For more than two centuries, biodiversity collections have served as the foundation
for scientific investigation of and education about life on Earth (Melber and Abraham
2002, Cook et al. 2014, Funk 2018). The collections that have been assembled in the
past and continue to grow today are a cornerstone of our national heritage that have
been treated as such since the founding of the United States (e.g., Jefferson 1799,
Goode 1901a, 1901b, Meisel 1926). A diverse array of institutions throughout the United
States, from museums and botanical gardens to universities and government agencies,
maintain our biodiversity collections as part of their research and education missions.
Collectively, these institutions and their staff are stewards for at least 1 billion
biodiversity specimens that include such diverse objects as dinosaur bones, pressed
plants, dried mushrooms, fish preserved in alcohol, pinned insects, articulated skeletons,
eggshells, and microscopic pollen grains. In turn, these collections are a premier
resource for exploring life, its forms, interactions, and functions, across evolutionary,
temporal, and spatial scales (Bebber et al. 2010, Monfils et al. 2017, Schindel and
Cook 2018).
Biodiversity collections have historically consisted of physical objects and the infrastructure
to support those objects (Bradley et al. 2014). However, the last two decades have
witnessed a remarkable wave of digitization that has reshaped the collections paradigm
to include digital data and infrastructure (Nelson and Ellis 2018), opening vast new
areas for integrative biological research (e.g., a single plant specimen mounted on
an herbarium sheet may be analyzed in multitude ways to yield data on flower morphology,
DNA for applications from systematic studies to genome sequences, and isotopes for
analyses of nitrogen to understand the mechanisms of phenology in relation to nitrogen
uptake). In the United States, investment by the federal government through the National
Science Foundation's (NSF) Advancing Digitization of Biodiversity Collections (ADBC)
program has facilitated the digitization of approximately 62 million US biodiversity
specimens since 2011 through 24 thematic collection networks connecting over 700 collections.
These networks have helped to develop a collaborative infrastructure connecting specimen
data, human resources, research, and education among institutions. The ADBC program
has also provided support to iDigBio (the Integrated Digitized Biocollections), which
is the central coordinating unit for the digitization effort. The final ADBC grants
will be awarded in 2021.
During the last several years, the Biodiversity Collections Network has led an effort
to gather input from primary stakeholder communities regarding future directions for
collections and their use in research and education. The effort culminated in a workshop
held from 30 October through 1 November 2018 at Oak Spring Garden in Upperville, Virginia,
during which a strategy was developed to maximize the value of collections for future
research and education that builds on and leverages the accomplishments of the ADBC
program. The strategy that was informed by stakeholders, refined by workshop participants,
and vetted through public comment from scientific community is presented in the present
article.
The concept: Extended specimens
Science, industry, and society rely on physical specimens housed in US biodiversity
collections (e.g., Bradley et al. 2014, Tewksbury et al. 2014, Trejo-Salazar et al.
2016, DuBay and Fuldner 2017). Ongoing advances in data generation and analysis have
transformed biodiversity collections from physical specimens to dynamic suites of
interconnected resources enriched through study over time (Page et al. 2015, Soltis
2017, Nelson and Ellis 2018). The concept of an extended specimen (Webster 2017) conveys
the current perspective of the biodiversity specimen as extending beyond the singular
physical object to potentially limitless additional physical preparations and digital
resources (figure 1; Schindel and Cook 2018).
Figure 1.
Example of an extended specimen generated by the Dimensions of Biodiversity award
to study lichen biodiversity gradients in the Southern Appalachian Mountain Biodiversity
Hotspot of the eastern United States. The specimen (E. Tripp 6292) was collected in
Little River Canyon National Preserve, Alabama, and formally described as Lecanora
markjohnstonii by the project team in a paper lead authored by a graduate student
from University of Colorado, Boulder. The primary specimen extensions were created
and disseminated by The New York Botanical Garden.
The initiative: An extended specimen network
The monumental effort to digitize millions of specimens has resulted in a more accessible
and integrated body of information on species occurrence in space and time. Imaging
of specimens has provided access to verification and validation of species identification.
New and emerging techniques (e.g., CT scanning, isotopes, and AI) are actively unveiling
new sources of data and information related to collected specimens. Researchers in
biological informatics have provided new methods to analyze and integrate data to
address emerging questions. The next step in advancing and enhancing biodiversity
collections infrastructure must take into account the rapid development of novel applications
for biodiversity data and the growing body of data and resources derived from specimens.
Addressing the new hypotheses that researchers may generate, and serving new user
communities, will require richer, more complex, and more interconnected networks of
information about biodiversity specimens.
The Extended Specimen Network (ESN) is an initiative that would enhance the research
potential of specimens, through digitization and links with associated extended data.
These extensions will scale from molecules to the ecosphere, and would include genetic,
phenotypic, behavioral, and environmental data, as well as biotic interaction networks
and new multimedia components (e.g., 2D and 3D specimen images, in situ field images,
videos of field conditions). These data reside in disparate databases, have not yet
been digitized or made accessible to the scientific community, and are not linked
directly to the specimens with which they are associated. Physical specimens are the
critical objects that represent the depth and breadth of biodiversity held in US collections,
and specimens are the hubs through which these complex data are linked and can be
verified and enhanced. The creation of the ESN will leverage and even drive data integration
technologies. Once they are integrated and accessible, the extended specimens have
the potential to transform the sciences.
The ESN will therefore include the primary physical specimen, all associated physical
preparations (e.g., tissue subsamples), and all associated digital data (e.g., micrographs,
habit photographs, trait data, genomic data and other molecular markers). The network
will involve digitization and extension of existing specimens, and drive the collection
of new specimens purposefully collected and accessioned with these extended attributes
in mind. The ESN will rely on the development of new data integration mechanisms necessary
to link all of the dynamic components together across collections, data types, and
existing and evolving databases. These links will help researchers study and better
understand the rules that govern how organisms grow, diversify, and interact with
one another and how environmental change and human activities may affect those rules.
The ESN is also ideally suited to educating the next generation of data and biodiversity
scientists. The combination of object-based learning and digital data will provide
a unique gateway to data literacy for the twenty-first century scientist (Petrelli
et al. 2013, Hannan et al. 2016). As we look to develop our current and future workforce
and foster an informed citizenry, the openly accessible ESN will provide scalable
learning opportunities for K–12, undergraduate, graduate, and lifelong learning in
data literacy for life sciences.
The ESN will promote discovery
The ESN will stimulate new avenues of investigation, expedite existing ones, and provide
an enhanced resource for making science-based policy decisions. By linking physical
specimens to the data derived from them (e.g., gene sequences, images, behavior, geographic
ranges, and species interactions) and making all of the derived data searchable and
easily discoverable, we will have a rich and accessible integrated data source that
can be used to advance diverse areas of research. For instance, it will be possible
to more fully define and understand the traits that make up organisms, their relationships
with each other, and the ecosystems they inhabit. Such information has direct benefits
and can inform science relative to fundamental questions that challenge society and
the quality of human life. These questions include how crops can be more effectively
and efficiently grown in changing climates, how we can sustain and renewably use biological
resources in our oceans (Palkovacs et al. 2012), and how zoonotic diseases are transmitted
and spread (Samy et al. 2016). In addition to addressing complex questions with broad
societal benefits, the ESN will facilitate the as yet incomplete work of documenting
and naming the organisms that make up global biodiversity. Machine learning and other
novel data science and engineering techniques can help speed identification of museum
specimens in the ESN and may aid in recognizing hidden novelties.
Most current portals for digitized specimen data have user interfaces designed for
access primarily by biodiversity scientists and collections professionals. To take
full advantage of the rich data content and broad relevance of the ESN, the interfaces
need to be redesigned to both attract and facilitate use by a broader user base. Certain
analyses, data cleaning procedures, and static query parameters, among other features
can be added to allow users to interact with the data in more substantive ways. The
existing interfaces are set up to retrieve relevant occurrence records from a search
on the basis of a taxonomic name, geographic unit, or time period. The ESN will provide
an interface that can allow the user to query data in dynamic and discipline specific
ways. Future portals, designed for broader uses and broader user bases, could allow
for automated queries that include an ability to assess data quality, fitness for
use, and information gaps. This would allow users to answer questions such as Do the
available data comprise a representative set, or are critical data lacking because
key specimens have not been collected or digitized? How many different species, as
opposed to different species names, occur in a given region? How many specimens or
species in a given query possess a specific trait or suite of traits? Do the organisms
of the region occur in populations that are genetically distinct from other populations
of the same species? Have unique interactions among organisms been documented in the
region of interest?
The ESN will enable seamless data integration, attribution, and use tracking
Central to the success of the ESN is the development and implementation of a system
of identifiers and specimen tracking protocols. These will enable dynamic linking
of extended specimen components that would otherwise be separated in physical or digital
spaces, elucidate relationships between items in disparate collections (tissue:voucher,
plant:pollinator, host:parasite, etc.), and facilitate interoperability with data
sources outside of our immediate realm (Guralnick et al. 2015). It will also allow
collections institutions to follow the use of their specimens and develop metrics
for measuring their impact, particularly when used in concert with unique identifiers
(e.g., DOIs) assigned to individual data sets. Such metrics permit collections to
demonstrate their value, as well as better acquire and manage resources. Currently,
collections lack access to the data that demonstrate their full contributions to specimen-based
research through citation in publications, vouchering of molecular data (through the
National Center for Biotechnology Informatics, NCBI), or products created from direct
specimen use (images, CT scans, DNA extracts, etc.).
In addition to providing a discrete and reliable framework for quantifying the impact
of biodiversity collections, the new system of tracking will create the potential
for cost recovery when specimens are used in commercial enterprise. Use in applied
research (e.g., pharmacology, human health, food security) and commercial communities
(e.g., pharmaceuticals, agriculture) will further demonstrate the value of collections
to additional communities and contribute to the increased sustainability of biodiversity
collections.
A further benefit of the new tracking system is that it will also allow biodiversity
collections to meet new international standards for documenting the use of specimens
and their derived data. An example is the Nagoya Protocol, which is a supplemental
agreement to the Convention on Biological Diversity that establishes an international
legal framework for access to and methods of sharing benefits of genetic resources.
It requires that countries providing specimens define their access procedure and requires
users (countries and institutions) to report on and share benefits on their use.
Implementing and sustaining the extended specimen network
Establishing a comprehensive network of extended specimen data that integrates the
wealth of biodiversity and expertise held in US collections and associated data repositories
will require a monumental effort, comparable to building a new telescope for planetary
exploration. However, the focus on digital and human infrastructure, rather than physical
infrastructure, makes the magnitude of the effort required to build and sustain such
a resource harder to comprehend. Therefore, a major challenge to develop and maintain
the ESN will be to establish the unity of the resource, workforce, and scope of effort
required to build and maintain it across a network of collections-based institutions.
Creating, growing, and sustaining the ESN requires building and maintaining a network
of data providers, a centralized database infrastructure, and an educated workforce.
For consistency and sustainability, this requires a central coordinating unit with
long term secure funding, which is outside the scope of existing grant programs. Building
on the models of the National Center for Ecological Analysis Synthesis, and the National
Evolutionary Synthesis Center and the NCBI, a securely funded coordinating center
would anchor the ESN and support the data resources. If driven by the stakeholder
community, it can serve as a common portal to share established techniques, emerging
resources, and common tools for contributing to and sustain the ESN.
We suggest that a distributed ESN platform will be indispensable and that stable funding
is required for the ESN to reach its full potential. The envisioned data integration
mechanisms would facilitate data integration across major data resources. For example,
GenBank (a nondistributed database managed by the NCBI through the National Institutes
of Health) data would be integrated within the larger framework of the proposed ESN,
thus enhancing the utility of this existing platform by effectively linking genotype,
phenotype, and environment. Similarly, data from other new and ambitious efforts such
as the Earth BioGenome Project, which aims to sequence, catalog, and characterize
the genomes of all of Earth's eukaryotic biodiversity over a period of 10 years (Lewin
et al. 2018), and isotopic data from IsoBank would also be integrated with and accessible
through the ESN, as would data from new, comprehensive collecting initiatives, such
as the NEON Biorepository (e.g., Kao et al. 2012). By integrating the nation's existing
critical databases and bioinitiatives, the ESN will greatly enhance the nation's collective
biological knowledge, resources, and potential.
Index US biodiversity collections and their holdings
Biological collections comprise the most comprehensive record of life on Earth; their
potential will only be fully realized when the data contained within them are revealed
and made more accessible for computational analyses. Many of the approximately 1469
US biodiversity collections are not digitized and do not have accurate estimates of
the size or taxonomic breadth of their holdings. We need to address this information
gap and take stock of the holdings in US biodiversity collections and characterize
them in terms of taxonomic, temporal, and geographic emphases, and compile these data
into a national collections index. The existing Index Herbariorum (Theirs 2019), an
index of plant collections, is a logical model for this resource. An index of all
US collections will allow the community to prioritize collections for digitization
and facilitate completion tracking for the overall ESN.
Complete and improve existing digitized data
Significant proportions of the existing digitized specimen records are incomplete,
with many entered as skeletal records lacking critical data fields (e.g., locality,
date, collector). Geocoordinates need entry and verification for the vast majority
of digitized specimens. A foundational step in building the ESN will involve completing
and standardizing records to maximize their value and interoperability. Development
of computational tools that can infer missing values or aid users in completing missing
data must be a high priority. Efforts are in place taking advantage of a combination
of image analysis (including optical character recognition) and data pattern matching.
Identifying and filling gaps in biodiversity data
Biodiversity specimens have become critical for researchers documenting and investigating
environmental change. We must continue to collect specimens and build our collections
to inform research into the future. New collections may be especially important in
areas that are undergoing rapid change or reduction, such as high-elevation mountain
ecosystems, tropical forests, the Atlantic and Gulf coastlines, and the Arctic. Continued
collection and integration of new specimens is central to the success of the ESN and
as we learn more about how specimens can be used to inform science, we must adjust
our sampling protocols to implement a holistic, next-generation approach to the collection
of biodiversity specimens. As was discussed by Schindel and Cook (2018), a next-generation
approach must be focused on nested sampling that extends beyond the single organism
(e.g., a single plant), to include nested sampling of the biotic associates (e.g.,
soil microbes, epiphytes, endophytes, and parasites spanning from viruses to arthropods
and fungi) and data on its environment (e.g., community composition, microclimate,
macroclimate, habitat quality). In addition to nested sampling and detailed observations,
we need to augment our collecting patterns to conduct targeted sampling to fill existing
gaps. Links among nested samples can facilitate new and dynamic research opportunities
and transform our capacity to understand life on Earth.
Build and strengthen strategic partnerships
The ESN will enable the expansion of existing partnerships and creation of new strategic
engagements. There is a strong need for interdisciplinary development among biology,
biological collections, and the computer and data sciences community in order to build,
improve, and maintain next-generation collections infrastructure, workforce, and accessibility.
We will continue to embrace an openness to collaboration with nontraditional partners
in academia and industry that fosters bidirectional benefits.
Build dynamic links with data aggregators
Some of the extended components that need to be linked to existing biodiversity specimens
via the ESN are hosted in a growing variety of databases such as the Catalogue of
Life checklist, the Biodiversity Heritage Library, the Barcode of Life Data System,
the NCBI, and the Encyclopedia of Life Traitbank. Establishing a multidirectional
means of data exchange with aggregators is a necessity. Collaboration with programs
such as the NSF-funded National Ecological Observatory Network (NEON), the Long Term
Ecological Research Network, and Critical Zone Observatories, will ensure that standards
and protocols are developed that enable interoperability between collections data
and occurrence records both past and present. Furthermore, standardization of extended
specimen data driven by the ESN (and the taxonomic expertise across the ESN) will
make the data collected by future researchers using these centers computable and therefore
accessible to a broad audience of users.
Facilitate data integration across international biodiversity organizations
Participation to the fullest extent possible in the Global Biodiversity Information
Facility proposed alliance for biodiversity knowledge (Hobern et al. 2019) will facilitate
local work and help align efforts to document, describe, and quantify US biodiversity
in relation to other global efforts, including the Atlas of Living Australia and the
Distributed System of Scientific Collections, a new European Union program. The ESN
also provides the ideal framework within which to identify and address persistent
issues in specimen-based data sharing, including the development of standardized taxonomies
and ontologies. This could be a strategic goal in conjunction with pursuit of collaboration
with data aggregators from Mexico (CONABIO) and Canada (Canadensys) to Brazil (SpeciesLink)
to permit the seamless transfer of data needed for large-scale understanding of the
breadth of global biodiversity, its distribution and change over time.
The extended specimen network and twenty-first century learners
The ESN has significant transformative potential for scientific research and policy.
The ESN can serve as an effective tool to educate and inform broad and diverse audiences
about biodiversity and data science. Below we outline the roles that the ESN could
have in the realms of formal and informal education.
Formal education
The ESN and collections community has significant potential to engage, educate, and
empower the next generation of biodiversity data stewards, researchers, and ESN data
users. Biodiversity data and ESN usage, require skills and competencies that align
naturally with next-generation science standards outlined for K–12 science curricula
(NRC 2013) and the undergraduate biology concepts and competencies included in Vision
and Change in Undergraduate Biology Education: A Call to Action (Brewer and Smith
2011). The digital data and specimens central to biodiversity science can be valuable
resources and incorporated seamlessly into existing courses, including subject matter
in evolution, biodiversity, systematics, taxonomy, and ecology. Specimen-based data
make science accessible through the specimen itself, which is tangible, place based,
and engaging, as well as through aggregated specimen data that are verifiable, relevant,
and a logical gateway to data literacy (Petrelli et al. 2013, Hannan et al. 2016,
Monfils et al. 2017). The place-based capacity of collections data combined with the
social and societal relevance of biodiversity science can serve a role in creating
inclusive, culturally relevant, and socially conscious educational materials that
engage a broad and diverse audience in biodiversity science. By defining biodiversity
data literacy skills, creating a learning progression that incorporates the ESN and
data literacy into formal education, and providing accessible materials with teacher
training and educator interfaces that facilitate use in the classroom, we can support
an increasingly biodiversity literate society and train the next generation of data
literate scientists.
Informal education
As digital resources centered around the ESN expand, so too will informal education
opportunities. Indeed, we likely cannot reach the full potential of the ESN without
strong involvement of the citizen science community. Many citizen science projects
are already structured on monitoring biodiversity: eBird, eButterfly, iNaturalist,
and the US National Phenology Network, for example, provide platforms for contributing
sightings or recordings of organisms or a particular attribute of an organism. Internet-based
projects can involve the public directly in the development and maintenance of the
ESN through contributing to collections-based science and databases. Projects such
as Notes from Nature (Hill et al. 2012), the Smithsonian Transcription Center, and
CitSciScribe are platforms that invite the public to add digital data to images of
specimens. Tasks include transcription, morphological measurements, and phenological
annotations. Furthermore, the majority of these projects contribute directly to active
research projects. Such programs are broadly inclusive and engage participants from
a wide range of ages, abilities, and interests, and with minimal start-up costs.
The ESN will advance the NSF’s 10 big ideas
If implemented, the new strategy for biodiversity collections proposed in the present
article will provide a powerful scientific tool for the biological sciences. As we
outline below, it will also establish a resource that will enable progress toward
cross-cutting challenges at the frontiers of science reflected in the 10 big ideas
recently identified by the NSF.
Understanding the rules of life
Understanding the rules by which biological and environmental factors influence the
wide range of organisms on which humans depend will require diverse data accessed
from specimens spanning the tree of life. Biodiversity specimens are a source of genomic,
phenomic, and environmental data, the three basic data types required for identifying
causal and predictive relationships across these scales. Collections provide these
fundamental data, although, as was outlined above, they have not yet been exposed
through comprehensive digitization and data linkages. When the vision of the ESN is
fully realized, it will be possible to examine key evolutionary traits across spatial
and temporal scales, using diverse combinations of data types from the genome to the
phenome and beyond. Previously unrecognized patterns may also be discovered using
new AI methods, and these could address specific research questions such as how genetic
regulators of similar phenotypes evolve in relation to environment.
Harnessing data for twenty-first century science and engineering
The digitization of natural history collections has already contributed to a deluge
of data from the nation's scientific facilities. As we broaden the knowledge bank
of specimens with additional genotypic, phenotypic, and environmental data, the amount
of data will further increase exponentially. The ESN will be a prime example of a
cohesive, national scale approach to research data infrastructure through the development
and implementation of new tools to integrate data. In addition, specimen-based data
provides a unique opportunity to educate students in data science, train a data-enabled
workforce, and train future biodiversity data professionals. Collections data, alongside
the archived specimens, are an engaging and accessible data source that can provide
students an opportunity to experience the entirety of the data pathway while practicing
verifiable and testable science.
Midscale infrastructure
Much of the support required for the ESN falls in the gap between what the NSF currently
funds as either small or large infrastructure. Specifically, the computer and human
infrastructure required for data acquisition, deployment, and training to support
the ESN represent midscale infrastructure needs, both in terms of funding level and
the scientific research it will support. Although many aspects of the ESN would be
characterized as midscale infrastructure, it is important to highlight that support
for the ESN coordinating center itself would likely fall within the scope of large
infrastructure.
Navigating the new Arctic
The Arctic biota has been minimally sampled over the past two centuries. Arctic biodiversity
specimens are stored in relatively few US collections and provide our best baselines
for understanding the implications of rapid environmental changes on life (e.g., Bond
et al. 2015) in a geopolitical region that is increasingly critical to the global
economy and security. Because of the rapid rate of annual warming in the Arctic, we
should immediately build international coalitions that will invest in spatially extensive,
site intensive natural history collections that will provide the biodiversity infrastructure
necessary to critically assess change. Over time, specimens and their associated digitized
data, accessed via the ESN, would provide the samples required by diverse technologies
(e.g., genomics, isotope ecology), a robust historical context for the proposed network
of observational platforms, and a reference for the identification, distribution,
behavior, and response of species and their pathogens in the Arctic (Cook et al. 2013,
Hoberg et al. 2013).
Growing convergent research at NSF
Enhancement of the roles that collections-derived data can play in understanding and
protecting human health, and in education, are key objectives of the new agenda. This
could be achieved through the centralized efforts to integrate and share data more
effectively and widely. The ESN combines diverse data sources linked to physical biodiversity
specimens and, as such, is a physical manifestation of convergent research that will
clearly demonstrate the power of this approach.
The future of work at the human technology frontier
The use of biodiversity collections in projects to both refine current techniques
in machine learning and to document variation among organisms as exhibited by specimens
holds great promise (e.g., Carranza-Rojas et al. 2017, McAllister et al. 2018). The
use of these tools will lead to new avenues of data analysis, requiring new skills
for researchers and data managers. Collections professionals will find themselves
at this frontier. Supporting the adoption of new technology and documenting the experience
through training and best practices is a key aim of the strategy presented in the
present article. The work carried out by this community may prove transferable to
other communities using the tools and workflows developed as part of the ESN.
Enhancing science and engineering through diversity
The ESN requires new generations of taxonomic expertise. The place-based capacity
of biodiversity specimens and associated data combined with the social and societal
relevance of biodiversity science can serve a role in creating inclusive, culturally
relevant, and socially conscious educational materials that engage a broad and diverse
audience in biodiversity science. Biodiversity collections institutions have significant
potential to engage a broad range of people to create a scientifically literate work
force and build the ranks of both the scientific and engineering communities.
Immediate action items to support the ESN
Although a long-term funding structure for the ESN will take time to develop, steps
can be taken immediately to initiate the process, including the following:
A robust, comprehensive specimen identifier system should be developed in collaboration
with other international data aggregators and providers to enable transparent and
uncomplicated integration of biodiversity data with other data sources. The system
must also facilitate the attribution of collections’ role in discovery, policy, and
promoting transparency for broader issues involving multiple stakeholders (e.g., access
and benefit sharing).
An authoritative, comprehensive, and self-updateable index of US collections institutions
should be created, similar to the Index Herbariorum for global herbaria, with structured
metadata to describe their holdings. This is the first step toward expediting the
discovery of undigitized collections and revealing these to the research community.
The digitization of existing material should continue, with a focus on underrepresented
taxa (e.g., those in entomology, paleontology, and archeology collections), including
data gaps in time, space, and scale, and incorporating of specimens held in small
regional and individual researcher collections. These efforts must also include improvement
of previously digitized specimen data by imaging specimens, completing skeletal records,
and augmenting data with georeferencing.
New protocols must be developed for the collection and dissemination of data-rich
samples and nested samples that provide greater context for understanding the biotic
and abiotic interactions of organisms, and comprehensive data sets must be created
for research and education.
An accessible educator and student interface, baseline analysis tools, and vetted
educational materials should be developed to enable integration of biodiversity data
in K–12 and undergraduate course work. New tools and resources, combined with training
opportunities, will facilitate educator adoption of data-centric educational materials
that foster student engagement with digital biodiversity data. Creating an accessible
entry into digital biodiversity data will enable training of an informed, digitally
fluent workforce.
Broad-scale adoption of core biodiversity data literacy skills and competencies in
K–12 and undergraduate curricula should be championed in order to foster a biodiversity
savvy future workforce, engage new end users in novel uses of biodiversity data, and
sustain and promote careers in advancing collections science, biodiversity research,
and data literacy.
Enhanced training of emerging and established professionals for interdisciplinary
work in biodiversity, data science, and informatics should be supported. Team Science
skills to work collaboratively across disciplines should be emphasized, together with
soft skills related to communication, creativity, and critical thinking, because these
are paramount to conducting transformative science, communicating research, and cultivating
and leveraging relationships with new research and user communities.