoUML, (iii) an operational version of BiGe-Onto encoded in OWL 2, and (iv) an integrated dataset for its exploitation through a SPARQL endpoint. We will show use cases that allow researchers to answer questions that manage information from both domains.

scholarly journals Vocabulary challenges with invasive species data sharing

2018 ◽  
Vol 2 ◽  
pp. e25642
Author(s):  
Annie Simpson
Keyword(s):  
Invasive Species ◽  
Native Species ◽  
Value Added ◽  
Application Programming Interface ◽  
The United States ◽  
United States Geological Survey ◽  
Global Biodiversity Information Facility ◽  
Darwin Core ◽  
Biodiversity Information ◽  
The U.S

Biodiversity Information Serving our Nation - BISON (bison.usgs.gov) is the U.S. node to the Global Biodiversity Information Facility (gbif.org), containing more than 375 million documented locations for all species in the U.S. It is hosted by the United States Geological Survey (USGS) and includes a web site and application programming interface for apps and other websites to use for free. With this massive database one can see not only the 15 million records for nearly 10 thousand non-native species in the U.S. and its territories, but also their relationship to all of the other species in the country as well as their full national range. Leveraging this huge resource and its enterprise level cyberinfrastructure, USGS BISON staff have created a value-added feature by labeling non-native species records, even where contributing datasets have not provided such labels. Based on our ongoing four-year compilation of non-native species scientific names from the literature, specific examples will be shared about the ambiguity and evolution of terms that have been discovered, as they relate to invasiveness, impact, dispersal, and management. The idea of incorporating these terms into an invasive species extension to Darwin Core has been discussed by Biodiversity Information Standards (TDWG) working group participants since at least 2005. One roadblock to the implementation of this standard's extension has been the diverse terminology used to describe the characteristics of biological invasions, terminology which has evolved significantly over the past decade.

scholarly journals A reference library for the identification of Canadian invertebrates: 1.5 million DNA barcodes, voucher specimens, and genomic samples

2019 ◽  
Author(s):  
Jeremy R. deWaard ◽  
Sujeevan Ratnasingham ◽  
Evgeny V. Zakharov ◽  
Alex V. Borisenko ◽  
Dirk Steinke ◽  
...  
Keyword(s):  
Land Surface ◽  
Animal Species ◽  
Sequence Data ◽  
Dna Barcodes ◽  
Reference Library ◽  
Global Biodiversity Information Facility ◽  
Dna Sequence Data ◽  
Voucher Specimens ◽  
Data Portal ◽  
Biodiversity Information

AbstractThe reliable taxonomic identification of organisms through DNA sequence data requires a well parameterized library of curated reference sequences. However, it is estimated that just 15% of described animal species are represented in public sequence repositories. To begin to address this deficiency, we provide DNA barcodes for 1,500,003 animal specimens collected from 23 terrestrial and aquatic ecozones at sites across Canada, a nation that comprises 7% of the planet’s land surface. In total, 14 phyla, 43 classes, 163 orders, 1123 families, 6186 genera, and 64,264 Barcode Index Numbers (BINs; a proxy for species) are represented. Species-level taxonomy was available for 38% of the specimens, but higher proportions were assigned to a genus (69.5%) and a family (99.9%). Voucher specimens and DNA extracts are archived at the Centre for Biodiversity Genomics where they are available for further research. The corresponding sequence and taxonomic data can be accessed through the Barcode of Life Data System, GenBank, the Global Biodiversity Information Facility, and the Global Genome Biodiversity Network Data Portal.

scholarly journals A reference library for Canadian invertebrates with 1.5 million barcodes, voucher specimens, and DNA samples

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Jeremy R. deWaard ◽  
Sujeevan Ratnasingham ◽  
Evgeny V. Zakharov ◽  
Alex V. Borisenko ◽  
Dirk Steinke ◽  
...  
Keyword(s):  
Land Surface ◽  
Animal Species ◽  
Sequence Data ◽  
Dna Barcodes ◽  
Reference Library ◽  
Global Biodiversity Information Facility ◽  
Dna Sequence Data ◽  
Voucher Specimens ◽  
Data Portal ◽  
Biodiversity Information

AbstractThe reliable taxonomic identification of organisms through DNA sequence data requires a well parameterized library of curated reference sequences. However, it is estimated that just 15% of described animal species are represented in public sequence repositories. To begin to address this deficiency, we provide DNA barcodes for 1,500,003 animal specimens collected from 23 terrestrial and aquatic ecozones at sites across Canada, a nation that comprises 7% of the planet’s land surface. In total, 14 phyla, 43 classes, 163 orders, 1123 families, 6186 genera, and 64,264 Barcode Index Numbers (BINs; a proxy for species) are represented. Species-level taxonomy was available for 38% of the specimens, but higher proportions were assigned to a genus (69.5%) and a family (99.9%). Voucher specimens and DNA extracts are archived at the Centre for Biodiversity Genomics where they are available for further research. The corresponding sequence and taxonomic data can be accessed through the Barcode of Life Data System, GenBank, the Global Biodiversity Information Facility, and the Global Genome Biodiversity Network Data Portal.

scholarly journals Knowledge Extraction from Specimen-Derived Data from GenBank to Enrich Biodiversity Information

2021 ◽  
Vol 5 ◽  
Author(s):  
Takeru Nakazato
Keyword(s):  
Gene Sequence ◽  
Environmental Dna ◽  
Knowledge Extraction ◽  
Sequence Information ◽  
Gene Sequences ◽  
File Transfer ◽  
Global Biodiversity Information Facility ◽  
Darwin Core ◽  
Taking Action ◽  
Biodiversity Information

DNA barcoding and environmental DNA (eDNA) are increasing the need for the utilization of gene sequences in the field of biodiversity. GBIF (Global Biodiversity Information Facility) and GGBN (Global Genome Biodiversity Network) are taking action on the treatment of gene sequences in the field of biodiversity (Finstad et al. 2020). Gene sequences have been collected and published by INSDC (International Nucleotide Sequence Database Collaboration) for over 30 years (Arita et al. 2020). Biodiversity information has been collected using standards such as Darwin Core (Wieczorek et al. 2012), but INSDC gene sequences are stored in their own format. In the field of bioinformatics, researchers are also organizing the BioHackathon series, notably the NBDC/DBCLS BioHackathon and the spin-off Biohackathon Europe, to standardize data through the Semantic Web (Garcia Castro et al. 2021, Vos et al. 2020), but the linkage with biodiversity information has just begun. In this study, as an example of linking gene sequence information with biodiversity information, I attempted to construct an infrastructure for knowledge extraction by utilising gene sequence entries derived from museum specimens from GenBank (Sayers et al. 2020). I have previously surveyed the BOLD (The Barcode of Life Data System) (Ratnasingham and Hebert 2007) IDs listed in GenBank (Nakazato 2020). I downloaded the fish and insect data from the GenBank FTP (file transfer protocol) site. Then I extracted the descriptions in the "specimen_voucher" field and obtained 749,627 (28% of the fish entries in GenBank) and 1,621,890 (13%) specimen IDs, respectively. I also extracted from the "note" field approximately 1000 entries describing the type of the specimen, such as "holotype", "lectotype", and "paratype". These extracts include descriptions written in natural language. NCBI (National Center for Biotechnology Information) publishes the BioCollections database (Sharma et al. 2019), and these data may be able to refine the description. In the future, I plan to map these extracted IDs to the collection IDs in the biodiversity information database. This will enable us to enrich the biodiversity information with GenBank descriptions, for example, by adding articles listed in GenBank as references to the specimen data.

scholarly journals A Case Study for Connecting Collections and Ecological Research

2018 ◽  
Vol 2 ◽  
pp. e26008
Author(s):  
Richard Levy
Keyword(s):  
Field Work ◽  
Ex Situ ◽  
Full Potential ◽  
Ecological Research ◽  
Global Biodiversity Information Facility ◽  
Tissue Samples ◽  
Plot Sampling ◽  
Darwin Core ◽  
Voucher Specimens

Integration of ecological research and specimen collection has recently been a topic of focus in the literature (i.e. Morrison et al. 2017) and within organizing groups such as Integrated Digitized Biocollections (iDigBio). Pairing these two fields only stands to benefit biodiversity science, as one’s weakness is the other’s strength. For example, ecological studies often lack the verifiable proof of the taxonomy of its subjects, which is offered by voucher specimens. Conversely, museum collections are often lacking detailed site descriptions or are completely disjointed from plot sampling datasets. Researchers at the Denver Botanic Gardens are addressing this disconnect by conducting a case study that melds ecological plot sampling and floristic documentation. We center our study design and methods around the objective of producing a deliverable data package in the form of a Darwin Core Archive. Moreover, our aim is to use the Darwin Core to its full potential, ultimately publishing a package on the Global Biodiversity Information Facility (GBIF) that includes extensive metadata, voucher specimens, genomic quality tissue samples, plot sampling data, in-situ, ex-situ, and habitat level images. Here I present an update on the ongoing field work, our intentions, any evaluation, and the overall workflow of the process.

scholarly journals SpOccSum: An easy-to-use Python tool to summarize species occurrence data from material examined lists in taxonomic revisions

2019 ◽  
Vol 3 ◽  
Author(s):  
Michael Trizna ◽  
Torsten Dikow
Keyword(s):  
Data Science ◽  
Biodiversity Data ◽  
Species Occurrence ◽  
Global Biodiversity Information Facility ◽  
Seasonal Incidence ◽  
Distribution Maps ◽  
Occurrence Data ◽  
Darwin Core ◽  
Biodiversity Information ◽  
Northern And Southern Hemispheres

Taxonomic revisions contain crucial biodiversity data in the material examined sections for each species. In entomology, material examined lists minimally include the collecting locality, date of collection, and the number of specimens of each collection event. Insect species might be represented in taxonomic revisions by only a single specimen or hundreds to thousands of specimens. Furthermore, revisions of insect genera might treat small genera with few species or include tens to hundreds of species. Summarizing data from such large and complex material examined lists and revisions is cumbersome, time-consuming, and prone to errors. However, providing data on the seasonal incidence, abundance, and collecting period of species is an important way to mobilize primary biodiversity data to understand a species’s occurrence or rarity. Here, we present SpOccSum (Species Occurrence Summary)—a tool to easily obtain metrics of seasonal incidence from specimen occurrence data in taxonomic revisions. SpOccSum is written in Python (Python Software Foundation 2019) and accessible through the Anaconda Python/R Data Science Platform as a Jupyter Notebook (Kluyver et al. 2016). The tool takes a simple list of specimen data containing species name, locality, date of collection (preferably separated by day, month, and year), and number of specimens in CSV format and generates a series of tables and graphs summarizing: number of specimens per species, number of specimens collected per month, number of unique collection events, as well as earliest, and most recent collecting year of each species. number of specimens per species, number of specimens collected per month, number of unique collection events, as well as earliest, and most recent collecting year of each species. The results can be exported as graphics or as csv-formatted tables and can easily be included in manuscripts for publication. An example of an early version of the summary produced by SpOccSum can be viewed in Tables 1, 2 from Markee and Dikow (2018). To accommodate seasonality in the Northern and Southern Hemispheres, users can choose to start the data display with either January or July. When geographic coordinates are available and species have widespread distributions spanning, for example, the equator, the user can itemize particular regions such as North of Tropic of Cancer (23.5˚N), Tropic of Cancer to the Equator, Equator to Tropic of Capricorn, and South of Tropic of Capricorn (23.5˚S). Other features currently in development include the ability to produce distribution maps from the provided data (when geographic coordinates are included) and the option to export specimen occurrence data as a Darwin-Core Archive ready for upload to the Global Biodiversity Information Facility (GBIF).

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