Biodiversity Literature Research Articles

A Possible Workflow from New and Legacy Publications to keep the World Flora Online up to date with New Species and Augmenting Taxonomic Treatments

Thousands of new species are discovered each year, and new results are published to add to the knowledge of existing species. A growing number of these are immediately accessible through the Biodiversity Literature Repository (BLR) and reused by Global Biodiversity Information Facility (GBIF), bringing the number of treatments covering plant species to over 25,000 treatments. This includes the findable, accessible, interoperable, and resuable (FAIR) treatments and related figures, and in many cases the material citation of the holotype, and links to the collection, specimen and gene sequences attribured to the codes. The FAIR data is deposited in the Biodiversity Literature Repository ensuring long-term access, and includes rich, customized metadata describing its content using standard vocabularies (e.g. Darwin Core (DwC) or Open Biological and Biomedical Ontology (OBO) Foundry, as well as links to related items and data reuse (e.g. GBIF and CheckListbank). TreatmentBank is a European Research Infrastructure, which annotates taxonomic publications including quality control, as much as possible by machine, and as needed by human curation. The process is versatile, the output can be customized and immediately used by GBIF and the Swiss Institute of Bioinformatics library system (SIBiLS) to add treatments akin to articles in PubMed Central. Another focus of conversion could be floras (several series published in Muséum national d'Histoire naturelle including those that are currently only available in print). In addition to the articles provided through these collaborations, other journals were processed, totaling 5,900 articles with 54,000 treatments of which 5,600 are plants, 48,000 figures, 140,000 material citations, of which 9,000 (670 plants) are new species and 670 (16) new genera described in 2021. Arcadia Fund is funding a project to include over 100 additional journals into the daily processing, as well as annotating data from legacy publications, with the possibility of including more journals covering plant taxonomy. The workflow is based on the open source software GoldenGate Imagine, a tool used to convert articles from PDF format into an Image Markup File (IMF) export file including all the annotations in a set of CSV files and allowing checking and improve the quality of data. The quality control parameter can be defined according to specific user requirements and the curation of the annotation can be done as part of the workflow or by third parties. The IMF can be uploaded to TreatmentBank where FAIR data is generated through their deposits in the Biodiversity Literature Repository. All the data is accessible from the Plazi API in various formats such as XML, DwC-A (DarwinCore Archive) or RDF, and checked when the data has been deposited or reused by returning the link of the respective recipient’s reuse identifier. Furthermore, the treatment citations annotated in the publications provide access to the treatments related to the same taxon, including synonyms. In this presentation, we explain the data annotated and made FAIR by TreatmentBank in order to discuss what would be needed to import this rapidly increasing corpus of taxonomic treatments as a new source for WFO (World Flora Online). A side effect of the discussion could be suggestions to publishers on how they should provide data so that the taxonomic data can be automatically integrated into WFO to keep it as up-to-date as possible.

Enabling Published Taxonomic Data to be used to Address the Biodiversity Crisis: Biodiversity Literature Repository and TreatmentBank

To understand the loss of species, a benchmark is needed, e.g. the status of biodiversity in 1992 when the Convention on Biological Diversity recognized biodiversity crisis to compare to its status in the successive year. Though we are far from knowning how many species there are on planet Earth, we keep track of their descriptions and number through the information kept in our libraries. Each species discovered is represented therein by at least one taxononic treatment. The library includes an estimated 500 million pages and is updated daily with an estimated 17–18,000 new species annually and over 100,000 treatments augmenting the knowledge of existing species. In reality, we do not know how many species exist. We know that the catalogue of life is incomplete and basic knowlege of known species is often lacking and not even updated regularly. On the other hand, the scientific standard to cite previous works and facts is at the same time an ideal prerequisit to build a knowledge graph in the era of digital knowledge. TreatmentBank (TB) and the Biodiversity Literature Repository (BLR), two European Research Infrastructures, provide a service to convert unstructured biodiversity data from scholarly publications into semantically enhanced, digital accessible knowledge (Fawcett et al. 2022) making it findable, accessible, interoperable, reusable (FAIR, Wilkinson et al. 2016) and providing long term access in collaboration with Zenodo. Data sources are either legacy publications or active journals using an XML workflow such as Zookeys or the Biodiversity Data Journal, published by the pioneer of taxonomically enhanced Taxpub XML publishing, Pensoft. As part of the Horizon 2020-funded project Biodiversity Community Integrated Knowledge Library (BiCIKL), bidirectional linking of taxonomic names with the Catalogue of Life, DNA-sequences with the International Nucleotide Sequence Database Collaboration (INSDC) and material citations with their respective natural history collection or their depositions in the Global Biodiversity Information Facility (GBIF) is targeted. As input to allow queries including text and data mining for traits and biotic interactions, the treatments are uploaded to the Swiss Institute of Bioinformatics (SIB) Library Service (SIBiLS) using TaxPub and schema based on Journal Article Tag Suite (JATS) widely used in life science publishing and PubMed Central, allowing the use of the advanced text and data mining tools in the life science community. Another research infrastructure that ensures an RDF representation and conversion into Linked Open Data (LOD) is OpenBiodiv allowing users to explore DAK as part of growing linked open biodiverstiy and related data. All the data fit for GBIF use is reused by GBIF representing close to 60% of all published data sets, which makes TreatmentBank and BLR, for example, a sole provider of data for approximately 90,000 species not recorded in GBIF by other publishers. The long-term strategy is to build up the momentum to be an infrastructure relevant for global biodiversity conservation and research. Long-term support will be achieved by negotiations with respective agencies and publishers, and through building up a global user community using the biodiversity digital acccessible knowledge.

A formalization of one of the main claims of “OpenBiodiv: A knowledge graph for literature-extracted linked open data in biodiversity science” by Penev et al. 20191

Penev et al. claimed in previous work that triples in the OpenBiodiv knowledge graph releases are generally semantic triples extracted from biodiversity literature. We present here a formalization of that claim, stating that all things of class “triple in OpenBiodiv knowledge graph” that are in the context of a thing of class “release of OpenBiodiv knowledge graph” generally have a relation of type “is same as” to a thing of class “semantic triple extracted from biodiversity literature” in the same context.

Urban biodiversity: State of the science and future directions

Since the 1990s, recognition of urban biodiversity research has increased steadily. Knowledge of how ecological communities respond to urban pressures can assist in addressing global questions related to biodiversity. To assess the state of this research field in meeting this aim, we conducted a systematic review of the urban biodiversity literature published since 1990. We obtained data from 1209 studies that sampled ecological communities representing 12 taxonomic groups. While advances have been made in the field over the last 30 years, we found that urban biodiversity research has primarily been conducted in single cities within the Palearctic and Nearctic realms, within forest remnants and residential locations, and predominantly surveys plants and birds, with significant gaps in research within the Global South and little integration of multi-species and multi-trophic interactions. Sample sizes remain limited in spatial and temporal scope, but citizen science and remote sensing resources have broadened these efforts. Analytical approaches still rely on taxonomic diversity to describe urban plant and animal communities, with increasing numbers of integrated phylogenetic and trait-based analyses. Despite the implementation of nature-based solutions across the world’s cities, only 5% of studies link biodiversity to ecosystem function and services, pointing to substantial gaps in our understanding of such solutions. We advocate for future research that encompasses a greater diversity of taxonomic groups and urban systems, focusing on biodiversity hotspots. Implementing such research would enable researchers to move forward in an equitable and multidisciplinary way to tackle the complex issues facing global urban biodiversity. Word cloud from titles of 1209 publications on urban biodiversity from 1990–2018.

European Journal of Taxonomy: a deeper look into a decade of data

The European Journal of Taxonomy (EJT) is a decade-old journal dedicated to the taxonomy of living and fossil eukaryotes. Launched in 2011, the EJT published exactly 900 articles (31 778 pages) from 2011 to 2021. The journal has been processed in its entirety by Plazi, liberating the data therein, depositing it into TreatmentBank, Biodiversity Literature Repository and disseminating it to partners, including the Global Biodiversity Information Facility (GBIF) using a combination of a highly automated workflow, quality control tools, and human curation. The dissemination of original research along with the ability to use and reuse data as freely as possible is the key to innovation, opening the corpus of known published biodiversity knowledge, and furthering advances in science. This paper aims to discuss the advantages and limitations of retro-conversion and to showcase the potential analyses of the data published in EJT and made findable, accessible, interoperable and reusable (FAIR) by Plazi. Among others, taxonomic and geographic coverage, geographical distribution of authors, citation of previous works and treatments, timespan between the publication and treatments with their cited works are discussed. Manually counted data were compared with the automated process, the latter being analysed and discussed. Creating FAIR data from a publication results in an average multiplication factor of 166 for additional access through the taxonomic treatments, figures and material citations citing the original publication in TreatmentBank, the Biodiversity Literature Repository and the Global Biodiversity Information Facility. Despite the advances in processing, liberating data remains cumbersome and has its limitations which lead us to conclude that the future of scientific publishing involves semantically enhanced publications.

TaxoNERD: Deep neural models for the recognition of taxonomic entities in the ecological and evolutionary literature

Abstract Easy access to multi‐taxa information (e.g. distribution, traits, diet) in the scientific literature is essential to understand, map and predict all‐inclusive biodiversity. Tools are needed to automatically extract useful information from the ever‐growing corpus of ecological texts and feed this information to open data repositories. A prerequisite is the ability to recognise mentions of taxa in text, a special case of named entity recognition (NER). In recent years, deep learning‐based NER systems have become ubiquitous, yielding state‐of‐the‐art results in the general and biomedical domains. However, no such tool is available to ecologists wishing to extract information from the biodiversity literature. We propose a new tool called TaxoNERD that provides deep neural network (DNN) models to recognise taxon mentions in ecological documents. To achieve high performance, these models usually need to be trained on a large corpus of manually annotated text. Creating such a corpus is a laborious and costly process, with the result that manually annotated corpora in the ecological domain tend to be too small to learn an accurate DNN model from scratch. To address this issue, we leverage existing models pretrained on large biomedical corpora using transfer learning. The performance of our models is evaluated on four corpora and compared to the most popular taxonomic entity recognition tools. Our experiments suggest that existing taxonomic NER tools are not suited to the extraction of ecological information from text as they performed poorly on ecologically oriented corpora, either because they do not take account of the variability of taxon naming practices or because they do not generalise well to the ecological domain. Conversely, a domain‐specific DNN‐based tool like TaxoNERD outperformed the other approaches on an ecological information extraction task. Efforts are needed to raise ecological information extraction to the same level of performance as its biomedical counterpart. One promising direction is to leverage the huge corpus of unlabelled ecological texts to learn a language representation model that could benefit downstream tasks. These efforts could be highly beneficial to ecologists on the long term.

The BHL-Plazi Partnership: Getting data from the 1800s directly into 21st century, reused digital accessible knowledge

Plazi is a Swiss non-governmental organization dedicated to the liberation of data imprisoned in flat, dead-end formats such as PDFs. In the process, the data therein is annotated and exported in various formats, following field-specific standards, facilitating free access and reutilization by several other service providers and end-users. This data mining and enhancement process allows for the rediscovery of the known biodiversity since the knowledge on known taxa is published into an ever-growing corpus of papers, chapters and books, inaccessible to the state-of-the-art service providers, such as Global Biodiversity Information Facility (GBIF). The data liberated by Plazi focuses on taxonomic treatments, which carry the unit of knowledge about a taxon concept in a given publication and can be considered the building block of taxonomic science. Although these extracted taxonomic treatments can be found in Plazi’s TreatmentBank and Biodiversity Literature Repository (BLR), hosted in the European Organization for Nuclear Research (CERN) digital repository Zenodo, data included in treatments (e.g., material citations and treatment citations) can also be found in other applications as well, such as Plazi’s Synospecies, Zenodeo, and GBIF. Plazi’s efforts result in more Findable, Accessible, Interoperable, and Reusable (FAIR) biodiversity literature, improving, enhancing and enabling access to data included therein as digital accessible data, otherwise almost unreachable. The Biodiversity Heritage Library (BHL), on the other hand, provides a pivotal service by digitizing heritage literature and current literature for which BHL negotiates permission, and provides free access to otherwise inaccessible sources. In 2021, BHL and Plazi signed a Statement of Collaboration, aiming to combine the efforts of both institutions to contribute even further to FAIR-ifying biodiversity literature and data. In a collaborative demonstration project, we selected the earliest volumes and issues of the Revue Suisse de Zoologie in order to conduct a pilot study that combines the efforts of both BHL and Plazi. The corpus is composed of eight volumes (tomes), 24 issues (numbers) and 98 papers, including a total of over 5000 pages and 200 images. To process this material, BHL assigned CrossRef Digital Object Identifiers (DOI) to these already digitally accessible publications. Plazi created a template to be used in GoldenGate-Imagine, indicating key parameters used for tailored data mining of these articles, and customized to the journal’s graphic layout characteristics at that time. Then, we proceeded with quality control steps to provide fit-for-use data for BLR and GBIF by ensuring that the data was correctly annotated and eliminating potential data transit blockages at Plazi’s built-in data gatekeeper. The data was then subsequently reused by GBIF. Finally, we present here the summary of the obtained results, highlighting the number of key publication attributes aforementioned (pages, images), but also including a drill-down into the different taxonomic groups, countries and collections of origin of the studied material, and more. All the data is available via the Plazi statistics, the Biodiversity Literature Repository Website and community at Zenodo, the Zenodeo APIs and GBIF where the data is being reused.

Biodiversity Heritage Library and Global Names: Successes, opportunities and the challenges for the future collaboration

The Biodiversity Heritage Library (BHL) is a major aggregator of biodiversity literature with more than 200,000 volumes. The Global Names Architecture (GNA) strives to develop and provide tools for finding, parsing and verifying scientific names. GNA and BHL have enjoyed 10 years of collaboration in the creation of a scientific names index for BHL. Such an index provides researchers with a means for finding data about more than a million species. Recently, BHL and GNA developed a workflow for the creation of an index that covers more than 50 million pages of BHL, and finds and verifies scientific names in less than a day. The unprecedented speed of the index creation opens an opportunity to dramatically increase its quality and reach. The following challenges can now be addressed. 1. Abbreviated names reconciliation. From 20% to 25% of all scientific names in BHL are abbreviated. It is much harder to reconcile and verify abbreviated names, because their specific epithets are not unique. We plan to reconcile the vast majority of such names via a statistical approach. 2. Linking of biodiversity publication titles with actual pages in BHL. Scientific names are closely connected to publications of original description, taxonomic treatments, and other usages. We plan to build algorithms for finding out how different lexical variants of the same publication reference can be disambiguated and connected to corresponding BHL pages. 3. Using taxonomic intelligence for finding information about species. According to our estimation, on average, there are three scientific names (historical and current) per taxon. Names of species often change over time as a result of misspellings, and homotypic or heterotypic synonymy. We plan to link outdated names with currently accepted names of taxa. This functionality provides all information about a taxon in BHL, no matter what names were used to reference the taxon at the time of publication. 4. Finding information about original descriptions of genera and species. For every species there is a publication with the original description. We want to create an index of species that are described in the publications aggregated by BHL. 5. Detection of species names in spite of "incorrect" capitalization. Previously, or in horticultural sources, specific epithets were often capitalized (e.g., Bulbophyllum Nocturnum), or for patronyms in which the species was named in honor of someone (e.g., Notiospathius Johnlennoni). We plan to detect names with non-standard capitalization of this sort. 6. Removal of false positives. Texts in Latin language, names of people, and geographical entities often create false positives that look like scientific names. Using machine learning techniques will allow us to detect and remove most of these errors from the names index. 7. Detection of the names of biodiversity scientists and geographical entities in texts. Finding names of biologists and geographical places in addition to scientific names would allow us to draw connections between these data and to create metadata demonstrating these links. We plan to add tools and algorithms for indexing person names and geographical names. In this talk I will present plans for a dramatic quality increase in the scientific name-finding algorithms, as well as an introduction of other elements that would enhance usability of BHL for its patrons.

Delivering Fit-for-Use Data: Quality control

Automatic data mining is not an easy task and its success in the biodiversity world is deeply tied to the standardization and consistency of scientific journals' layout structure. The various formatting styles found in the over 500 million pages of published biodiversity information (Kalfatovich 2010), pose a remarkable challenge towards the goal of automating the liberation of data currently trapped on the printed page. Regular expressions and other pattern-recognition strategies invariably fail to cope with this diverse landscape of academic publishing. Challenges such as incomplete data and taxonomic uncertainty add several additional layers of complexity. However, in the era of big data, the liberation of all the different facts contained in biodiversity literature is of crucial importance. Plazi tackles this daunting task by providing workflows and technology to automatically process biodiversity publications and annotate the information therein, all within the principles of FAIR (findable, accessible, interoperable, and reusable) data usage (Agosti and Egloff 2009). It uses the concept of taxonomic treatments (Catapano 2019) as the most fundamental unit in biodiversity literature, to provide a framework that reflects the reality of taxonomic data for linking the different pieces of information contained in these taxonomic treatments. Treatment citations, composed of a taxonomic name and a bibliographic reference, and material citations carrying all specimen-related information are additional conceptual cornerstones for this framework. The resulting enhanced data are added to TreatmentBank. Figures and treatments are made Findable, Accessible, Interoperable and Reuseable (FAIR) by depositing them including specific metadata to the Biodiversity Literature Repository community (BLR) at the European Organization for Nuclear Research (CERN) repository Zenodo, and pushed to GBIF. The automation, however, is error prone due to the constraints explained above. In order to cope with this remarkable task without compromising data quality, Plazi has established a quality control process, based on logical rules that check the components of the extracted document raising errors in four different levels of severity. These errors are also used in a data transit control mechanism, “the gatekeeper”, which blocks certain data transits to create deposits (e.g., BLR) or reuse of data (e.g., GBIF) in the presence of specific errors. Finally, a set of automatic notifications were included in the plazi/community Github repository, in order to provide a channel that empowers external users to report data issues directly to a dedicated team of data miners, which will in turn and in a timely manner, fix these issues, improving data quality on demand. In this talk, we aim to explain Plazi’s internal quality control process and phases, the data transits that are potentially affected, as well as statistics on the most common issues raised by this automated endeavor and how we use the generated data to continuously improve this important step in Plazi's workflow.

(Re)Discovering Known Biodiversity: Introduction

Biodiversity sciences, including taxonomy, are empirical sciences where all results are published in scholarly publications as part of the research life cycle. This creates a corpus of an estimated 500 million printed pages (Kalfatovic 2010) including billions of facts such as traits, biotic interactions, observations characterizing all the estimated 1.9 million known species (Costello et al. 2013). This library is continually reused, cited and extended, for example with more than an estimated 15,000–20,000 new species annually (Polaszek 2005). All of these figures are estimates because we neither know how many species have been discovered, nor how many are being discovered every day, let alone what we know about them. Following standard scientific practice, previous publications, specimens, gene sequences, or taxonomic treatments (Catapano 2019) are cited more or less explicitly. In the pre-digital age, these links were meant for the human reader to be understood. For example, "L. 1758" is an established reference and links to both, Carolus Linnaeus and Linnaeus 1758, understandable at least by an expert human, and in the digital age, provides access to the respective digital representation. These data within the hundreds of millions of printed and now increasingly digitally published pages form a seamless, albeit implicit knowledge graph. Unfortunately, most of these publications are in print—the Biodiversity Heritage Library digitized about 50 million pages (Kalfatovic 2010)—or in many cases, closed access publications, and thus this knowledge is not readily accessible in the digital age. However, in today's digital age, each of these kinds of implicit links is an expensive stumbling block to access and reuse of the referenced data, its parent publications and the cited referenced data therein. Inadequate formats, language and access to taxonomic information were already recognized in 1992 at the Rio Summit (Taxonomic Impediment). The consequences of these impediments are only now obvious with the realization of the daunting amount of human resources needed to digitally catalogue and index this unknown (not discoverable and inaccessible) known knowledge, let alone making the data itself findable, accessible, interoperable and reusable (FAIR). This is a formidable and complex scientific challenge. Plazi is taking on this challenge. Its vision is to promote and enable the discovery and liberation of data to transform the unknown known data into digitally accessible knowledge, i.e., to build a digital knowledge base aimed at discovering all the species (and other taxa) we know, and what we know about them. Taxonomic publications with their highly standardized taxonomic names, taxonomic treatments, treatment citations, material citations and illustrations are well suited to machine extraction. Together they include the entire catalogue of life with all the discovered species and their synonyms, often tens to hundreds of treatments, and figures that depict the myriad forms that comprise the world’s biodiversity. Once these data are FAIR, it allows bidirectional linking, for example of taxonomic names to the referenced taxonomic treatment, other digital resources such as gene sequences or digital specimens. At the same time, each datum is an entry point to the wealth of information that can be followed by the human user by clicking the links, but more importantly, analysed by machines. Here, digitally accessible knowledge will be defined in the context of discovering known biodiversity, including strategies of how to approach the challenge, which then will be detailed in subsequent talks in this symposium. This symposium is based on Plazi’s ongoing data liberation and discovery supported by the European Union (e.g. Biodiversity Community Integrated Knowledge Library BiCIKL), United States (e.g. NIH) and Swiss research funding (e.g. e-BioDiv and the Arcadia Fund), collaboration with publishers (e.g. Pensoft, Muséum national d'Histoire naturelle, Consortium of European Taxonomic Facilities Publications, the Zenodo repository, Biodiversity Heritage Library), and data reusers like the Global Biodiversity Information Facility, Ocellus, Synospecies and openBiodiv. Currently, over 500,000 taxonomic treatments and 300,000 illustrations have been liberated and are accessible through TreatmentBank and the Biodiversity Literature Repository.

Biodiversity Literature Repository: Building the customized FAIR repository by using custom metadata

In the landscape of general-purpose repositories, Zenodo was built at the European Laboratory for Particle Physics' (CERN) data center to facilitate the sharing and preservation of the long tail of research across all disciplines and scientific domains. Given Zenodo’s long tradition of making research artifacts FAIR (Findable, Accessible, Interoperable, and Reusable), there are still challenges in applying these principles effectively when serving the needs of specific research domains. Plazi’s biodiversity taxonomic literature processing pipeline liberates data from publications, making it FAIR via extensive metadata, the minting of a DataCite Digital Object Identifier (DOI), a licence and both human- and machine-readable output provided by Zenodo, and accessible via the Biodiversity Literature Repository community at Zenodo. The deposits (e.g., taxonomic treatments, figures) are an example of how local networks of information can be formally linked to explicit resources in a broader context of other platforms like GBIF (Global Biodiversity Information Facility). In the context of biodiversity taxonomic literature data workflows, a general-purpose repository’s traditional submission approach is not enough to preserve rich metadata and to capture highly interlinked objects, such as taxonomic treatments and digital specimens. As a prerequisite to serve these use cases and ensure that the artifacts remain FAIR, Zenodo introduced the concept of custom metadata, which allows enhancing submissions such as figures or taxonomic treatments (see as an example the treatment of Eurygyrus peloponnesius) with custom keywords, based on terms from common biodiversity vocabularies like Darwin Core and Audubon Core and with an explicit link to the respective vocabulary term. The aforementioned pipelines and features are designed to be served first and foremost using public Representational State Transfer Application Programming Interfaces (REST APIs) and open web technologies like webhooks. This approach allows researchers and platforms to integrate existing and new automated workflows into Zenodo and thus empowers research communities to create self-sustained cross-platform ecosystems. The BiCIKL project (Biodiversity Community Integrated Knowledge Library) exemplifies how repositories and tools can become building blocks for broader adoption of the FAIR principles. Starting with the above literature processing pipeline, the concepts of and resulting FAIR data, with a focus on the custom metadata used to enhance the deposits, will be explained.

Semantic Search in Legacy Biodiversity Literature: Integrating data from different data infrastructures

Nowadays, obtaining information by entering queries into a web search engine is routine behaviour. With its search portal, the Specialised Information Service Biodiversity Research (BIOfid) adapts the exploration of legacy biodiversity literature and data extraction to current standards (Driller et al. 2020). In this presentation, we introduce the BIOfid search portal and its functionalities in a How-To short guide. To this end, we adapted a knowledge graph representation of our thematic focus of Central European, primarily German language, biodiversity literature of the 19th and 20th centuries. Now, users can search our text-mined corpus containing to date more than 8.700 full-text articles from 68 journals, and particularly focussing on birds, lepidopterans and vascular plants. The texts are automatically preprocessed by the Natural Language Processing provider TextImager (Hemati et al. 2016) and will be linked to various databases such as Wikidata, Wikipedia, the Global Biodiversity Information Facility (GBIF), Encyclopedia of Life (EoL), Geonames, the Integrated Authority File (GND) and WordNet. For data retrieval, users can filter search results and download the article metadata as well as text annotations and database links in JavaScript Object Notation (JSON) format. For example, literature that mentions taxa from certain decades or co-occurrences of species can be searched. Our search engine recognises scientific and vernacular taxon names based on the GBIF Backbone Taxonomy and offers search suggestions to support the user. The semantic network of the BIOfid search portal is also enriched with data from the EoL trait bank, so that trait data can be included in the search queries. Thus, scientists can enhance their own data sets with the search results and feed them into the relevant biodiversity data repositories to sustainably expand the corresponding knowledge graphs with reliable data. Since BIOfid applies standard ontology terms, all data mobilized from literature can be combined with data on natural history collection objects or data from current research projects in order to generate more comprehensive knowledge. Furthermore, taxonomy, ecology and trait ontologies that have been built or extended within this project will be made available through appropriate platforms such as The Open Biological and Biomedical Ontology (OBO) Foundry and the Terminology Service of The German Federation for Biological Data (GFBio).

Towards Interlinked FAIR Biodiversity Knowledge: The BiCIKL perspective

The Horizon 2020 project Biodiversity Community Integrated Knowledge Library (BiCIKL) (started 1st of May 2021, duration 3 years) will build a new European community of key research infrastructures, researchers, citizen scientists and other stakeholders in biodiversity and life sciences. Together, the BiCIKL 14 partners will solidify open science practices by providing access to data, tools and services at each stage of, and along the entire biodiversity research and data life cycle (specimens, sequences, taxon names, analytics, publications, biodiversity knowledge graph) (Fig. 1, see also the BiCIKL kick-off presentation through Suppl. material 1), in compliance with the FAIR (Findable, Accessible, Interoperable and Reusable) data principles. The existing services provided by the participating infrastructures will expand through development and adoption of shared, common or interoperable domain standards, resulting in liberated and enhanced flows of data and knowledge across these domains. BiCIKL puts a special focus on the biodiversity literature. Over the span of the project, BiCIKL will develop new methods and workflows for semantic publishing and integrated access to harvesting, liberating, linking, and re-using sub-article-level data extracted from literature (i.e., specimens, material citations, sequences, taxonomic names, taxonomic treatments, figures, tables). Data linkages may be realised with different technologies (e.g., data warehousing, linking between FAIR Data Objects, Linked Open Data) and can be bi-lateral (between two data infrastructures) or multi-lateral (among multiple data infrastructures). The main challenge of BiCIKL is to design, develop and implement a FAIR Data Place (FDP), a central tool for search, discovery and management of interlinked FAIR data across different domains. The key final output of BiCIKL will the future Biodiversity Knowledge Hub (BKH), a one-stop portal, providing access to the BiCIKL services, tools and workflows, beyond the lifetime of the project.

#RetroPIDs: The missing link to the foundation of biodiversity knowledge

The Biodiversity Heritage Library (BHL) will soon upload its 60 millionth page of open access biodiversity literature onto the BHL website and the BHL's Internet Archive Collection. The BHL’s massive repository of free knowledge includes content that is available nowhere else online, as well as accessible versions of content that are locked behind paywalls elsewhere. If we are to continue to expand our understanding of life on Earth, we must ensure that the foundation of biodiversity knowledge provided by BHL is discoverable by the tools we rely on to navigate the ever-expanding internet. These tools – search engines and their algorithms – preferentially deliver (and rank) content with good metadata and persistent identifiers (PIDs). In modern online publishing, PID assignment and linking happens at the point of publication: DOIs (Digital Object Identifiers) for publications, ORCIDs (Open Researcher and Contributor IDs) for people, and RORs (Research Organization Registry IDs) for organisations. The DOI system provided by Crossref (the DOI registration agency for scholarly content) delivers reciprocal citations, enabling convenient clicking from article to article, and citation tracking, enabling authors and institutions to track the impact and reach of their research output. Publications that lack PIDs, which include the vast majority of legacy literature, are hard to find and sit outside the linked network of scholarly research. This makes it nearly impossible to determine whether they are being cited, let alone viewed, mentioned, shared or liked. At TDWG 2020, Page 2020, Kearney 2020, Richard 2020 (and 2019, Page 2019b, Page 2019a, Kearney 2019b, Kearney 2019a and 2018, Kearney 2018), we emphasised the need to bring the historic biodiversity literature into the modern linked network of scholarly research. In October 2020, BHL launched a new working group to do exactly this. The BHL Persistent Identifier Working Group (Team #RetroPID) brings together expertise from across BHL’s global community. Over the past year, we have worked tirelessly to make it easier to find, cite, link, share and track the content on BHL, adding article-level metadata to journals and retrospectively assigning DOIs (#RetroPIDs). Most importantly, we have developed the tools and documentation that will enable the entire BHL community to take contributed content from “just” accessible to persistently discoverable. This paper will detail our efforts to retrofit the historic literature (a square peg) into the modern PID system (a round hole) and will present both the achievements and the challenges of this important work.

Algorithms for connecting scientific names with literature in the Biodiversity Heritage Library via the Global Names Project and Catalogue of Life

Being able to quickly find and access original species descriptions is essential for efficiently conducting taxonomic research. Linking scientific name queries to the original species description is challenging and requires taxonomic intelligence because on average there are an estimated three scientific names associated with each currently accepted species, and many historical scientific names have fallen into disuse from being synonymized or forgotten. Additionally, non-standard usage of journal abbreviations can make it difficult to automatically disambiguate bibliographic citations and ascribe them to the correct publication. The largest open access resource for biodiversity literature is the Biodiversity Heritage Library (BHL), which was built by a consortium of natural history institutions and contains over 200,000 digitized volumes of natural history publications spanning hundreds of years of biological research. Catalogue of Life (CoL) is the largest aggregator of scientific names globally, publishing an annual checklist of currently accepted scientific names and their historical synonyms. TaxonWorks is an integrative web-based workbench that facilitates collaboration on biodiversity informatics research between scientists and developers. The Global Names project has been collaborating with BHL, TaxonWorks, and CoL to develop a Global Names Index that links all of these services together by finding scientific names in BHL and using the taxonomic intelligence provided by CoL to conveniently link directly to the page referenced in BHL. The Global Names Index is continuously updated as metadata is improved and digitization technologies advance to provide more accurate optical character recognition (OCR) of scanned texts. We developed an open source tool, “BHLnames,” and launched a restful application programming interface (API) service with a freely available Javascript widget that can be embedded on any website to link scientific names to literature citations in BHL. If no bibliographic citation is provided, the widget will link to the oldest name usage in BHL, which often is the original species description. The BHLnames widget can also be used to browse all mentions of a scientific name and its synonyms in BHL, which could make the tool more broadly useful for studying the natural history of any species.

Biodiversity at the global scale: the synthesis continues.

Traditionally, the generation and use of biodiversity data and their associated specimen objects have been primarily the purview of individuals and small research groups. While deposition of data and specimens in herbaria and other repositories has long been the norm, throughout most of their history, these resources have been accessible only to a small community of specialists. Through recent concerted efforts, primarily at the level of national and international governmental agencies over the last two decades, the pace of biodiversity data accumulation has accelerated, and a wider array of biodiversity scientists has gained access to this massive accumulation of resources, applying them to an ever-widening compass of research pursuits. We review how these new resources and increasing access to them are affecting the landscape of biodiversity research in plants today, focusing on new applications across evolution, ecology, and other fields that have been enabled specifically by the availability of these data and the global scope that was previously beyond the reach of individual investigators. We give an overview of recent advances organized along three lines: broad-scale analyses of distributional data and spatial information, phylogenetic research circumscribing large clades with comprehensive taxon sampling, and data sets derived from improved accessibility of biodiversity literature. We also review synergies between large data resources and more traditional data collection paradigms, describe shortfalls and how to overcome them, and reflect on the future of plant biodiversity analyses in light of increasing linkages between data types and scientists in our field.

Using taxonomic treatments to assess an author's career: the impactful Jocélia Grazia.

Here we present a descriptive analysis of the bibliographic production of the world-renowned heteropterist Dr. Jocélia Grazia and comments on her taxonomic reach based on extracted taxonomic treatments. We analyzed a total of 219 published documents, including scientific papers, scientific notes, and book chapters. Additionally, we applied the Plazi workflow to extract taxonomic treatments, images, tables, treatment citations and materials citations, and references from 75 different documents in accordance with the FAIR (Findability, Accessibility, Interoperability, and Reuse) principles and made them available on the Biodiversity Literature Repository (BLR), hosted on Zenodo, and on TreatmentBank. We found that Dr. Grazia published 200 new names, including species (183) and genera (17), and 1,444 taxonomic treatments in total. From these, 104 and 581, respectively, were extracted after applying the Plazi Workflow. A total of 544 figures, 50 tables, 2,242 references, 2,107 materials citations, and 1,101 treatment citations were also extracted. In order to make her publications properly citable and accessible, we assigned DOIs (Digital Object Identifiers) for all publications that lacked this persistent identifier, including those that were not processed (88 in total), therefore enhancing the open-access share of her publications.

Disturbance Effects on Spatial Autocorrelation in Biodiversity: An Overview and a Call for Study

The spatially autocorrelated patterns of biodiversity can be an important determinant of ecological processes, functions and delivery of services across spatial scales. Therefore, understanding disturbance effects on spatial autocorrelation in biodiversity is crucial for conservation and restoration planning but remains unclear. In a survey of disturbance versus spatial patterns of biodiversity literature from forests, grasslands and savannah ecosystems, we found that habitat disturbances generally reduce the spatial autocorrelation in species diversity on average by 15.5% and reduce its range (the distance up to which autocorrelation prevails) by 21.4%, in part, due to disturbance-driven changes in environmental conditions, dispersal, species interactions, or a combination of these processes. The observed effect of disturbance, however, varied markedly among the scale of disturbance (patch-scale versus habitat-scale). Surprisingly, few studies have examined disturbance effects on the spatial patterns of functional diversity, and the overall effect was non-significant. Despite major knowledge gaps in certain areas, our analysis offers a much-needed initial insights into the disturbance-driven changes in the spatial patterns of biodiversity, thereby setting the ground for informed discussion on conservation and promotion of spatial heterogeneity in managing natural systems under a changing world.

Corporate Accountability Towards Species Extinction Protection: Insights from Ecologically Forward-Thinking Companies

This paper contributes to biodiversity and species extinction literature by examining the relationship between corporate accountability in terms of species protection and factors affecting such accountability from forward-thinking companies. We use triangulation of theories, namely deep ecology, legitimacy, and we introduce a new perspective to the stakeholder theory that considers species as a ‘stakeholder’. Using Poisson pseudo-maximum likelihood (PPML) regression, we examine a sample of 200 Fortune Global companies over 3 years. Our results indicate significant positive relations between ecologically conscious companies that are accountable for the protection of biodiversity and species extinction and external assurance, environmental performance, partnerships with socially responsible organizations and awards for sustainable activities. Our empirical results appear to be robust in controlling for possible endogeneities. Our findings contribute to the discussion on the concern of species loss and habitat destruction in the context of corporate accountability, especially in responding to the sixth mass extinction event and COVID-19 crisis. Our results can also guide the policymakers and stakeholders of the financial market in better decision making.

Liberating Biodiversity Data From COVID-19 Lockdown: Toward a knowledge hub for mammal host-virus information

A deep irony of COVID-19 likely originating from a bat-borne coronavirus (Boni et al. 2020) is that the global lockdown to quell the pandemic also locked up physical access to much basic knowledge regarding bat biology. Digital access to data on the ecology, geography, and taxonomy of potential viral reservoirs, from Southeast Asian horseshoe bats and pangolins to North American deer mice, was suddenly critical for understanding the disease's emergence and spread. However, much of this information lay inside rare books and personal files rather than as open, linked, and queryable resources on the internet. Even the world's experts on mammal taxonomy and zoonotic disease could not retrieve their data from shuttered laboratories. We were caught unprepared. Why, in this digitally connected age, were such fundamental data describing life on Earth not already freely accessible online? Understanding why biodiversity science was unprepared—and how to fix it before the next pandemic—has been the focus of our COVID-19 Taskforce since April 2020 and is continuing (organized by CETAF and DiSSCo). We are a group of museum-based and academic scientists with the goal of opening the rich ecological data stored in natural history collections to the research public. This information is rooted in what may seem an unlikely location—taxonomic names and their historical usages, which are the keys for searching literature and extracting linked ecological data (Fig. 1). This has been the core motivation of our group, enabled by the pioneering efforts of Plazi (Agosti and Egloff 2009) to build tools for literature digitization, extraction, and parsing (e.g., Synospecies, Ocellus) without which biodiversity science would be even less prepared. Our group led efforts to build an additional pipeline from Plazi to the Biodiversity Literature Repository at Zenodo, a free and unlimited data repository (Agosti et al. 2019), and then to GloBI, an open-source database of biotic interactions (Poelen et al. 2014, GloBI 2020). We also developed a direct integration from Pensoft Journals to GloBI, leveraging that publisher’s indexing of computer-readable terms (called semantic metadata; Senderov et al. 2018) to extract mammal host and virus information. Overall, considerable progress was made. In total, 85,492 new interactions were added to GloBI from 14 April to 21 May 2020 (see entire dataset on Zenodo: Poelen et al. 2020). Of those, 28,839 interactions are present when subset to "hasHost", "hostOf", "pathogenOf", "virus", and 4,101 unique name combinations are present after considering mammal species synonymies (from Meyer et al. 2015). Of those interactions, 892 species of mammals and 1,530 unique virus names are involved, which compares to 754 mammals and 586 viruses in the most recent data synthesis (Olival et al. 2017). While these liberated data may still include redundancies, they demonstrate the value of our approach and the expanse of known but digitally unconnected data that remains locked in publications. We can liberate host-virus data from publications, but doing so is expensive and does not scale to the continued influx of new articles that are inadequately digitized. Our efforts make it clear that Pensoft-style semantic publishing should be expanded to all major journals. The pandemic has created an opportunity for re-thinking the way we do science in the digital age. Thankfully, our future is not the past, so we do not have to keep wasting resources to digitially 'rediscover' biodiversity knowledge. We collectively call for changes to the publishing paradigm, so that research findings are directly accessible, citable, discoverable, and reusable for creating complete forms of digital knowledge.