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 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 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 Creating a National Biodiversity Database in Gabon and the Challenges of Mobilizing Natural History Data for Francophone Countries

2021 ◽  
Vol 5 ◽  
Author(s):  
Elie Tobi ◽  
Geovanne Aymar Nziengui Djiembi ◽  
Anna Feistner ◽  
Donald Midoko Iponga ◽  
Jean Felicien Liwouwou ◽  
...  
Keyword(s):  
Natural History ◽  
Spoken Language ◽  
Decision Makers ◽  
Global Biodiversity Information Facility ◽  
Major Barrier ◽  
French Speaking ◽  
Collection Data ◽  
Biodiversity Database ◽  
Biodiversity Information ◽  
Different Parts

Language is a major barrier for researchers wanting to digitize and publish collection data in Africa. Despite being the fifth most spoken language on Earth and the second most common in Africa, resources in French about digitization, data management, and publishing are lacking. Furthermore, French-speaking regions of Africa (primarily Central/West Africa and Madagascar) host some of the highest biodiversity on the continent and therefore are of great importance to scientists and decision-makers. Without having representation in online portals like the Global Biodiversity Information Facility (GBIF) and Integrated Digitized Biocollections (iDigBio), these important collections are effectively invisible. Producing relevant/applicable resources about digitization in French will help shine a light on these valuable natural history records and allow the data-holders in Africa to retain the autonomy of their collections. Awarded a GBIF-BID (Biodiversity Information for Development) grant in 2021, an international, multilingual network of partners has undertaken the important task of digitizing and mobilizing Gabon’s vertebrate collections. There are an estimated 13,500 vertebrate specimens housed in five institutions in different parts of Gabon. To date, the group has mobilized >4,600 vertebrate records to our recently launched Gabon Biodiversity Portal (https://gabonbiota.org/). The portal also hosts French guides for using Symbiota-based portals to manage, georeference, and publish natural history databases. These resources can provide much-needed guidance for other Francophone countries⁠—in Africa and beyond⁠—working to maximize the accessibility and value of their biodiversity collections.

scholarly journals Mobilizing Data from Taxonomic Literature for an Iconic Species (Dinosauria, Theropoda, Tyrannosaurus rex)

2019 ◽  
Vol 3 ◽  
Author(s):  
Jeremy Miller ◽  
Yanell Braumuller ◽  
Puneet Kishor ◽  
David Shorthouse ◽  
Mariya Dimitrova ◽  
...  
Keyword(s):  
Global Biodiversity Information Facility ◽  
Museum Exhibits ◽  
The Public ◽  
The Past ◽  
Biodiversity Knowledge ◽  
Informatics Infrastructure ◽  
The Subject ◽  
The Impact ◽  
Biodiversity Information ◽  
Occurrence Records

A vast amount of biodiversity data is reported in the primary taxonomic literature. In the past, we have demonstrated the use of semantic enhancement to extract data from taxonomic literature and make it available to a network of databases (Miller et al. 2015). For technical reasons, semantic enhancement of taxonomic literature is most efficient when customized according to the format of a particular journal. This journal-based approach captures and disseminates data on whatever taxa happen to be published therein. But if we want to extract all treatments on a particular taxon of interest, these are likely to be spread across multiple journals. Fortunately, the GoldenGATE Imagine document editor (Sautter 2019) is flexible enough to parse most taxonomic literature. Tyrannosaurus rex is an iconic dinosaur with broad public appeal, as well as the subject of more than a century of scholarship. The Naturalis Biodiversity Center recently acquired a specimen that has become a major attraction in the public exhibit space. For most species on earth, the primary taxonomic literature contains nearly everything that is known about it. Every described species on earth is the subject of one or more taxonomic treatments. A taxon-based approach to semantic enhancement can mobilize all this knowledge using the network of databases and resources that comprise the modern biodiversity informatics infrastructure. When a particular species is of special interest, a taxon-based approach to semantic enhancement can be a powerful tool for scholarship and communication. In light of this, we resolved to semantically enhance all taxonomic treatments on T. rex. Our objective was to make these treatments and associated data available for the broad range of stakeholders who might have an interest in this animal, including professional paleontologists, the curious public, and museum exhibits and public communications personnel. Among the routine parsing and data sharing activities in the Plazi workflow (Agosti and Egloff 2009), taxonomic treatments, as well as cited figures, are deposited in the Biodiversity Literature Repository (BLR), and occurrence records are shared with the Global Biodiversity Information Facility (GBIF). Treatment citations were enhanced with hyperlinks to the cited treatment on TreatmentBank, and specimen citations were linked to their entries on public facing collections databases. We used the OpenBiodiv biodiversity knowledge graph (Senderov et al. 2017) to discover other taxa mentioned together with T. rex, and to create a timeline of T. rex research to evaluate the impact of individual researchers and specimen repositories to T. rex research. We contributed treatment links to WikiData, and queried WikiData to discover identifiers to different platforms holding data about T. rex. We used bloodhound-tracker.net to disambiguate human agents, like collectors, identifiers, and authors. We evaluate the adequacy of the fields currently available to extract data from taxonomic treatments, and make recommendations for future standards.

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 Quantifying Institutional Reach Through the Human Network in Natural History Collections

2019 ◽  
Vol 3 ◽  
Author(s):  
David Shorthouse ◽  
Roderic Page
Keyword(s):  
Natural History ◽  
Professional Relationships ◽  
Global Biodiversity Information Facility ◽  
Closed Loops ◽  
Natural History Collections ◽  
Darwin Core ◽  
International Audience ◽  
The Impact ◽  
To Receive ◽  
Formal Recognition

Through the Bloodhound proof-of-concept, https://bloodhound-tracker.net an international audience of collectors and determiners of natural history specimens are engaged in the emotive act of claiming their specimens and attributing other specimens to living and deceased mentors and colleagues. Behind the scenes, these claims build links between Open Researcher and Contributor Identifiers (ORCID, https://orcid.org) or Wikidata identifiers for people and Global Biodiversity Information Facility (GBIF) specimen identifiers, predicated by the Darwin Core terms, recordedBy (collected) and identifiedBy (determined). Here we additionally describe the socio-technical challenge in unequivocally resolving people names in legacy specimen data and propose lightweight and reusable solutions. The unique identifiers for the affiliations of active researchers are obtained from ORCID whereas the unique identifiers for institutions where specimens are actively curated are resolved through Wikidata. By constructing closed loops of links between person, specimen, and institution, an interesting suite of potential metrics emerges, all due to the activities of employees and their network of professional relationships. This approach balances a desire for individuals to receive formal recognition for their efforts in natural history collections with that of an institutional-level need to alter budgets in response to easily obtained numeric trends in national and international reach. If handled in a coordinating fashion, this reporting technique may be a significant new driver for specimen digitization efforts on par with Altmetric, https://www.altmetric.com, an important new tool that tracks the impact of publications and delights administrators and authors alike.

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 Digitizing Primary Data on Biodiversity to Protect Natural History Collections Against Catastrophic Events: The type material of dragonflies (Insecta: Odonata) from Museu Nacional of Brazil

2021 ◽  
Vol 5 ◽  
Author(s):  
Marcus De Almeida ◽  
Ângelo Pinto ◽  
Alcimar Carvalho
Keyword(s):  
Natural History ◽  
Natural World ◽  
Type Material ◽  
Primary Data ◽  
Future Research ◽  
Catastrophic Events ◽  
Type Specimens ◽  
Global Biodiversity Information Facility ◽  
Natural History Collections ◽  
The Impact

Natural history collections (NHC) are guardians of biodiversity (Lane 1996) and essential to understand the natural world and its evolutionary processes. They hold samples of morphological and genetic heritages of living and extinct biotas, helping to reconstruct the timeline of life over the centuries (Gardner 2014). Primary data from specimens in NHC are crucial elements for research in many areas of biological sciences, considered the “bricks” of systematics and therefore one of the pillars for evolutionary studies (Troudet 2018). For this reason, studies carried out in NHC are essential for the development of the scientific knowledge and are pivotal for the scientific-technological progress of a nation (Camargo 2015). The digitization and availability of primary data on biodiversity from NHC represents a inexpensive, practical and secure means of exchanging information, allowing collaboration between institutions and researchers. In this sense, initiatives such as the Sistema de Informação sobre a Biodiversidade Brasileira (SiBBr), a country-level branch of the Global Biodiversity Information Facility (GBIF) platform, aim to encourage and establish ways for the informatization of biological collections and their type specimens. Known for housing one of the largest and oldest collections of insects in the world focused on Neotropical fauna, the Entomological Collection of the Museu Nacional of Federal University of Rio de Janeiro (MNRJ) had more than 3,000 primary types and approximately 12,005,000 specimens, of which about 96% were lost in the tragic fire occurred at the institution on September 2, 2018. The SiBBr project was active in that collection from 2016 to 2019 and enabled the digitization and preservation of data from the type material of many insect orders, including the charismatic dragonflies (order Odonata). Due to the end of the agreement between SiBBr and the Museu Nacional, most of the obtained primary data are pending full curation and, therefore, are not yet available to the public and researchers. The MNRJ housed the biggest and most important collection of dragonflies among all Central and South American institutions. It assembled most of the physical records of neotropical dragonfly fauna gathered over the last 80 years, many of which are of undescribed taxa. Unfortunately, almost all material was permanently lost. This study aims to gather, analyze and publicize primary data of the type material of dragonflies housed in the MNRJ, ensuring the preservation of its history, as well as providing data on the taxonomy and diversity of this marvelous group of insects. A total of 11 families, 50 genera and 131 species were recorded, belonging to the suborders Anisoptera and Zygoptera with distributional records widespread in South America. The MNRJ housed 105 holotypes of dragonflies' nomina representing 11.7% of the richness of the Brazilian Odonata fauna (901 spp.), a country with the highest number of species of the biosphere. The impact of the loss of this collection to studies of these insects is unprecedented, since some enigmatic and monotypic genera such as Brasiliogomphus, Fluminagrion and Roppaneura lost 100% of their type series, while others most diverse such as Lauromacromia, Oxyagrion and Neocordulia lost 50%, 35% and 31% of their holotypes. Therefore, due to the registration and preservation of primary biodiversity data, this work reiterates the importance of curating and digitizing biological scientific collections. Furthermore, it shows extreme relevance for preserving information on existing biodiversity permanently and providing support for future research. Digitization and interconnecting digital extended specimen data proves to be one of the main and most effective ways to protect NHC heritage and their primary data against catastrophic events.

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 The European Journal of Taxonomy: Enhancing taxonomic publications for dynamic data exchange and navigation

2019 ◽  
Vol 3 ◽  
Author(s):  
Laurence Bénichou ◽  
Isabelle Gerard ◽  
Chloé Chester ◽  
Donat Agosti
Keyword(s):  
Natural History ◽  
Data Exchange ◽  
State Of The Art ◽  
Global Biodiversity Information Facility ◽  
Set Up ◽  
Semantic Markup ◽  
Pdf Format ◽  
Text And Data Mining ◽  
Biodiversity Information ◽  
Publishing Workflow

The European Journal of Taxonomy (EJT) was initiated by a consortium of European natural history publishers to take advantage of the shift from paper to electronic-only publishing (Benichou et al. 2011). Whilst originally publishing in PDF format has been considered the state of the art, it became recently obvious that complementary dissemination channels help to disseminate taxonomic data - one of the pillars of Natural History institutions research - more widely and efficiently (Côtez et al. 2018). The adoption of semantic markup and assignment of persistent identifiers for content allow more comprehensive citations of the article, including elements therein, such as images, taxonomic treatments, and materials citation. It also allows more in-depth analyses and visualization of the contribution of collections, authors, or specimens to taxonomic output and third parties, such as the Global Biodiversity Information Facility, for reuse of the data or building the catalogue of life. In this presentation, EJT will be used to outline the nature of natural history publishers and their technical set up. This is followed by a description of the post-publishing workflow using the Plazi workflow and dissemination via the Biodiversity Literature Repository (BLR) and TreatmentBank. It outlines switching the publishing workflow to an increased use of extended markup language (XML) and visualization of the output and concludes by publishing guidelines that enable more efficient text and data mining of the content of taxonomic publications.

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