Global Genome Biodiversity Network Research Articles

An Overview of the French eDNA Data Landscape: Focus on a national technical repository of reference genetic sequences

Environmental DNA (eDNA) data enables biodiversity to be monitored at unprecedented resolution and scale. There is great potential in combining knowledge from traditional and innovative methods such as eDNA for biodiversity assessment. eDNA use cases are increasing in aquatic and marine environments, and studies on soils have been developed in recent years. PatriNat*1 (under the guardianship of the French Biodiversity Office (OFB), National Museum of Natural History (MNHN), National Center for Scientific Research (CNRS), and Research Institute for Development (IRD)) is a French data and expertise center working with environmental and research stakeholders to develop data exchanges at all levels. We discuss what eDNA data is (Fig. 1), the different types of data, and the importance of their storage and accessibility. As the amount of eDNA data increases, public agencies need to propose FAIR (Findable, Accessible, Interoperable, Reusable) tools and methods to facilitate their use and foster the development of relevant scientific expertise. We give an overview of the French eDNA data landscape and links with existing standards SINP*2 (National Heritage Inventory Information System), Darwin Core*3(Wieczorek et al. 2012) and workflows (Fig. 2). A priority of eDNA data is to have reliable reference bases and FAIR metadata. PatriNat's new tool will provide access to expertly validated genetic sequence data on species present in France, and is urgently needed for research but also knowledge, monitoring, public policies, and potential law enforcement purposes. We therefore present this technical database built in conjunction with, among other initiatives, DiSSCo*4, iBOL*5 and TaxRef*6 (Gargominy et al. 2022). It will manage 3 data types: Intrinsic sequence data (marker, sequencing methods, etc.). Sequence management (organization, identifiers, URLs, etc.). Voucher data Intrinsic sequence data (marker, sequencing methods, etc.). Sequence management (organization, identifiers, URLs, etc.). Voucher data It will use the nomenclature of Chakrabarty et al. (2013) as well as: The Global Genome Biodiversity Network (GGBN) standard*7 (Droege et al. 2016) The Minimum information about any sequence (MIxS) standard (Yilmaz et al. 2011) The Biological Collection Data (ABCD) standard*8 (Holetschek et al. 2012) The Collections Descriptions terms*9 (Woodburn et al. 2021) The Global Genome Biodiversity Network (GGBN) standard*7 (Droege et al. 2016) The Minimum information about any sequence (MIxS) standard (Yilmaz et al. 2011) The Biological Collection Data (ABCD) standard*8 (Holetschek et al. 2012) The Collections Descriptions terms*9 (Woodburn et al. 2021) The DwC DNA extension*10 can be used for sharing parts of its contents to the Global Biodiversity Information Facility, but referencing sequences associated with specimens/vouchers will require other standards.

Enhancing DNA barcode reference libraries by harvesting terrestrial arthropods at the Smithsonian's National Museum of Natural History.

The use of DNA barcoding has revolutionised biodiversity science, but its application depends on the existence of comprehensive and reliable reference libraries. For many poorly known taxa, such reference sequences are missing even at higher-level taxonomic scales. We harvested the collections of the Smithsonian's National Museum of Natural History (USNM) to generate DNA barcoding sequences for genera of terrestrial arthropods previously not recorded in one or more major public sequence databases. Our workflow used a mix of Sanger and Next-Generation Sequencing (NGS) approaches to maximise sequence recovery while ensuring affordable cost. In total, COI sequences were obtained for 5,686 specimens belonging to 3,737 determined species in 3,886 genera and 205 families distributed in 137 countries. Success rates varied widely according to collection data and focal taxon. NGS helped recover sequences of specimens that failed a previous run of Sanger sequencing. Success rates and the optimal balance between Sanger and NGS are the most important drivers to maximise output and minimise cost in future projects. The corresponding sequence and taxonomic data can be accessed through the Barcode of Life Data System, GenBank, the Global Biodiversity Information Facility, the Global Genome Biodiversity Network Data Portal and the NMNH data portal.

Specimen Identifiers: Linking tissues, DNA samples, and sequence data to voucher specimens in publicly accessible databases

Nearly all disciplines of biology now have some form of molecular genetic analyses incorporated into areas of their research, from systematics, ecology, and behavior, to physiology and conservation. In order for science to be transparent, the source and provenance of the genetic material used must be easily identifiable and traceable, following the FAIR principles of being Findable Accessible, Interoperable, and Reusable (Wilkinson et al. 2016). Natural history collections are ever-increasingly facilitating the use of genetic components from collection objects, and in some cases increasing the number and types of collection objects under their care (i.e., tissue/DNA-only, e.g., blood, feather, skin- fin-clips, environmental samples). Most natural history collections are now making their holdings available online, either on their own platforms or via aggregate search engines like the Global Biodiversity Information Facility (GBIF) and the Global Genome Biodiversity Network (GGBN). Many natural history collections are also now using digital management systems, where digital identifiers such as Digital Object Identifiers (DOIs) and Uniform Resource Identifiers (URIs) are assigned to objects in collections (Güntsch et al. 2017), including multiple objects derived from the same individual organism (e.g., voucher specimen, images, and genomic samples). Associated objects may receive different digital identifiers in order to be uniquely identifiable in the digital management system, but sharing this information on third-party platforms (e.g., GBIF, GGBN) is challenging, especially in avoiding duplicate entries. Furthermore, genetic materials are often sought out by researchers external to the holding collection institution, and molecular sequence data are then generated and deposited in third-party public repositories, such as GenBank and the Barcode of Life Database (BOLD). Making genomic material digitally discoverable to researchers, and linking them and data generated from these samples back to the associated voucher specimens is another challenge. Fortunately, there is a current international initiative to collate the different forms of data surrounding a voucher specimen, as a Digital Extended Specimen (DES), across multiple institutions worldwide (Hardisty et al. 2022). The National Center for Biotechnology Information (NCBI), which hosts GenBank, has created a BioCollections Database to curate metadata for natural history collections and linking sequence data to voucher specimens (Sharma et al. 2018). Institution codes, collection codes, and catalog numbers are linked to create a “structured voucher” annotation (following the Darwin Core Triplet) to standardize usage across interconnected databases (e.g., GenBank, European Nucleotide Archive, and the DNA Databank of Japan). However, duplicate institution codes can make this complicated, and collection institutions that use digital identifiers instead of traditional catalog numbers make this even more challenging. The NCBI BioCollections Database curators have resolved the duplicate institution codes problem, by adding the three-letter country code (or state code, within the same country). However, this database is used only for sequence data, in GenBank, and related databases (e.g., ENA, DDBJ), which raises the question, is there a need for a more universal biocollection codes database? Additionally, as museums move towards using digital identifiers, in the place of catalog numbers, confusion can arise when multiple digital identifiers are assigned to parts of the same “specimen” (e.g., specimen voucher, tissue, DNA, images, etc.). For instance, if a given specimen has unique URIs for the voucher specimen, the DNA, and an image, a researcher borrowing the DNA, might use the DNA URI as an identifier for the genetic database. A different researcher, at a later date, might see that specimen (or image) in the museum’s collection, and think it is a different specimen of that species, when in fact it is the same specimen. This could result in a second researcher borrowing the sample and publishing it as a “new” sequence. Researchers already have difficulties in submitting sequences to GenBank, as several have confused field numbers for catalog numbers from the National Museum of Natural History, Smithsonian Institution (Mulcahy et al. 2022). Some museums, using modifiable codes, can append a primary code (from the specimen voucher) for additional “parts” of that specimen. For example, if the primary code for an insect specimen ends in “…6d15ce”, a leg taken for DNA extraction could be modified as “…6d15ce_leg” and “…6d15ce_dna” for the extract. This minimizes the chances for mistaking these as being from different specimens. However, if completely different codes are assigned to different parts of the same specimen, the chance increases for mistaking two objects from the same specimen as being from different specimens. Collections staff must carefully consider the hierarchical relationships of objects in their collections, and how they are assigned URIs, especially when considering long-term operability in current and future aggregate database structures (e.g., GBIF, GGBN, NCBI, and the DES). In this presentation, these issues are raised and the difficulties in linking specimens, genomic resources, and associated data in aggregate databases and data repositories are discussed.

Latimer Core: A new data standard for collection descriptions

The Latimer Core (LtC) schema, named after Marjorie Courtenay-Latimer, is a standard designed to support the representation and discovery of natural science collections by structuring data about the groups of objects that those collections and their subcomponents encompass. Individual items within those groups are represented through other emerging or current standards (e.g., Darwin Core, ABCD). The LtC classes and properties aim to represent information that describes these groupings in enough detail to inform deeper discovery of the resources contained within them. The standard has been developed under the Biodiversity Information Standards (TDWG) Collection Descriptions (CD) Interest Group, and evolved from the earlier work of the Natural Collection Descriptions (NCD) group. Version 1 of the standard includes 23 classes, each with two or more properties (Fig. 1 and Suppl. material 1). The central concept of the standard is the ObjectGroup class, which represents 'an intentionally grouped set of objects with one or more common characteristics'. Arranged around the ObjectGroup are a set of classes that are commonly used to describe and classify the objects within the ObjectGroup, classes covering aspects of the custodianship, management and tracking of the collections, a generic class (MeasurementOrFact) for storing qualitative or quantitative measures within the standard, and a set of classes that are used to describe the structure and description of the dataset. Latimer Core is intended to be sufficiently flexible and scalable to apply to a wide range of collection description use cases, from describing the overall collections holdings of an institution to the contents of a single drawer of material. Various approaches are used to support this flexibility, including the use of generic classes to represent organisations, people, roles and identifiers, and enabling flexible relationships for constructing data models that meet different use cases. The collection description scheme concept is introduced to enable adopters to specify rules in the use of LtC within each specific implementation, demonstrated in Fig. 2. Guidance and reference examples for different modelling approaches to suit different use cases are provided in the LtC guidance documentation. The LtC standard has significant overlap with existing data standards (Suppl. material 2) that represent, for example, individual objects and occurrences, organisations, people and activities. Where possible, LtC has either borrowed terms directly from these standards or less formally aligned with them. Achieving a balance between offering a standard that is sufficiently comprehensive to stand alone and maintains a low technical barrier to adoption whilst minimalising duplication of effort in the context of the wider standards landscape is a notable challenge in the standard development process. The draft standard was submitted to the TDWG Executive in June 2022 to begin the process of formal review and ratification. This includes a list of standard terms and a GitHub wiki of guidance on the concepts behind and use of the standard. In the meantime, the Task Group will continue working on reference examples and serialisations, and working with infrastructures such as the Distributed System of Scientific Collections (DiSSCo) consortium, the GBIF (Global Biodiversity Information Facility) Registry of Scientific Collections, the CETAF (Consortium of European Taxonomic Facilities) Registry of Collections and the Global Genome Biodiversity Network (GGBN) on potential roadmaps towards adoption. In this presentation, we will introduce the key Latimer Core deliverables, highlight some of the challenges faced in the development process, and discuss the potential for community adoption.

RECODE: Towards a next-gen collections management system as part of the institutional and community data ecosystem

Since 2020, the Natural History Museum, London (NHM) has been running the RECODE (Rethinking Collections Data Ecosystems) programme, an initiative that will provision a more open, manageable, configurable and interoperable collections management system (CMS) for the museum. With the overall aim of going live with an initial version of the new CMS by 2025, the first phase of defining a platform-agnostic set of high-level requirements and selecting a new technology partner and platform is nearing completion. The requirements, conceptual data models and other procurement documentation are shared openly through the Open Science Framework (OSF) platform so that any material may benefit and elicit feedback from the wider natural sciences community. RECODE has strived to ensure that our new supplier and technology platform will be well positioned to deliver on the wider vision for community data interoperability, sharing and annotation. Through this presentation, we hope to continue our engagement with the global community by introducing our vision and describing our efforts to ensure that data sharing through technical interoperability and data standards are core features of the new solution. As a digital representation of the collections and related processes, events and transactions, a CMS is an essential tool for many natural science collections, replacing systems that were first analogue and paper-based, and later often distributed across multiple siloed, unstandardised, and unconnected files and databases. Consolidating that data and functionality into coherent, centralised application (as was first achieved at the NHM in 2002) facilitates more effective management of, and access to, both the physical collections and the data describing them. This consolidation also enabled the construction of a core collections data ecosystem within the museum, linking the CMS with frozen collections, providing some basic process for ingestion from digitisation workflows, and setting up a pipeline to offer up data to the NHM Data Portal for publication to the community (Fig. 1). Although an important step on the path, the bespoke nature of these integrations, in part due to technical limitations in the CMS platform for importing and exporting data at scale, have limited further progress in this area. Even just within the museum’s suite of science and collections data platforms there is a range of further potential integrations around the CMS that could add considerable value in streamlining processes and joined-up decision support (Fig. 2). Modern technical capabilities, such as APIs, workflow capabilities and data models, dashboards and analytics, and integrated artificial intelligence (AI) and machine learning (ML) services, provide great potential for better management, sharing and exploitation of the data and the collections themselves. These capabilities, in particular those that support data interoperability, then open up much greater potential for positioning the institutional CMS within the wider external collections, biodiversity and geodiversity data ecosystem (Fig. 3). Not only does this offer much greater potential for using community-curated authorities, tools and services (e.g., Catalogue of Life, GeoNames, Bionomia and Wikidata), but also closer integration with data aggregators and service providers such as the Global Biodiversity Information Facility (GBIF), Distributed System of Scientific Collections (DiSSCo), GeoCASe and Global Genome Biodiversity Network (GGBN), and opens up avenues for joining future initiatives like community data annotation. Over the past decade, the NHM has become increasingly aware that one of the major barriers to moving forward with our ambitions in this regard is outdated infrastructure and technology in the CMS marketplace, which has struggled to keep pace with the wider technology landscape. This realisation has driven the museum to consider more enterprise (and better resourced) technology sectors like Content Services Platforms (CSP). These platforms provide mature products that include these more cutting edge technical capabilities, and tend to be highly configurable in order to be applicable across a wide range of domains. The onus, however, would be on us to design the data models and processes that would need to be configured within these platforms, which forms a major component of the RECODE programme. In this regard, both existing and emerging community standards and models like Spectrum, Darwin Core, Access to Biological Collections Data + Extension for Geosciences (ABCD+EFG), Latimer Core and the International Committee for Documentation Conceptual Reference Model (CIDOC CRM) are vital and will be used heavily to inform this work. Throughout the RECODE process, NHM intends to remain focused on the bigger community vision, and by creating a more open, flexible and community-ready CMS with a stronger focus on interoperability, standards, data quality and data sharing from the outset, pioneer a potential new CMS approach that may benefit others as well as ourselves.

The Ocean Genome Legacy: A Genomic Resource Repository for Marine Life.

The Ocean Genome Legacy: A Genomic Resource Repository for Marine Life.

Knowledge Extraction from Specimen-Derived Data from GenBank to Enrich 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.

Mapping and Publishing Sequence-Derived Data through Biodiversity Data Platforms

Most users will foresee the use of genetic sequences in the context of molecular ecology or phylogenetic research, however, a sequence with coordinates and a timestamp is a valuable biodiversity occurrence that is useful in a much broader context than its original purpose. To uncover this potential, sequence-derived data need to become findable, accessible, interoperable, and reusable through generalist biodiversity data platforms. Stimulated by the Biodiversity_Next discussions in 2019, we have worked for about 10 months to put together practical data mapping and data publishing experiences in Norway, Australia, Sweden, and Denmark, as well as in the UNITE and the GBIF (Global Biodiversity Information Facility) networks. The resulting guide was put together to provide practical instruction for mapping sequence-derived data. Biodiversity data communities remain dominated by the macroscopic, easily detectable, morphologically identifiable species. This is not only true for citizen science and other forms of biodiversity popularization, but is also visible in the university and museum department structures, financial resource allocations, biodiversity legislation, and policy design. Recent decades of molecular advances have increased the power of genetic methods for detecting, describing, and documenting global biodiversity. We have yet to see the wide shift of data generating efforts from the traditional taxonomic foci of biodiversity assesments to the more balanced and inclusive systems focusing on all functionally important taxa and environments. These include soil, limnic and marine environments, decomposing plants and deadwood, and all life therein. Environmental DNA data enable recording of present and past presence of micro- and macroscopic organisms with minimal effort and by non-invasive methods. The apparent ease of these methods requires a cautious approach to the resulting data and their interpretation. It remains important to define and agree on the organism recording and reporting routines for genetic data. DNA data represent a major addition to the many ways in which GBIF and other biodiversity data platforms index the living world. Our guide is resting on the shoulders of those who have been developing and improving MIxS (Minimum Information about any (x) Sequence), GGBN (Global Genome Biodiversity Network) and other data standards. The added value of publishing sequence-derived data through non-genetic biodiversity discovery platforms relates to spatio-temporal occurrences and sequence-based names. Reporting sequence-derived occurrences in an open and reproducible way has a wide range of benefits: notably, it increases citability, highlights the taxa concerned in the context of biological conservation, and contributes to taxonomic and ecological knowledge.

Linking Agrobiodiversity Data through Metadata Standards

Agrobiodiversity, or biodiversity for food and agriculture, plays a major role in the sustainability of food production. As stated by FAO 2019, agrobiodiversity can provide food production systems and society with a variety of services as ecosystem services, crops resilience to threats, sustainable intensification, livelihoods, food security and nutrition. The official definition of the concept has been given by CBD 2000 as "a broad term that includes all components of biological diversity of relevance to food and agriculture, and all components of biological diversity that constitute the agroecosystem: the variety and variability of animals, plants and micro-organisms, at the genetic, species and ecosystem levels, which are necessary to sustain key functions of the agro-ecosystem, its structure and processes". Thus, agrobiodiversity is primarily based on species and their function in agroecosystems. Many projects for sharing agrobiodiversity data in a structured way have emerged over the years. One realizes in looking at the Bioversity International (2018) crop descriptors list that the earliest groups of descriptors for crops and some associated data emerged back in the 1970s. In the same list, there are four multi-crop descriptors and derived standards, which are broad standards for crop-related data, namely: Core descriptors for in situ conservation of crop wild relatives v.1 (Thormann et al. 2013); FAO/Bioversity multi-crop passport descriptors V.2.1 (Alercia et al. 2015); Descriptors for farmers' knowledge of plants (Aknazarov et al. 2009); Descriptors for Genetic Marker Technologies (Vicente et al. 2004). Core descriptors for in situ conservation of crop wild relatives v.1 (Thormann et al. 2013); FAO/Bioversity multi-crop passport descriptors V.2.1 (Alercia et al. 2015); Descriptors for farmers' knowledge of plants (Aknazarov et al. 2009); Descriptors for Genetic Marker Technologies (Vicente et al. 2004). These standards share some core elements in common, as taxon, location, a period of collecting, and were intended to be used in the context of data on the occurrence of species in nature. Darwin Core, a TDWG standard commonly used for sharing data of taxon occurrence in nature (Wieczorek et al. 2012), is a globally used metadata standard, representing "a large majority of the 1.4 billion of species occurrence records shared by the Global Biodiversity Information Facility (GBIF), published by more than 1561 organizations in 59 countries in January 2020" (Body et al. 2020). Darwin Core is a standardized language that applies unique Internationalized Resource Identifiers (IRIs) to each element assigned as a metadata element, plus a label and a definition. It improves the interoperability between databases in the context of the Semantic Web (Duerst and Suignard 2005). We believe it is possible to use Darwin Core to represent agrobiodiversity data if a metadata extension is developed to enroll the agrobiodiversity concepts missing in Darwin Core. Thus, a research project held at the University of São Paulo in partnership with Brazilian Agricultural Research Corporation started to map concepts and descriptors from the literature for agrobiodiversity data representation. This project is the sequence of the research initiated by Soares et al. 2019. The crop descriptors published by Bioversity International (2018) may be integrated into the metadata extension, but also other standards like Global Genome Biodiversity Network (GGBN) Data Standard v1 (Droege et al. 2016) and the Darwin Core germplasm extension (DwC-germplasm). At the moment, we are designing a mind map to organize the agrobiodiversity concepts. We expect the metadata extension will be useful for the scientific community to share agrobiodiversity data as linked data, applying Resource Description Framework (RDF) as a resource relationship model, for example.

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

The 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.

Inclusive innovation: Enhancing global participation in and benefit sharing linked to the utilization of marine genetic resources from areas beyond national jurisdiction

Negotiations for a new international legally binding instrument under the United Nations Convention on the Law of the Sea for the conservation and sustainable use of marine biological diversity of areas beyond national jurisdiction (ABNJ) have commenced. For the new agreement to be fair and effective, it is vital that all States are able to participate in the long-term sustainable use and conservation of the ocean beyond national jurisdiction. This includes participation in marine scientific research and the utilization of marine genetic resources (MGR) through subsequent innovation processes. Open access to MGR, such as data, coupled with capacity building, can promote the equitable sharing of benefits associated with MGR. In this paper, it is hypothesized that an ‘inclusive innovation’ approach may facilitate participation and promote enhanced engagement in the conservation and sustainable use of biodiversity beyond national jurisdiction. A number of existing genetic resource initiatives provide examples of efforts to foster inclusivity in the innovation process, including BioBricks, Open Source Drug Discovery, GenBank and the Global Genome Biodiversity Network. An analysis of these examples enables clear identification of common elements that are adopted by such initiatives, whereby inclusive innovation either develops naturally or is promoted actively through measures for open access, capacity building, and collaboration. By empowering more States and stakeholders to participate in research and innovation processes, global potential in terms of enhanced scientific knowledge and opportunities associated with biodiversity of ABNJ can be promoted and the overall objective of the conservation and sustainable use can be best pursued.

SYNTHESYS+ Molecular Collections in the Age of Genomics: Standards and processes

The aim of the Global Genome Biodiversity Network (GGBN, http://www.ggbn.org) is to foster collaboration among biodiversity biobanks on a global scale in order to further compliance with standards, best practices, and to secure interoperability and exchange of material in accordance with national and international legislation and conventions. Thus, key aspects of GGBN’s mission are to develop a network of trusted collections, establishing standards, and identifying best practices by reaching out to other communities. This is especially critical in the light of new international legislation such as the recent Nagoya Protocol on Access and Benefit Sharing (ABS). Biological repositories such as but not limited to natural history collections, botanic gardens, culture collections and zoos are facing a series of challenges triggered by the rapid acceleration in sequencing technology that has put added pressure on the use of samples, which just a few years ago were considered inaccessible for sequencing. ABS legislation applies to nearly all collection types, and with biodiversity biobanks increasing in number worldwide, there is an urgent need to streamline procedures and to ensure legislative compliance. Within Europe it is necessary to 1) reach common standards for biodiversity and environmental biobanks; 2) define best practices for the use of molecular collections; and 3) try to ease exchange of samples and related information, while staying compliant with legislation and conventions. Within the EU funded SYNTHESYS+ project (http://www.synthesys.info), GGBN is leading Network Activity 3 (NA3). An overview of planned activities and tasks will be given here with special emphasis on linkages within and beyond SYNTHESYS+.

PlutoF: Biodiversity data management platform for the complete data lifecycle

PlutoF online platform (https://plutof.ut.ee) is built for the management of biodiversity data. The concept is to provide a common workbench where the full data lifecycle can be managed and support seamless data sharing between single users, workgroups and institutions. Today, large and sophisticated biodiversity datasets are increasingly developed and managed by international workgroups. PlutoF's ambition is to serve such collaborative projects as well as to provide data management services to single users, museum or private collections and research institutions. Data management in PlutoF follows a logical order of the data lifecycle Fig. 1. At first, project metadata is uploaded including the project description, data management plan, participants, sampling areas, etc. Data upload and management activities then follow which is often linked to the internal data sharing. Some data analyses can be performed directly in the workbench or data can be exported in standard formats. PlutoF includes also data publishing module. Users can publish their data, generating a citable DOI without datasets leaving PlutoF workbench. PlutoF is part of the DataCite collaboration (https://datacite.org) and so far released more than 600 000 DOIs. Another option is to publish observation or collection datasets via the GBIF (Global Biodiversity Information Facility) portal. A. new feature implemented in 2019 allows users to publish High Throughput Sequencing data as taxon occurrences in GBIF. There is an additional option to send specific datasets directly to the Pensoft online journals. Ultimately, PlutoF works as a data archive which completes the data life cycle. In PlutoF users can manage different data types. Most common types include specimen and living specimen data, nucleotide sequences, human observations, material samples, taxonomic backbones and ecological data. Another important feature is that these data types can be managed as a single datasets or projects. PlutoF follows several biodiversity standards. Examples include Darwin Core, GGBN (Global Genome Biodiversity Network), EML (Ecological Metadata Language), MCL (Microbiological Common Language), and MIxS (Minimum Information about any (x) Sequence).

Taxonomic Gap Analysis: A method of evaluating the taxa represented in biodiversity databases

The Global Genome Initiative (GGI) endeavors to collect the Earth’s genomic biodiversity, preserve this biodiversity as high quality genetic resources in Global Genome Biodiversity Network (GGBN) affiliated biorepositories, increase knowledge of biodiversity through genetic sequencing, and make resources and knowledge accessible to researchers via the GGBN Data Portal, the Global Catalogue of Microorganisms (GCM), and the National Center for Biotechnology Information (NCBI) GenBank. In GGI's seven year timespan, it is attempting to collect samples from all 9,870 families and half of the 165,683 genera of life on Earth (Roskov et al. 2019). To accomplish this, GGI must synergistically consider the following questions: What life exists? What has already been preserved as physical resources? What is already known from genetic sequencing? How will novel or legacy collections fill the gaps in resources or knowledge? What life exists? What has already been preserved as physical resources? What is already known from genetic sequencing? How will novel or legacy collections fill the gaps in resources or knowledge? To answer the first question, GGI has explored the use of taxonomic authorities such as the Global Biodiversity Information Facility (GBIF) Backbone Taxonomy and the Catalogue of Life as taxonomic backbones to variously match taxonomic names and derive complete lists of extant taxa at each taxonomic rank. To answer the second question, GGI utilizes the GGBN Data Portal API and the GCM website to extract lists of taxonomic names, which are then standardized to a taxonomic backbone. To answer the third question, following the recommendations of Hanner 2009 for identifying high-quality DNA barcode records, GGI employs the NCBI Entrez Programming Utilities to download GenBank records, then standardizes the associated taxa to a taxonomic backbone. Finally, GGI compares lists of taxa found in specific geographic areas or specific legacy collections to determine the amount of taxonomic novelty a new collection may supply. GGI refers to this comparison of taxonomic databases as a taxonomic gap analysis, an assessment of how well a potential collection fills the taxonomic gaps in physical collections and genetic knowledge. A gap analysis performed by GGI in March 2019 shows that 49% of families and 78% of genera still have no representation as either physical samples or genetic information (Table 1). There are substantial gaps to fill in the endeavor to capture the Earth's biodiversity, and taxonomic gap analysis will continue to be a powerful tool to identify the most promising potential new collections.

Big Data Knowledge of Major Lineages of Life and Priorities for Genomic Research

Genomic science is revolutionizing and accelerating biodiversity research. For collections-based institutions to continue to lead and support biodiversity research, they must adapt to this new reality. Simultaneously, “big data” is accumulating so rapidly that we have unprecedented capacity to plan strategically to use genomics to advance basic and applied science on multiple fronts. For example, seven “big data” sources have the following numbers of records (2018 data): Global Biodiversity Information Facility (GBIF), ~1B; Biodiversity Heritage Library (BHL), ~3.6M; National Center for Biotechnology Information (NCBI), ~220M; Open Tree of Life (OToL), 1.9M; Barcode of Life Data System (BOLD), ~6.3M; Encyclopedia of Life (EOL), ~99K; Global Genome Biodiversity Network (GGBN), ~2M. Collectively, they offer more than 1.2B records on biodiversity. At the scale of species (~2M described, multiple millions undescribed), these data are still too sparse to permit comprehensive conclusions. At the scale of families (i.e. deeper clades of life), the situation is far more promising: about 9,911 families are known, and relatively few are discovered each year. This suggests that at the family rank (and above), our knowledge of life on Earth is reasonably complete. Approximately 160,000 valid and accepted genera exist, but certainly many new genera await discovery and description. Genomics is the fastest way to group species into more inclusive lineages such as genera and families, and is certainly faster than traditional alpha taxonomy. Synergistically, these “big data” answer four important questions at deeper clade levels: What is it? Where is it? What do we know about it? What do we know about its genome? Approximately 4,500 eukaryotic genomes have been sequenced. The converse of what we know is what we do not know, another meaning of “dark taxa.” We can use the distribution and density of big data at deeper clade levels (families, genera) to quantitatively analyze “dark taxa” and therefore to strategically optimize knowledge and preservation of biodiversity at a global scale. Technicalities of the quantitative prioritization scheme are debatable, but some initial, simple scoring systems can help to prioritize lineages for collection and genetic research so as to most efficiently illuminate regions in the tree of life that that are neither preserved, imaged, geo-located, studied, nor known genomically. This analysis presents criteria and goals for collaborating to build a global genomic collection to maximize efficient acquisition of biodiversity genomic knowledge, and identifies the most valuable and highest priority taxa for genomic research.

Towards Linked Open Molecular Data: Recommendations for researchers, collections, infrastructures and publishers

The variety of molecular methods used to analyze biosamples is continuously increasing, as is the need for the standardized deposition, documentation and citation of both the samples as well as the methods applied to them. Global initiatives such as the International Nucleotide Sequence Database Collaboration (INSDC, http://www.insdc.org), Barcode of Life Data System (BOLD, http://www.boldsystems.org), the Global Biodiversity Information Facility (GBIF, http://www.gbif.org) and the Global Genome Biodiversity Network (GGBN, http://www.ggbn.org), in addition to many others, have been working towards standardized access to biological data for many years. Collectively, these biodiversity data management platforms provide a considerable and indispensable infrastructure to the research community. However, cross-linking the massive amounts of protein and DNA sequence data submitted to these databases every year with standardized records of the underlying biological material remains challenging. Best practices for standardized data submissions and data citations are urgently needed. In the long run, two goals should be achieved above all else: all sequence data should be linked to natural history collections, and biological material that was used for molecular research, especially DNA sequencing, should be deposited and, thus, made accessible in public, well curated collections. all sequence data should be linked to natural history collections, and biological material that was used for molecular research, especially DNA sequencing, should be deposited and, thus, made accessible in public, well curated collections. Here we will provide recommendations both for researchers and collections how to cite underlying biological material at INSDC and in publications in a standardized way towards Linked Open Data. We will also address how the global infrastructures and publishers can improve their interoperability.

Tracing the Flow of Genetic Resources in our Collections – How the Nagoya challenge supports the integration of our collection data

Transparency as well as complete and traceable documentation of specimens, samples and associated information are prerequisites to comply with laws and regulations in Provider and User Countries to ensure benefits of utilised genetic resources are shared. Besides legal compliance, these measures should also help to build trust among users, suppliers and collaborators. This concerns for example laws of providing countries that have established access laws under the Nagoya Protocol, such as Mexico's Ley General de la Vida Silvestre, or under the Convention of Biological Diversity (CBD), such as the Brazil Law No. 13,123, regulating access to the country's genetic heritage. On the other hand there are laws and regulations in user countries that ensure compliance with access laws of providing countries under the Nagoya protocol (e. g. Regulation (EU) No 511/2014 of the European Parliament and of the Council of 16. April 2014, which has to be implemented at national level in the EU member states). As an institution holding genetic resources as living collections (including seeds), herbarium specimens and DNA and tissue samples as well as a wealth of associated data, the Botanic Garden and Botanical Museum Berlin (BGBM) aims at creating transparency on the processes associated with the handling of these materials and data, such as metadata or associated analytical research results (Fig. 1). As a member of CETAF (Consortium of European Taxonomic Facilities), IPEN (International Plant Exchange Network), and GGBN (Global Genome Biodiversity Network) the workflows and documentation of biological collections at BGBM are in compliance with CETAF’s Code of Conduct on Access and Benefit Sharing (https://www.cetaf.org/services/natural-science-collections-and-access-and-benefit-sharing) for herbarium specimens including algae, IPEN´s Code of Conduct (http://www.bgci.org/policy/ipen) for living plants and seeds, and GGBN’s (https://library.ggbn.org/share/s/UM5JietQR9aevtYDymHbjw) code of conduct (CoC) for DNA and tissue samples. A major challenge was to ensure the comprehensive, transparent, and traceable documentation of specimens and associated material and information along our internal workflows that have evolved with the development of a manifold of protocols. However, this challenge presented the opportunity to revise the existing protocols that cover the handling, collecting, and processing of the specimens, which had accumulated over the long history of our collections and our databases, into a consistent set of workflows (Stevens et al. 2019). A key component is the Collection Data Form (CDF) which guarantees that all necessary documentation will be imported into our collection management systems, including potential restriction of destructive sampling or loaning. The latest version of the CDF as wells as other information about BGBM’s collection and data workflows can be found at https://wiki.bgbm.org/collectionworkflows. This site has been created in late 2018 to be used by everyone to explore BGBM’s routines and examples. All legal and formal documents, such as collecting permits, Prior Informed Consent (PIC), CITES documentation, phytosanitary documents, Material Transfer Agreement (MTA), long term agreements with partner institutions, project agreements etc., are digitized and managed using a digital asset management software (Alfresco, an open source document management system, www.alfresco.com. The challenge is to link all this information unambiguously. To achieve this, all of BGBM’s collections (tissue and DNA-samples as well as living plants, seeds and diatom cultures) must have, whenever possible, a herbarium specimen that can be permanently stored and that allows a correct taxonomic identification of the material. These voucher specimens shall be digitized. Therefore, all data and all documentation can be traced back to identifiers referring to a herbarium specimen or living accession. The other collections (e. g. DNA and tissue samples) also get unique identifiers that are cross-referenced with each other. By this process we ensure that genetic material is identified by collecting number (assigned by the collector), as well as accession number and barcodes (assigned by BGBM according to type of material such as plant tissue, DNA, sample, seed lot, plant accession number of living plants, environmental sample, culture strain or herbarium specimen), and, most importantly in this regard, the document number/identifier of the legal or formal documents issued by the national legal entity or signed by a partner institution (assigned by the documentation office at BGBM when digitized). All these identifiers or numbers must refer to the respective material and as such allow BGBM to trace back the material at all stages of processing. This is of vital importance when genetic material is exchanged with partners. If there are any restrictions or any requirements for the further processing, use or exchange of plant material this is documented and flagged in all database modules and accession numbers.

An Evolving Business Model for a Biodiversity Biobank Network: GGBN

GGBN, the Global Genome Biodiversity Network, is a consortium of virtually linked biodiversity biobanks that provide unified open access to their sample data through a web portal (www.ggbn.org), together improve best practices and develop standards. Since its inception in 2011, GGBN has largely been supported by external grants and in-kind support from its members. Starting with representatives from thirteen organizations across Africa, Australia, Europe, North, Central, and South America, preliminary plans for an international coordinating mechanism for biodiversity biobanks was developed. In 2013, an interim executive committee was established and an MOU (memorandum of understanding) was distributed to 17 potential collaborators for signature. Subsequently a governance and business model were developed based on input from across the collections and research communities. As the network grew, the interim executive committee solicited letters of intent to transition GGBN into a formal member-driven organization. In 2016 with 12 biodiversity collections online through GGBN’s data portal, the organization was launched and the business model implemented. This included a general and a technical secretariat, an executive committee and general assembly of its, at that time, 41 members. Having grown to encompass 87 general assembly members and 22 collections online in two years, GGBN is assessing its current business model, with focus on increasing revenue, and marketing strategy. Results of this assessment and associated next steps for GGBN are presented and discussed.

Gardens4Science: Setting Up a Trusted Network for German Botanic Gardens Using Open Source Technologies

Botanic gardens are an invaluable refuge for plant diversity for conservation, education and research. Worldwide, they manage over 100,000 species, roughly 30% of all plant species diversity, and over 41% of known threatened species; the botanic gardens in Germany house approximately 50,000 different species (Marquardt et al. in press). Scientists in need of plant material rely upon these resources for their research; they require a pooled, up-to-date inventory of ideally all accessions of these gardens. Sharing data from (living) specimen collections online has become routine in the past years; initiatives like PlantSearch of Botanic Gardens Conservation International and the Global Biodiversity Information Facility (GBIF) allow requesting specimens of interest. However, these catalogues are accessible for everyone. Legitimate concerns about potential theft and legal issues keep curators of living collections from sharing their full catalogues; in most cases, only filtered views of the data will be fed into these networks. Gardens4Science (http://gardens4science.biocase.org) aims at overcoming this issue by creating a trusted network between botanic gardens that allows an unfiltered access on the constituents’ accession catalogues. This unified data pool needs to be automatically synchronized with the individual garden’s catalogues, irrespective of the collection management systems used locally. For the three-year construction phase of Gardens4Science, focus is on Cactaceae and Bromeliaceae, since these families are well-represented in the collections and ideal models for studying the origin of biodiversity on evolutionary time scale. Gardens4Science’s technical architecture (Fig. 1) is based on existing tools for setting up biodiversity networks: The BioCASe (Biological Collections Access Service) Provider Software acts as an interface to the local databases that shields the network from their peculiarities (database management systems and data models used). BioCASe transforms the data into the Access to Biological Collections Data schema (ABCD) and publishes them as a BioCASe-compliant web service (Holetschek and Döring 2008, Holetschek et al. 2012). The data portal is based on portal software from the Global Genome Biodiversity Network and provides a user-specific view on the data. Registered trusted users will be able to display full details of individual accessions, whereas guest users will see only an aggregated view (Droege et al. 2014). The Berlin Indexing and Harvesting Toolkit (B-HIT) is used for harvesting the BioCASe web services of the local catalogues and creating a unified index database (Kelbert et al. 2015). Harvesting is done in regular intervals in order to keep the index in sync with the source databases and does not require any action on the provider’s side. The BioCASe (Biological Collections Access Service) Provider Software acts as an interface to the local databases that shields the network from their peculiarities (database management systems and data models used). BioCASe transforms the data into the Access to Biological Collections Data schema (ABCD) and publishes them as a BioCASe-compliant web service (Holetschek and Döring 2008, Holetschek et al. 2012). The data portal is based on portal software from the Global Genome Biodiversity Network and provides a user-specific view on the data. Registered trusted users will be able to display full details of individual accessions, whereas guest users will see only an aggregated view (Droege et al. 2014). The Berlin Indexing and Harvesting Toolkit (B-HIT) is used for harvesting the BioCASe web services of the local catalogues and creating a unified index database (Kelbert et al. 2015). Harvesting is done in regular intervals in order to keep the index in sync with the source databases and does not require any action on the provider’s side. In addition to harvesting, B-HIT performs several data cleaning steps. Foremost, it reconciles scientific names from the source databases with a taxonomic backbone (currently caryophyllales.org for Cactaceae and the Butcher and Gouda checklist for Bromeliaceae), which allows harmonizing the taxonomies from the different sources and the correction of outdated species names and orthographic mistakes. Provenance information are validated (for example specified geographic coordinates versus country) and corrected, if possible; date values are parsed and converted into a standard format. The issues found and potential corrections are compiled in reports and send to the curators, so the mistakes can be rectified in the source databases. In the construction phase, Gardens4Science consists of seven German Botanic gardens that share their accessions of the Bromeliaceae and Cactaceae families. Up to now (March 2019), 19.539 records have been published in Evo-BoGa, with about 3,500 to be added until the end of the project in January 2020. After the construction phase, it is planned to extend the network to include more Botanic Gardens – both from Germany and other countries – as well as additional plant families.

Luomus’ Genomic Resources Collection Available as Open Data Through FinBIF

There is an increasing demand for high-quality genetic samples for biodiversity research as the techniques are rapidly developing and the costs are decreasing. The Finnish Museum of Natural History Luomus, an independent research institute within the University of Helsinki holding and developing the national natural history collections, has joined the Global Genome Biodiversity Network (GGBN; http://www.ggbn.org/ggbn_portal/) and established a Genomic Resources Collection (GRC) in 2018. In March 2019, the Luomus GRC comprised 2500 DNA extractions and 4000 vertebrate tissue samples amassed in approximately the last 10 years. The DNA extractions are mainly of lichens, polypores, beetles, flies, molluscs and crustaceans of worldwide origin, reflecting the focal organism groups of research groups in Luomus. The deep-frozen tissue samples are mostly of Finnish birds and mammals, as accessions of vertebrate specimens acquired to Luomus’ collections are sampled. High-quality whole-genome DNA extracts will also be prepared. We expect the GRC to increase rapidly in numbers of samples within the coming years. Furthermore, the collection will also serve the many active research groups in the Faculty of Biological and Environmental Sciences of the University of Helsinki. The GRC collection follows the best practices of the Global Genome Biodiversity Network (GGBN) concerning long-term storage and physical quality of samples, and international agreements (the Convention on Biological Diversity, the Nagoya Protocol, CITES) as regards the legitimacy of the samples. The GRC samples are always cross-linked with the taxonomically identified and georeferenced voucher specimen from which it is separated. Each GRC sample gets a Unique Resource Identifier HTTP-URI, which is a derivative of the unique specimen ID used in Luomus’ Collection Management System (CMS) ‘Kotka’. The sample tubes are cryolabelled with the QR code on the lid of the tube. The voucher specimens are deposited in Luomus’ collections or in another international public repository. The data on the GRC samples form part of the Open Data distributed through the Finnish Biodiversity Information Facility FinBIF species.fi (Data policy: https://laji.fi/en/about/960), and will be made searchable at the web portal in 2019. The specific database functions to meet the needs of Luomus’ GRC are developed by Luomus’ Biodiversity Informatics Unit and implemented in Kotka. We have already implemented part of the database tools to manage the compliance with the Nagoya protocol. The tool for registering material transactions (donations / loans) makes use of the Application Programming Interface (API) provided by the Access and Benefit Sharing Clearing House (ABS-CH) and includes links to the ABS-CH webpage (https://absch.cbd.int/). The ABS-CH shows the contact person or organization details of the provider country, and the country-specific requirements for access to genetic resources, when present. The necessary information and documentation (letter of Prior Informed Consent, Mutually Agreed Terms, Material Transaction Agreement, and other permits) are linked from the material transactions to the relevant specimens.