Digital Extended Specimens: Enabling an Extensible Network of Biodiversity Data Records as Integrated Digital Objects on the Internet.

The early twenty-first century has witnessed massive expansions in availability and accessibility of digital data in virtually all domains of the biodiversity sciences. Led by an array of asynchronous digitization activities spanning ecological, environmental, climatological, and biological collections data, these initiatives have resulted in a plethora of mostly disconnected and siloed data, leaving to researchers the tedious and time-consuming manual task of finding and connecting them in usable ways, integrating them into coherent data sets, and making them interoperable. The focus to date has been on elevating analog and physical records to digital replicas in local databases prior to elevating them to ever-growing aggregations of essentially disconnected discipline-specific information. In the present article, we propose a new interconnected network of digital objects on the Internet-the Digital Extended Specimen (DES) network-that transcends existing aggregator technology, augments the DES with third-party data through machine algorithms, and provides a platform for more efficient research and robust interdisciplinary discovery.

Bridging the Research Gap between Live Collections in Zoos and Preserved Collections in Natural History Museums.

Zoos and natural history museums are both collections-based institutions with important missions in biodiversity research and education. Animals in zoos are a repository and living record of the world's biodiversity, whereas natural history museums are a permanent historical record of snapshots of biodiversity in time. Surprisingly, despite significant overlap in institutional missions, formal partnerships between these institution types are infrequent. Life history information, pedigrees, and medical records maintained at zoos should be seen as complementary to historical records of morphology, genetics, and distribution kept at museums. Through examining both institution types, we synthesize the benefits and challenges of cross-institutional exchanges and propose actions to increase the dialog between zoos and museums. With a growing recognition of the importance of collections to the advancement of scientific research and discovery, a transformational impact could be made with long-term investments in connecting the institutions that are caretakers of living and preserved animals.

Machine Learning Using Digitized Herbarium Specimens to Advance Phenological Research.

Machine learning (ML) has great potential to drive scientific discovery by harvesting data from images of herbarium specimens-preserved plant material curated in natural history collections-but ML techniques have only recently been applied to this rich resource. ML has particularly strong prospects for the study of plant phenological events such as growth and reproduction. As a major indicator of climate change, driver of ecological processes, and critical determinant of plant fitness, plant phenology is an important frontier for the application of ML techniques for science and society. In the present article, we describe a generalized, modular ML workflow for extracting phenological data from images of herbarium specimens, and we discuss the advantages, limitations, and potential future improvements of this workflow. Strategic research and investment in specimen-based ML methods, along with the aggregation of herbarium specimen data, may give rise to a better understanding of life on Earth.

Small herbaria contribute unique biogeographic records to county, locality, and temporal scales.

PREMISE: With digitization and data sharing initiatives underway over the last 15 years, an important need has been prioritizing specimens to digitize. Because duplicate specimens are shared among herbaria in exchange and gift programs, we investigated the extent to which unique biogeographic data are held in small herbaria vs. these data being redundant with those held by larger institutions. We evaluated the unique specimen contributions that small herbaria make to biogeographic understanding at county, locality, and temporal scales. METHODS: We sampled herbarium specimens of 40 plant taxa from each of eight states of the United States of America in four broad status categories: extremely rare, very rare, common native, and introduced. We gathered geographic information from specimens held by large (≥100,000 specimens) and small (<100,000 specimens) herbaria. We built generalized linear mixed models to assess which features of the collections may best predict unique contributions of herbaria and used an Akaike information criterion-based information-theoretic approach for our model selection to choose the best model for each scale. RESULTS: Small herbaria contributed unique specimens at all scales in proportion with their contribution of specimens to our data set. The best models for all scales were the full models that included the factors of species status and herbarium size when accounting for state as a random variable. CONCLUSIONS: We demonstrated that small herbaria contribute unique information for research. It is clear that unique contributions cannot be predicted based on herbarium size alone. We must prioritize digitization and data sharing from herbaria of all sizes.

Toward a large-scale and deep phenological stage annotation of herbarium specimens: Case studies from temperate, tropical, and equatorial floras.

PREMISE OF THE STUDY: Phenological annotation models computed on large-scale herbarium data sets were developed and tested in this study. METHODS: Herbarium specimens represent a significant resource with which to study plant phenology. Nevertheless, phenological annotation of herbarium specimens is time-consuming, requires substantial human investment, and is difficult to mobilize at large taxonomic scales. We created and evaluated new methods based on deep learning techniques to automate annotation of phenological stages and tested these methods on four herbarium data sets representing temperate, tropical, and equatorial American floras. RESULTS: Deep learning allowed correct detection of fertile material with an accuracy of 96.3%. Accuracy was slightly decreased for finer-scale information (84.3% for flower and 80.5% for fruit detection). DISCUSSION: The method described has the potential to allow fine-grained phenological annotation of herbarium specimens at large ecological scales. Deeper investigation regarding the taxonomic scalability of this approach is needed.

The history and impact of digitization and digital data mobilization on biodiversity research.

The first two decades of the twenty-first century have seen a rapid rise in the mobilization of digital biodiversity data. This has thrust natural history museums into the forefront of biodiversity research, underscoring their central role in the modern scientific enterprise. The advent of mobilization initiatives such as the United States National Science Foundation's Advancing Digitization of Biodiversity Collections (ADBC), Australia's Atlas of Living Australia (ALA), Mexico's National Commission for the Knowledge and Use of Biodiversity (CONABIO), Brazil's Centro de Referência em Informação (CRIA) and China's National Specimen Information Infrastructure (NSII) has led to a rapid rise in data aggregators and an exponential increase in digital data for scientific research and arguably provide the best evidence of where species live. The international Global Biodiversity Information Facility (GBIF) now serves about 131 million museum specimen records, and Integrated Digitized Biocollections (iDigBio) in the USA has amassed more than 115 million. These resources expose collections to a wider audience of researchers, provide the best biodiversity data in the modern era outside of nature itself and ensure the primacy of specimen-based research. Here, we provide a brief history of worldwide data mobilization, their impact on biodiversity research, challenges for ensuring data quality, their contribution to scientific publications and evidence of the rising profiles of natural history collections.This article is part of the theme issue 'Biological collections for understanding biodiversity in the Anthropocene'.

Use of globally unique identifiers (GUIDs) to link herbarium specimen records to physical specimens.

With the advent of the U.S. National Science Foundation's Advancing Digitization of Biodiversity Collections program and related worldwide digitization initiatives, the rate of herbarium specimen digitization in the United States has expanded exponentially. As the number of electronic herbarium records proliferates, the importance of linking these records to the physical specimens they represent as well as to related records from other sources will intensify. Although a rich and diverse literature has developed over the past decade that addresses the use of specimen identifiers for facilitating linking across the internet, few implementable guidelines or recommended practices for herbaria have been advanced. Here we review this literature with the express purpose of distilling a specific set of recommendations especially tailored to herbarium specimen digitization, curation, and management. We argue that associating globally unique identifiers (GUIDs) with physical herbarium specimens and including these identifiers in all electronic records about those specimens is essential to effective digital data curation. We also address practical applications for ensuring these associations.

Herbarium data: Global biodiversity and societal botanical needs for novel research.

Building on centuries of research based on herbarium specimens gathered through time and around the globe, a new era of discovery, synthesis, and prediction using digitized collections data has begun. This paper provides an overview of how aggregated, open access botanical and associated biological, environmental, and ecological data sets, from genes to the ecosystem, can be used to document the impacts of global change on communities, organisms, and society; predict future impacts; and help to drive the remediation of change. Advocacy for botanical collections and their expansion is needed, including ongoing digitization and online publishing. The addition of non-traditional digitized data fields, user annotation capability, and born-digital field data collection enables the rapid access of rich, digitally available data sets for research, education, informed decision-making, and other scholarly and creative activities. Researchers are receiving enormous benefits from data aggregators including the Global Biodiversity Information Facility (GBIF), Integrated Digitized Biocollections (iDigBio), the Atlas of Living Australia (ALA), and the Biodiversity Heritage Library (BHL), but effective collaboration around data infrastructures is needed when working with large and disparate data sets. Tools for data discovery, visualization, analysis, and skills training are increasingly important for inspiring novel research that improves the intrinsic value of physical and digital botanical collections.

Digitization protocol for scoring reproductive phenology from herbarium specimens of seed plants.

PREMISE OF THE STUDY: Herbarium specimens provide a robust record of historical plant phenology (the timing of seasonal events such as flowering or fruiting). However, the difficulty of aggregating phenological data from specimens arises from a lack of standardized scoring methods and definitions for phenological states across the collections community. METHODS AND RESULTS: To address this problem, we report on a consensus reached by an iDigBio working group of curators, researchers, and data standards experts regarding an efficient scoring protocol and a data-sharing protocol for reproductive traits available from herbarium specimens of seed plants. The phenological data sets generated can be shared via Darwin Core Archives using the Extended MeasurementOrFact extension. CONCLUSIONS: Our hope is that curators and others interested in collecting phenological trait data from specimens will use the recommendations presented here in current and future scoring efforts. New tools for scoring specimens are reviewed.

Old Plants, New Tricks: Phenological Research Using Herbarium Specimens.

The timing of phenological events, such as leaf-out and flowering, strongly influence plant success and their study is vital to understanding how plants will respond to climate change. Phenological research, however, is often limited by the temporal, geographic, or phylogenetic scope of available data. Hundreds of millions of plant specimens in herbaria worldwide offer a potential solution to this problem, especially as digitization efforts drastically improve access to collections. Herbarium specimens represent snapshots of phenological events and have been reliably used to characterize phenological responses to climate. We review the current state of herbarium-based phenological research, identify potential biases and limitations in the collection, digitization, and interpretation of specimen data, and discuss future opportunities for phenological investigations using herbarium specimens.

speciesLink: rich data and novel tools for digital assessments of biodiversity / speciesLink: dados valiosos e ferramentas inovadoras para avaliações digitais da biodiversidade

Abstract speciesLink is a large-scale biodiversity information portal that exists thanks to a broad collaborative network of people and institutions. CRIA's involvement with the scientific community of Brazil and other countries is responsible for the significant results achieved, currently reaching more than 15 million primary biodiversity data records, 95% of which are associated with preserved specimens and about 25% with high-quality digital images. The network provides data on over 200,000 species, of which over 110,000 occur in Brazil. This article describes thematic networks within speciesLink, as well as some of the most useful tools developed. The importance and contributions of speciesLink are outlined, as are concerns about securing stable budgetary support for such biodiversity data e-infrastructures. Here we review the value of speciesLink as a major source of biodiversity information for research, education, informed decision-making, policy development, and bioeconomy.

Resumo speciesLink é um portal de informações em larga escala sobre biodiversidade, que existe graças a uma ampla rede colaborativa de pessoas e instituições. O envolvimento do CRIA com a comunidade científica do Brasil e de outros países é responsável pelos resultados expressivos alcançados, atingindo atualmente mais de 15 milhões de registros de dados primários de biodiversidade, sendo 95% associados a espécimes preservados e cerca de 25% a imagens digitais de alta qualidade. A rede fornece dados sobre mais de 200.000 espécies, das quais mais de 110.000 ocorrem no Brasil. Este artigo descreve as redes temáticas do speciesLink, bem como algumas das ferramentas mais úteis desenvolvidas. A importância e as contribuições do speciesLink são destacadas, assim como as preocupações em garantir um apoio financeiro estável para e-infraestruturas de dados sobre biodiversidade. Aqui revisamos o valor do speciesLink como uma das principais fontes de informação sobre biodiversidade para pesquisa, educação, tomada de decisão, desenvolvimento de políticas e bioeconomia.

Digitization workflows for flat sheets and packets of plants, algae, and fungi.

Effective workflows are essential components in the digitization of biodiversity specimen collections. To date, no comprehensive, community-vetted workflows have been published for digitizing flat sheets and packets of plants, algae, and fungi, even though latest estimates suggest that only 33% of herbarium specimens have been digitally transcribed, 54% of herbaria use a specimen database, and 24% are imaging specimens. In 2012, iDigBio, the U.S. National Science Foundation's (NSF) coordinating center and national resource for the digitization of public, nonfederal U.S. collections, launched several working groups to address this deficiency. Here, we report the development of 14 workflow modules with 7-36 tasks each. These workflows represent the combined work of approximately 35 curators, directors, and collections managers representing more than 30 herbaria, including 15 NSF-supported plant-related Thematic Collections Networks and collaboratives. The workflows are provided for download as Portable Document Format (PDF) and Microsoft Word files. Customization of these workflows for specific institutional implementation is encouraged.

Five task clusters that enable efficient and effective digitization of biological collections.

This paper describes and illustrates five major clusters of related tasks (herein referred to as task clusters) that are common to efficient and effective practices in the digitization of biological specimen data and media. Examples of these clusters come from the observation of diverse digitization processes. The staff of iDigBio (The U.S. National Science Foundation's National Resource for Advancing Digitization of Biological Collections) visited active biological and paleontological collections digitization programs for the purpose of documenting and assessing current digitization practices and tools. These observations identified five task clusters that comprise the digitization process leading up to data publication: (1) pre-digitization curation and staging, (2) specimen image capture, (3) specimen image processing, (4) electronic data capture, and (5) georeferencing locality descriptions. While not all institutions are completing each of these task clusters for each specimen, these clusters describe a composite picture of digitization of biological and paleontological specimens across the programs that were observed. We describe these clusters, three workflow patterns that dominate the implemention of these clusters, and offer a set of workflow recommendations for digitization programs.