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 Join the Dots: Adding collection assessment to collection descriptions

2019 ◽  
Vol 3 ◽  
Author(s):  
Matt Woodburn ◽  
Sarah Vincent ◽  
Helen Hardy ◽  
Clare Valentine
Keyword(s):  
Natural History ◽  
Use Cases ◽  
Global Biodiversity Information Facility ◽  
Reference Case ◽  
Major Barrier ◽  
Data Standard ◽  
Time Investment ◽  
Description Framework ◽  
The Impact ◽  
Biodiversity Information

The natural science collections community has identified an increasing need for shared, structured and interoperable data standards that can be used to describe the totality of institutional collection holdings, whether digitised or not. Major international initiatives - including the Global Biodiversity Information Facility (GBIF), the Distributed System of Scientific Collections (DiSSCo) and the Consortium of European Taxonomic Facilities (CETAF) - consider the current lack of standards to be a major barrier, which must be overcome to further their strategic aims and contribute to an open, discoverable catalogue of global collections. The Biodiversity Information Standards (TDWG) Collection Descriptions (CD) group is looking to address this issue with a new data standard for collection descriptions. At an institutional level, this concept of collection descriptions aligns strongly with the need to use a structured and more data-driven approach to assessing and working with collections, both to identify and prioritise investment and effort, and to monitor the impact of the work. Use cases include planning conservation and collection moves, prioritising specimen digitisation activities, and informing collection development strategy. The data can be integrated with the collection description framework for ongoing assessments of the state of the collection. This approach was pioneered with the ‘Move the Dots’ methodology by the Smithsonian National Museum of Natural History, started in 2009 and run annually since. The collection is broken down into several hundred discrete subcollections, for each of which the number of objects was estimated and a numeric rank allocated according to a range of assessment criteria. This method has since been adopted by several other institutions, including Naturalis Biodiversity Centre, Museum für Naturkunde and Natural History Museum, London (NHM). First piloted in 2016, and now implemented as a core framework, the NHM’s adaptation, ‘Join the Dots’, divides the collection into approximately 2,600 ‘collection units’. The breakdown uses formal controlled lists and hierarchies, primarily taxonomy, type of object, storage location and (where relevant) stratigraphy, which are mapped to external authorities such as the Catalogue of Life and Paleobiology Database. The collection breakdown is enhanced with estimations of number of items, and ranks from 1 to 5 for each collection unit against 17 different criteria. These are grouped into four categories of ‘Condition’, ‘Information’ (including digital records), ‘Importance and Significance’ and ‘Outreach’. Although requiring significant time investment from collections staff to provide the estimates and assessments, this methodology has yielded a rich dataset that supports both discoverability (collection descriptions) and management (collection assessment). Links to further datasets about the building infrastructure and environmental conditions also make it into a powerful resource for planning activities such as collections moves, pest monitoring and building work. We have developed dynamic dashboards to provide rich visualisations for exploring, analysing and communicating the data. As an ongoing, embedded activity for collections staff, there will also be a build-up of historical data going forward, enabling us to see trends, track changes to the collection, and measure the impact of projects and events. The concept of Join the Dots also offers a generic, institution-agnostic model for enhancing the collection description framework with additional metrics that add value for strategic management and resourcing of the collection. In the design and implementation, we’ve faced challenges that should be highly relevant to the TDWG CD group, such as managing the dynamic breakdown of collections across multiple dimensions. We also face some that are yet to be resolved, such as a robust model for managing the evolving dataset over time. We intend to contribute these use cases into the development of the new TDWG data standard and be an early adopter and reference case. We envisage that this could constitute a common model that, where resources are available, provides the ability to add greater depth and utility to the world catalogue of collections.

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

2019 ◽  
Vol 3 ◽  
Author(s):  
Ole Seberg ◽  
Gabriele Droege ◽  
Jonas Astrin ◽  
Katharine Barker ◽  
Jonathan Coddington
Keyword(s):  
Best Practices ◽  
Global Scale ◽  
Network Activity ◽  
Benefit Sharing ◽  
Access And Benefit Sharing ◽  
Culture Collections ◽  
Related Information ◽  
Secure Interoperability ◽  
Key Aspects ◽  
The Eu

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+.

scholarly journals A Data Standard for Dynamic Collection Descriptions

2021 ◽  
Vol 5 ◽  
Author(s):  
Matt Woodburn ◽  
Gabriele Droege ◽  
Sharon Grant ◽  
Quentin Groom ◽  
Janeen Jones ◽  
...  
Keyword(s):  
Natural Science ◽  
Data Model ◽  
Use Cases ◽  
Use Case ◽  
Global Biodiversity Information Facility ◽  
Controlled Vocabularies ◽  
Data Standard ◽  
Wide Range ◽  
Scientific Collections ◽  
Biodiversity Information

The utopian vision is of a future where a digital representation of each object in our collections is accessible through the internet and sustainably linked to other digital resources. This is a long term goal however, and in the meantime there is an urgent need to share data about our collections at a higher level with a range of stakeholders (Woodburn et al. 2020). To sustainably achieve this, and to aggregate this information across all natural science collections, the data need to be standardised (Johnston and Robinson 2002). To this end, the Biodiversity Information Standards (TDWG) Collection Descriptions (CD) Interest Group has developed a data standard for describing collections, which is approaching formal review for ratification as a new TDWG standard. It proposes 20 classes (Suppl. material 1) and over 100 properties that can be used to describe, categorise, quantify, link and track digital representations of natural science collections, from high-level approximations to detailed breakdowns depending on the purpose of a particular implementation. The wide range of use cases identified for representing collection description data means that a flexible approach to the standard and the underlying modelling concepts is essential. These are centered around the ‘ObjectGroup’ (Fig. 1), a class that may represent any group (of any size) of physical collection objects, which have one or more common characteristics. This generic definition of the ‘collection’ in ‘collection descriptions’ is an important factor in making the standard flexible enough to support the breadth of use cases. For any use case or implementation, only a subset of classes and properties within the standard are likely to be relevant. In some cases, this subset may have little overlap with those selected for other use cases. This additional need for flexibility means that very few classes and properties, representing the core concepts, are proposed to be mandatory. Metrics, facts and narratives are represented in a normalised structure using an extended MeasurementOrFact class, so that these can be user-defined rather than constrained to a set identified by the standard. Finally, rather than a rigid underlying data model as part of the normative standard, documentation will be developed to provide guidance on how the classes in the standard may be related and quantified according to relational, dimensional and graph-like models. So, in summary, the standard has, by design, been made flexible enough to be used in a number of different ways. The corresponding risk is that it could be used in ways that may not deliver what is needed in terms of outputs, manageability and interoperability with other resources of collection-level or object-level data. To mitigate this, it is key for any new implementer of the standard to establish how it should be used in that particular instance, and define any necessary constraints within the wider scope of the standard and model. This is the concept of the ‘collection description scheme,’ a profile that defines elements such as: which classes and properties should be included, which should be mandatory, and which should be repeatable; which controlled vocabularies and hierarchies should be used to make the data interoperable; how the collections should be broken down into individual ObjectGroups and interlinked, and how the various classes should be related to each other. which classes and properties should be included, which should be mandatory, and which should be repeatable; which controlled vocabularies and hierarchies should be used to make the data interoperable; how the collections should be broken down into individual ObjectGroups and interlinked, and how the various classes should be related to each other. Various factors might influence these decisions, including the types of information that are relevant to the use case, whether quantitative metrics need to be captured and aggregated across collection descriptions, and how many resources can be dedicated to amassing and maintaining the data. This process has particular relevance to the Distributed System of Scientific Collections (DiSSCo) consortium, the design of which incorporates use cases for storing, interlinking and reporting on the collections of its member institutions. These include helping users of the European Loans and Visits System (ELViS) (Islam 2020) to discover specimens for physical and digital loans by providing descriptions and breakdowns of the collections of holding institutions, and monitoring digitisation progress across European collections through a dynamic Collections Digitisation Dashboard. In addition, DiSSCo will be part of a global collections data ecosystem requiring interoperation with other infrastructures such as the GBIF (Global Biodiversity Information Facility) Registry of Scientific Collections, the CETAF (Consortium of European Taxonomic Facilities) Registry of Collections and Index Herbariorum. In this presentation, we will introduce the draft standard and discuss the process of defining new collection description schemes using the standard and data model, and focus on DiSSCo requirements as examples of real-world collection descriptions use cases.

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 Unity in Variety: Developing a collection description standard by consensus

2020 ◽  
Vol 4 ◽  
Author(s):  
Matt Woodburn ◽  
Deborah L Paul ◽  
Wouter Addink ◽  
Steven J Baskauf ◽  
Stanley Blum ◽  
...  
Keyword(s):  
Natural History ◽  
Data Model ◽  
Quantitative Data ◽  
Geographic Origin ◽  
Task Group ◽  
Data Standard ◽  
Address Data ◽  
Object Group ◽  
Global Registry ◽  
Biodiversity Information

Digitisation and publication of museum specimen data is happening worldwide, but far from complete. Museums can start by sharing what they know about their holdings at a higher level, long before each object has its own record. Information about what is held in collections worldwide is needed by many stakeholders including collections managers, funders, researchers, policy-makers, industry, and educators. To aggregate this information from collections, the data need to be standardised (Johnston and Robinson 2002). So, the Biodiversity Information Standards (TDWG) Collection Descriptions (CD) Task Group is developing a data standard for describing collections, which gives the ability to provide: automated metrics, using standardised collection descriptions and/or data derived from specimen datasets (e.g., counts of specimens) and a global registry of physical collections (i.e., digitised or non-digitised). automated metrics, using standardised collection descriptions and/or data derived from specimen datasets (e.g., counts of specimens) and a global registry of physical collections (i.e., digitised or non-digitised). Outputs will include a data model to underpin the new standard, and guidance and reference implementations for the practical use of the standard in institutional and collaborative data infrastructures. The Task Group employs a community-driven approach to standard development. With international participation, workshops at the Natural History Museum (London 2019) and the MOBILISE workshop (Warsaw 2020) allowed over 50 people to contribute this work. Our group organized online "barbecues" (BBQs) so that many more could contribute to standard definitions and address data model design challenges. Cloud-based tools (e.g., GitHub, Google Sheets) are used to organise and publish the group's work and make it easy to participate. A Wikibase instance is also used to test and demonstrate the model using real data. There are a range of global, regional, and national initiatives interested in the standard (see Task Group charter). Some, like GRSciColl (now at the Global Biodiversity Information Facility (GBIF)), Index Herbariorum (IH), and the iDigBio US Collections List are existing catalogues. Others, including the Consortium of European Taxonomic Facilities (CETAF) and the Distributed System of Scientific Collections (DiSSCo), include collection descriptions as a key part of their near-term development plans. As part of the EU-funded SYNTHESYS+ project, GBIF organized a virtual workshop: Advancing the Catalogue of the World's Natural History Collections to get international input for such a resource that would use this CD standard. Some major complexities present themselves in designing a standardised approach to represent collection descriptions data. It is not the first time that the natural science collections community has tried to address them (see the TDWG Natural Collections Description standard). Beyond natural sciences, the library community in particular gave thought to this (Heaney 2001, Johnston and Robinson 2002), noting significant difficulties. One hurdle is that collections may be broken down into different degrees of granularity according to different criteria, and may also overlap so that a single object can be represented in more than one collection description. Managing statistics such as numbers of objects is complex due to data gaps and variable degrees of certainty about collection contents. It also takes considerable effort from collections staff to generate structured data about their undigitised holdings. We need to support simple, high-level collection summaries as well as detailed quantitative data, and to be able to update as needed. We need a simple approach, but one that can also handle the complexities of data, scope, and social needs, for digitised and undigitised collections. The data standard itself is a defined set of classes and properties that can be used to represent groups of collection objects and their associated information. These incorporate common characteristics ('dimensions') by which we want to describe, group and break down our collections, metrics for quantifying those collections, and properties such as persistent identifiers for tracking collections and managing their digital counterparts. Existing terms from other standards (e.g. Darwin Core, ABCD) are re-used if possible. The data model (Fig. 1) underpinning the standard defines the relationships between those different classes, and ensures that the structure as well as the content are comparable across different datasets. It centres around the core concept of an 'object group', representing a set of physical objects that is defined by one or more dimensions (e.g., taxonomy and geographic origin), and linked to other entities such as the holding institution. To the object group, quantitative data about its contents are attached (e.g. counts of objects or taxa), along with more qualitative information describing the contents of the group as a whole. In this presentation, we will describe the draft standard and data model with examples of early adoption for real-world and example data. We will also discuss the vision of how the new standard may be adopted and its potential impact on collection discoverability across the collections community.

scholarly journals Unlocking the Entomological Collection of the Natural History Museum of Maputo, Mozambique

2021 ◽  
Vol 9 ◽  
Author(s):  
Domingos Sandramo ◽  
Enrico Nicosia ◽  
Silvio Cianciullo ◽  
Bernardo Muatinte ◽  
Almeida Guissamulo
Keyword(s):  
Natural History ◽  
Crucial Role ◽  
Development Programme ◽  
Natural History Museum ◽  
Biodiversity Data ◽  
Global Biodiversity Information Facility ◽  
History Museum ◽  
Data Portal ◽  
Global Biodiversity ◽  
Biodiversity Information

The collections of the Natural History Museum of Maputo have a crucial role in the safeguarding of Mozambique's biodiversity, representing an important repository of data and materials regarding the natural heritage of the country. In this paper, a dataset is described, based on the Museum’s Entomological Collection recording 409 species belonging to seven orders and 48 families. Each specimen’s available data, such as geographical coordinates and taxonomic information, have been digitised to build the dataset. The specimens included in the dataset were obtained between 1914–2018 by collectors and researchers from the Natural History Museum of Maputo (once known as “Museu Alváro de Castro”) in all the country’s provinces, with the exception of Cabo Delgado Province. This paper adds data to the Biodiversity Network of Mozambique and the Global Biodiversity Information Facility, within the objectives of the SECOSUD II Project and the Biodiversity Information for Development Programme. The aforementioned insect dataset is available on the GBIF Engine data portal (https://doi.org/10.15468/j8ikhb). Data were also shared on the Mozambican national portal of biodiversity data BioNoMo (https://bionomo.openscidata.org), developed by SECOSUD II Project.

scholarly journals FinBIF: An all-embracing, integrated, cross-sectoral biodiversity data infrastructure

2019 ◽  
Vol 3 ◽  
Author(s):  
Leif Schulman ◽  
Aino Juslén ◽  
Kari Lahti
Keyword(s):  
Natural History ◽  
Data Management ◽  
Species Identification ◽  
Large Scale ◽  
Dna Barcode ◽  
National Research Council ◽  
Observation Data ◽  
Biodiversity Data ◽  
Research Infrastructures ◽  
Biodiversity Information

The service model of the Global Biodiversity Information Facility (GBIF) is being implemented in an increasing number of national biodiversity (BD) data services. While GBIF already shares >109 data points, national initiatives are an essential component: increase in GBIF-mediated data relies on national data mobilisation and GBIF is not optimised to support local use. The Finnish Biodiversity Information Facility (FinBIF), initiated in 2012 and operational since late 2016, is one of the more recent examples of national BD research infrastructures (RIs) – and arguably among the most comprehensive. Here, we describe FinBIF’s development and service integration, and provide a model approach for the construction of all-inclusive national BD RIs. FinBIF integrates a wide array of BD RI approaches under the same umbrella. These include large-scale and multi-technology digitisation of natural history collections; building a national DNA barcode reference library and linking it to species occurrence data; citizen science platforms enabling recording, managing and sharing of observation data; management and sharing of restricted data among authorities; community-driven species identification support; an e-learning environment for species identification; and IUCN Red Listing (Fig. 1). FinBIF’s aims are to accelerate digitisation, mobilisation, and distribution of biodiversity data and to boost their use in research and education, environmental administration, and the private sector. The core functionalities of FinBIF were built in a 3.5-year project (01/2015–06/2018) by a consortium of four university-based natural history collection facilities led by the Finnish Museum of Natural History Luomus. Close to 30% of the total funding was granted through the Finnish Research Infrastructures programme (FIRI) governed by the national research council and based on scientific excellence. Government funds for productivity enhancement in state administration covered c.40 % of the development and the rest was self-financed by the implementing consortium of organisations that have both a research and an education mission. The cross-sectoral scope of FinBIF has led to rapid uptake and a broad user base of its functionalities and services. Not only researchers but also administrative authorities, various enterprises and a large number of private citizens show a significant interest in the RI (Table 1). FinBIF is now in its second construction cycle (2019–2022), funded through the FIRI programme and, thus, focused on researcher services. The work programme includes integration of tools for data management in ecological restoration and e-Lab tools for spatial analyses, morphometric analysis of 3D images, species identification from sound recordings, and metagenomics analyses.

scholarly journals New ECCO model documents for Material Deposit and Transfer Agreements in compliance with the Nagoya Protocol

2020 ◽  
Vol 367 (5) ◽  
Author(s):  
Gerard Verkley ◽  
Giancarlo Perrone ◽  
Mery Piña ◽  
Amber Hartman Scholz ◽  
Jörg Overmann ◽  
...  
Keyword(s):  
Code Of Conduct ◽  
Relevant Information ◽  
Culture Collection ◽  
Benefit Sharing ◽  
Microbial Culture ◽  
Material Transfer ◽  
Access And Benefit Sharing ◽  
Culture Collections ◽  
Material Transfer Agreement ◽  
The Status

ABSTRACT The European Culture Collections’ Organisation presents two new model documents for Material Deposit Agreement (MDA) and Material Transfer Agreement (MTA) designed to enable microbial culture collection leaders to draft appropriate agreement documents for, respectively, deposit and supply of materials from a public collection. These tools provide guidance to collections seeking to draft an MDA and MTA, and are available in open access to be used, modified, and shared. The MDA model consists of a set of core fields typically included in a ‘deposit form’ to collect relevant information to facilitate assessment of the status of the material under access and benefit sharing (ABS) legislation. It also includes a set of exemplary clauses to be included in ‘terms and conditions of use’ for culture collection management and third parties. The MTA model addresses key issues including intellectual property rights, quality, safety, security and traceability. Reference is made to other important tools such as best practices and code of conduct related to ABS issues. Besides public collections, the MDA and MTA model documents can also be useful for individual researchers and microbial laboratories that collect or receive microbial cultures, keep a working collection, and wish to share their material with others.

scholarly journals Data Attribution from Download to Publication

2018 ◽  
Vol 2 ◽  
pp. e26060
Author(s):  
Pamela Soltis
Keyword(s):  
Natural History ◽  
Large Scale ◽  
Sequence Data ◽  
Research Process ◽  
Global Biodiversity Information Facility ◽  
Data Set ◽  
Dna Sequence Data ◽  
Large Scale Data ◽  
Data Tracking ◽  
Biodiversity Information

Digitized natural history data are enabling a broad range of innovative studies of biodiversity. Large-scale data aggregators such as Global Biodiversity Information facility (GBIF) and Integrated Digitized Biocollections (iDigBio) provide easy, global access to millions of specimen records contributed by thousands of collections. A developing community of eager users of specimen data – whether locality, image, trait, etc. – is perhaps unaware of the effort and resources required to curate specimens, digitize information, capture images, mobilize records, serve the data, and maintain the infrastructure (human and cyber) to support all of these activities. Tracking of specimen information throughout the research process is needed to provide appropriate attribution to the institutions and staff that have supplied and served the records. Such tracking may also allow for annotation and comment on particular records or collections by the global community. Detailed data tracking is also required for open, reproducible science. Despite growing recognition of the value and need for thorough data tracking, both technical and sociological challenges continue to impede progress. In this talk, I will present a brief vision of how application of a DOI to each iteration of a data set in a typical research project could provide attribution to the provider, opportunity for comment and annotation of records, and the foundation for reproducible science based on natural history specimen records. Sociological change – such as journal requirements for data deposition of all iterations of a data set – can be accomplished using community meetings and workshops, along with editorial efforts, as were applied to DNA sequence data two decades ago.

scholarly journals Describing Living Collections and Specimens 

2021 ◽  
Vol 5 ◽  
Author(s):  
Patricia Mergen ◽  
Maarten Trekels ◽  
Frederik Leliaert ◽  
Matt Woodburn ◽  
Gabriele Droege ◽  
...  
Keyword(s):  
Natural History ◽  
Best Practices ◽  
Group Living ◽  
World Federation ◽  
Culture Collections ◽  
Controlled Vocabularies ◽  
Cost Action ◽  
Botanical Gardens ◽  
Natural History Collections ◽  
Voucher Specimens

Many institutions harbor living collections in the form of living plants, animals, microrganisms or seeds. In the framework of the TDWG collections and specimen descriptions standards, it has become important to align exisiting standards for living collections and specimens or to identify where concepts or controlled vocabularies would be needed in the current TDWG standards. In September 2021 a workshop was organized in the framework of the COST Action Mobilise (https://www.mobilise-action.eu/) to get a better common understanding of the different types of living collections to consider and set the scene for further work on standards alignments. The EU COST Action CA17106 on “Mobilising Data, Experts and Policies in Scientific Collections”. Invited experts to these workshop were representatives of the TDWG Collection Description Group, the GGBN and TDWG molecular collections group, living plants collections and seed banks (Botanic Gardens Conservation International: BGCI, https://www.bgci.org/), living animal and biobanks (European Association of Zoos and Aquaria: EAZA, https://www.eaza.net/) and the culture collections (World Federation for Culture Collections: WFCC, http://www.wfcc.info/), who gave presentations on their currently used standards and challenges. The second day was devoted to break out sessions to brainstorm the specific needs for the different living collections with the aim to check and update the controlled vocabularies and concepts as needed. Identified topics were : Session 1: Voucher specimens of living accessions. Session 2: Living collections and GBIF. Session 3: How do we compare botanical gardens with herbaria? Session 4: How do we compare zoos and aquaria with natural history collections? Session 5: Culture collections: best practices and guidelines. Session 1: Voucher specimens of living accessions. Session 2: Living collections and GBIF. Session 3: How do we compare botanical gardens with herbaria? Session 4: How do we compare zoos and aquaria with natural history collections? Session 5: Culture collections: best practices and guidelines. The goal of this presentation is to address the outcome of these sessions and recommend future steps in collaboration with TDWG and the different identified stakeholders.

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