OpenBiodiv is a biodiversity database containing knowledge extracted from scientific literature, built as an Open Biodiversity Knowledge Management System.
Apart from coordinating the Horizon 2020-funded project BiCIKL, scholarly publisher and technology provider Pensoft has been the engine behind what is likely to be the first production-stage semantic system to run on top of a reasonably-sized biodiversity knowledge graph.
OpenBiodiv is a biodiversity database containing knowledge extracted from scientific literature, built as an Open Biodiversity Knowledge Management System.
As of February 2023, OpenBiodiv contains 36,308 processed articles; 69,596 taxon treatments; 1,131 institutions; 460,475 taxon names; 87,876 sequences; 247,023 bibliographic references; 341,594 author names; and 2,770,357 article sections and subsections.
In fact, OpenBiodiv is a whole ecosystem comprising tools and services that enable biodiversity data to be extracted from the text of biodiversity articles published in data-minable XML format, as in the journals published by Pensoft (e.g. ZooKeys, PhytoKeys, MycoKeys, Biodiversity Data Journal), and other taxonomic treatments – available from Plazi and Plazi’s specialised extraction workflow – into Linked Open Data.
“I believe that OpenBiodiv is a good real-life example of how the outputs and efforts of a research project may and should outlive the duration of the project itself. Something that is – of course – central to our mission at BiCIKL.”
explains Prof Lyubomir Penev, BiCIKL’s Project Coordinator and founder and CEO of Pensoft.
“The basics of what was to become the OpenBiodiv database began to come together back in 2015 within the EU-funded BIG4 PhD project of Victor Senderov, later succeeded by another PhD project by Mariya Dimitrova within IGNITE. It was during those two projects that the backend Ontology-O, the first versions of RDF converters and the basic website functionalities were created,”
he adds.
At the time OpenBiodiv became one of the nine research infrastructures within BiCIKL tasked with the provision of virtual access to open FAIR data, tools and services, it had already evolved into a RDF-based biodiversity knowledge graph, equipped with a fully automated extraction and indexing workflow and user apps.
Currently, Pensoft is working at full speed on new user apps in OpenBiodiv, as the team is continuously bringing into play invaluable feedback and recommendation from end-users and partners at BiCIKL.
As a result, OpenBiodiv is already capable of answering open-ended queries based on the available data. To do this, OpenBiodiv discovers ‘hidden’ links between data classes, i.e. taxon names, taxon treatments, specimens, sequences, persons/authors and collections/institutions.
Thus, the system generates new knowledge about taxa, scientific articles and their subsections, the examined materials and their metadata, localities and sequences, amongst others. Additionally, it is able to return information with a relevant visual representation about any one or a combination of those major data classes within a certain scope and semantic context.
Users can explore the database by either typing in any term (even if misspelt!) in the search engine available from the OpenBiodiv homepage; or integrating an Application Programming Interface (API); as well as by using SPARQL queries.
On the OpenBiodiv website, there is also a list of predefined SPARQL queries, which is continuously being expanded.
“OpenBiodiv is an ambitious project of ours, and it’s surely one close to Pensoft’s heart, given our decades-long dedication to biodiversity science and knowledge sharing. Our previous fruitful partnerships with Plazi, BIG4 and IGNITE, as well as the current exciting and inspirational network of BiCIKL are wonderful examples of how far we can go with the right collaborators,”
The FAIR Data Place – the key and final product of the partnership – is meant to provide scientists with all types of biodiversity data “at their fingertips”
The Horizon 2020 – funded project BiCIKL has reached its halfway stage and the partners gathered in Plovdiv (Bulgaria) from the 22nd to the 25th of October for the Second General Assembly, organised by Pensoft.
The BiCIKL project will launch a new European community of key research infrastructures, researchers, citizen scientists and other stakeholders in the biodiversity and life sciences based on open science practices through access to data, tools and services.
BiCIKL’s goal is to create a centralised place to connect all key biodiversity data by interlinking 15 research infrastructures and their databases. The 3-year European Commission-supported initiative kicked off in 2021 and involves 14 key natural history institutions from 10 European countries.
BiCIKL is keeping pace as expected with 16 out of the 48 final deliverables already submitted, another 9 currently in progress/under review and due in a few days. Meanwhile, 21 out of the 48 milestones have been successfully achieved.
Prof. Lyubomir Penev (BiCIKL’s project coordinator Prof. Lyubomir Penev and CEO and founder of Pensoft) opens the 2nd General Assembly of BiCIKL in Plovdiv, Bulgaria.
The hybrid format of the meeting enabled a wider range of participants, which resulted in robust discussions on the next steps of the project, such as the implementation of additional technical features of the FAIR Data Place (FAIR being an abbreviation for Findable, Accessible, Interoperable and Reusable).
This FAIR Data Place online platform – the key and final product of the partnership and the BiCIKL initiative – is meant to provide scientists with all types of biodiversity data “at their fingertips”.
This data includes biodiversity information, such as detailed images, DNA, physiology and past studies concerning a specific species and its ‘relatives’, to name a few. Currently, the issue is that all those types of biodiversity data have so far been scattered across various databases, which in turn have been missing meaningful and efficient interconnectedness.
Additionally, the FAIR Data Place, developed within the BiCIKL project, is to give researchers access to plenty of training modules to guide them through the different services.
Halfway through the duration of BiCIKL, the project is at a turning point, where crucial discussions between the partners are playing a central role in the refinement of the FAIR Data Place design. Most importantly, they are tasked with ensuring that their technologies work efficiently with each other, in order to seamlessly exchange, update and share the biodiversity data every one of them is collecting and taking care of.
By Year 3 of the BiCIKL project, the partners agree, when those infrastructures and databases become efficiently interconnected to each other, scientists studying the Earth’s biodiversity across the world will be in a much better position to build on existing research and improve the way and the pace at which nature is being explored and understood. At the end of the day, knowledge is the stepping stone for the preservation of biodiversity and humankind itself.
The Biodiversity Knowledge Hub is no longer existing on paper only! We are opening the 2nd day of the #BiCIKL_H2020 General Assembly looking at the prototype of the BKH created by the @LifeWatchERIC team. It's so exciting to see projects taking shape! 🤩 #Plovdivpic.twitter.com/RidzwBpxZx
“Needless to say, it’s an honour and a pleasure to be the coordinator of such an amazing team spanning as many as 14 partnering natural history and biodiversity research institutions from across Europe, but also involving many global long-year collaborators and their infrastructures, such as Wikidata, GBIF, TDWG, Catalogue of Life to name a few,”
said BiCIKL’s project coordinator Prof. Lyubomir Penev, CEO and founder of Pensoft.
“I see our meeting in Plovdiv as a practical demonstration of our eagerness and commitment to tackle the long-standing and technically complex challenge of breaking down the silos in the biodiversity data domain. It is time to start building freeways between all biodiversity data, across (digital) space, time and data types. After the last three days that we spent together in inspirational and productive discussions, I am as confident as ever that we are close to providing scientists with much more straightforward routes to not only generate more biodiversity data, but also build on the already existing knowledge to form new hypotheses and information ready to use by decision- and policy-makers. One cannot stress enough how important the role of biodiversity data is in preserving life on Earth. These data are indeed the groundwork for all that we know about the natural world”
Prof. Lyubomir Penev added.
Christos Arvanitidis (CEO of LifeWatch ERIC) at the 2nd General Assembly of the BiCIKL project.
“The point is: do we want an integrated structure or do we prefer federated structures? What are the pros and cons of the two options? It’s essential to keep the community united and allied because we can’t afford any information loss and the stakeholders should feel at home with the Project and the Biodiversity Knowledge Hub.”
Joe Miller, Executive Secretary and Director at GBIF, commented:
“We are a brand new community, and we are in the middle of the growth process. We would like to already have answers, but it’s good to have this kind of robust discussion to build on a good basis. We must find the best solution to have linkages between infrastructures and be able to maintain them in the future because the Biodiversity Knowledge Hub is the location to gather the community around best practices, data and guidelines on how to use the BiCIKL services… In order to engage even more partners to fill the eventual gaps in our knowledge.”
Joana Pauperio (biodiversity curator at EMBL-EBI) atthe 2nd General Assembly of the BiCIKL project.
“BiCIKL is leading data infrastructure communities through some exciting and important developments”
said Dr Guy Cochrane, Team Leader for Data Coordination and Archiving and Head of the European Nucleotide Archive at EMBL’s European Bioinformatics Institute (EMBL-EBI).
“In an era of biodiversity change and loss, leveraging scientific data fully will allow the world to catalogue what we have now, to track and understand how things are changing and to build the tools that we will use to conserve or remediate. The challenge is that the data come from many streams – molecular biology, taxonomy, natural history collections, biodiversity observation – that need to be connected and intersected to allow scientists and others to ask real questions about the data. In its first year, BiCIKL has made some key advances to rise to this challenge,”
“As a partner, we, at the Biodiversity Information Standards – TDWG, are very enthusiastic that our standards are implemented in BiCIKL and serve to link biodiversity data. We know that joining forces and working together is crucial to building efficient infrastructures and sharing knowledge.”
The project will go on with the first Round Table of experts in December and the publications of the projects who participated in the Open Call and will be founded at the beginning of the next year.
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Learn more about BiCIKL on the project’s website at: bicikl-project.eu
The purpose of this call is to solicit, select and implement four to six biodiversity data-related scientific projects that will make use of the added value services developed by the leading Research Infrastructures that make the BiCIKL project.
The BiCIKL project invites submissions of Expression of Interest (EoI) to the First BiCIKL Open Call for projects. The purpose of this call is to solicit, select and implement four to six biodiversity data-related scientific projects that will make use of the added value services developed by the leading Research Infrastructures that make the BiCIKL project.
By opening this call, BiCIKL aims to better understand how it could support scientific questions that arise from across the biodiversity world in the future, while addressing specific scientific or technical biodiversity data challenges presented by the applicants.
We need and want to assess real-world problems and make the best possible use of our data and technical capabilities. This will greatly assist in defining the long-term development goals of the participating Research Infrastructures and improve the way they can technically and operationally work together to deliver greater scientific value.
explain the project partners.
The BiCIKL project – a Horizon 2020-funded project involving 14 European institutions, representing major global players in biodiversity research and natural history, and coordinated by Pensoft – establishes a European starting community of key research infrastructures, researchers, citizen scientists and other biodiversity and life sciences stakeholders based on open science practices through access to data, tools and services.
Within Biodiversity Community Integrated Knowledge Library (BiCIKL), 14 key research and natural history institutions commit to link infrastructures and technologies to provide flawless access to biodiversity data.
In a recently started Horizon 2020-funded project, 14 European institutions from 10 countries, representing both the continent’s and global key players in biodiversity research and natural history, deploy and improve their own and partnering infrastructures to bridge gaps between each other’s biodiversity data types and classes. By linking their technologies, they are set to provide flawless access to data across all stages of the research cycle.
Three years in, BiCIKL (abbreviation for Biodiversity Community Integrated Knowledge Library) will have created the first-of-its-kind Biodiversity Knowledge Hub, where a researcher will be able to retrieve a full set of linked and open biodiversity data, thereby accessing the complete story behind an organism of interest: its name, genetics, occurrences, natural history, as well as authors and publications mentioning any of those.
Ultimately, the project’s products will solidify Open Science and FAIR (Findable, Accessible, Interoperable and Reusable) data practices by empowering and streamlining biodiversity research.
Together, the project partners will redesign the way biodiversity data is found, linked, integrated and re-used across the research cycle. By the end of the project, BiCIKL will provide the community with a more transparent, trustworthy and efficient highly automated research ecosystem, allowing for scientists to access, explore and put into further use a wide range of data with only a few clicks.
“In recent years, we’ve made huge progress on how biodiversity data is located, accessed, shared, extracted and preserved, thanks to a vast array of digital platforms, tools and projects looking after the different types of data, such as natural history specimens, species descriptions, images, occurrence records and genomics data, to name a few. However, we’re still missing an interconnected and user-friendly environment to pull all those pieces of knowledge together. Within BiCIKL, we all agree that it’s only after we puzzle out how to best bridge our existing infrastructures and the information they are continuously sourcing that future researchers will be able to realise their full potential,”
explains BiCIKL’s project coordinator Prof. Lyubomir Penev, CEO and founder of Pensoft, a scholarly publisher and technology provider company.
Continuously fed with data sourced by the partnering institutions and their infrastructures, BiCIKL’s key final output: the Biodiversity Knowledge Hub, is set to persist with time long after the project has concluded. On the contrary, by accelerating biodiversity research that builds on – rather than duplicates – existing knowledge, it will in fact be providing access to exponentially growing contextualised biodiversity data.
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Learn more about BiCIKL on the project’s website at: bicikl-project.eu
by Mariya Dimitrova, Jorrit Poelen, Georgi Zhelezov, Teodor Georgiev, Lyubomir Penev
Fig. 1. Pensoft-GloBI workflow for indexing biotic interactions from scholarly literature
Tables published in scholarly literature are a rich source of primary biodiversity data. They are often used for communicating species occurrence data, morphological characteristics of specimens, links of species or specimens to particular genes, ecology data and biotic interactions between species, etc. Tables provide a structured format for sharing numerous facts about biodiversity in a concise and clear way.
Inspired by the potential use of semantically-enhanced tables for text and data mining, Pensoft and Global Biotic Interactions (GloBI) developed a workflow for extracting and indexing biotic interactions from tables published in scholarly literature. GloBI is an open infrastructure enabling the discovery and sharing of species interaction data. GloBI ingests and accumulates individual datasets containing biotic interactions and standardises them by mapping them to community-accepted ontologies, vocabularies and taxonomies. Data integrated by GloBI is accessible through an application programming interface (API) and as archives in different formats (e.g. n-quads). GloBI has indexed millions of species interactions from hundreds of existing datasets spanning over a hundred thousand taxa.
The workflow
First, all tables extracted from Pensoft publications and stored in the OpenBiodiv triple store were automatically retrieved (Step 1 in Fig. 1). There were 6993 tables from 21 different journals. To identify only the tables containing biotic interactions, we used an ontology annotator, currently developed by Pensoft using terms from the OBO Relation Ontology (RO). The Pensoft Annotator analyses free text and finds words and phrases matching ontology term labels.
We used the RO to create a custom ontology, or list of terms, describing different biotic interactions (e.g. ‘host of’, ‘parasite of’, ‘pollinates’) (Step 2 in Fig. 1).. We used all subproperties of the RO term labeled ‘biotically interacts with’ and expanded the list of terms with additional word spellings and variations (e.g. ‘hostof’, ‘host’) which were added to the custom ontology as synonyms of already existing terms using the property oboInOwl:hasExactSynonym.
This custom ontology was used to perform annotation of all tables via the Pensoft Annotator (Step 3 in Fig. 1). Tables were split into rows and columns and accompanying table metadata (captions). Each of these elements was then processed through the Pensoft Annotator and if a match from the custom ontology was found, the resulting annotation was written to a MongoDB database, together with the article metadata. The original table in XML format, containing marked-up taxa, was also stored in the records.
Thus, we detected 233 tables which contain biotic interactions, constituting about 3.4% of all examined tables. The scripts used for parsing the tables and annotating them, together with the custom ontology, are open source and available on GitHub. The database records were exported as json to a GitHub repository, from where they could be accessed by GloBI.
GloBI processed the tables further, involving the generation of a table citation from the article metadata and the extraction of interactions between species from the table rows (Step 4 in Fig. 1). Table citations were generated by querying the OpenBiodiv database with the DOI of the article containing each table to obtain the author list, article title, journal name and publication year. The extraction of table contents was not a straightforward process because tables do not follow a single schema and can contain both merged rows and columns (signified using the ‘rowspan’ and ‘colspan’ attributes in the XML). GloBI were able to index such tables by duplicating rows and columns where needed to be able to extract the biotic interactions within them. Taxonomic name markup allowed GloBI to identify the taxonomic names of species participating in the interactions. However, the underlying interaction could not be established for each table without introducing false positives due to the complicated table structures which do not specify the directionality of the interaction. Hence, for now, interactions are only of the type ‘biotically interacts with’ (Fig. 2) because it is a bi-directional one (e.g. ‘Species A interacts with Species B’ is equivalent to ‘Species B interacts with Species A’).
Fig. 2. Example of a biotic interaction indexed by GloBI.
Examples of species interactions provided by OpenBiodiv and indexed by GloBI are available on GloBI’s website.
In the future we plan to expand the capacity of the workflow to recognise interaction types in more detail. This could be implemented by applying part of speech tagging to establish the subject and object of an interaction.
In addition to being accessible via an API and as archives, biotic interactions indexed by GloBI are available as Linked Open Data and can be accessed via a SPARQL endpoint. Hence, we plan on creating a user-friendly service for federated querying of GloBI and OpenBiodiv biodiversity data.
This collaborative project is an example of the benefits of open and FAIR data, enabling the enhancement of biodiversity data through the integration between Pensoft and GloBI. Transformation of knowledge contained in existing scholarly works into giant, searchable knowledge graphs increases the visibility and attributed re-use of scientific publications.
Tables published in scholarly literature are a rich source of primary biodiversity data. They are often used for communicating species occurrence data, morphological characteristics of specimens, links of species or specimens to particular genes, ecology data and biotic interactions between species etc. Tables provide a structured format for sharing numerous facts about biodiversity in a concise and clear way.
Inspired by the potential use of semantically-enhanced tables for text and data mining, Pensoft and Global Biotic Interactions (GloBI) developed a workflow for extracting and indexing biotic interactions from tables published in scholarly literature. GloBI is an open infrastructure enabling the discovery and sharing of species interaction data. GloBI ingests and accumulates individual datasets containing biotic interactions and standardises them by mapping them to community-accepted ontologies, vocabularies and taxonomies. Data integrated by GloBI is accessible through an application programming interface (API) and as archives in different formats (e.g. n-quads). GloBI has indexed millions of species interactions from hundreds of existing datasets spanning over a hundred thousand taxa.
The workflow
First, all tables extracted from Pensoft publications and stored in the OpenBiodiv triple store were automatically retrieved (Step 1 in Fig. 1). There were 6,993 tables from 21 different journals. To identify only the tables containing biotic interactions, we used an ontology annotator, currently developed by Pensoft using terms from the OBO Relation Ontology (RO). The Pensoft Annotator analyses free text and finds words and phrases matching ontology term labels.
We used the RO to create a custom ontology, or list of terms, describing different biotic interactions (e.g. ‘host of’, ‘parasite of’, ‘pollinates’) (Step 1 in Fig. 1). We used all subproperties of the RO term labeled ‘biotically interacts with’ and expanded the list of terms with additional word spellings and variations (e.g. ‘hostof’, ‘host’) which were added to the custom ontology as synonyms of already existing terms using the property oboInOwl:hasExactSynonym.
This custom ontology was used to perform annotation of all tables via the Pensoft Annotator (Step 3 in Fig. 1). Tables were split into rows and columns and accompanying table metadata (captions). Each of these elements was then processed through the Pensoft Annotator and if a match from the custom ontology was found, the resulting annotation was written to a MongoDB database, together with the article metadata. The original table in XML format, containing marked-up taxa, was also stored in the records.
Thus, we detected 233 tables which contain biotic interactions, constituting about 3.4% of all examined tables. The scripts used for parsing the tables and annotating them, together with the custom ontology, are open source and available on GitHub. The database records were exported as JSON to a GitHub repository, from where they could be accessed by GloBI.
GloBI processed the tables further, involving the generation of a table citation from the article metadata and the extraction of interactions between species from the table rows (Step 4 in Fig. 1). Table citations were generated by querying the OpenBiodiv database with the DOI of the article containing each table to obtain the author list, article title, journal name and publication year. The extraction of table contents was not a straightforward process because tables do not follow a single schema and can contain both merged rows and columns (signified using the ‘rowspan’ and ‘colspan’ attributes in the XML). GloBI were able to index such tables by duplicating rows and columns where needed to be able to extract the biotic interactions within them. Taxonomic name markup allowed GloBI to identify the taxonomic names of species participating in the interactions. However, the underlying interaction could not be established for each table without introducing false positives due to the complicated table structures which do not specify the directionality of the interaction. Hence, for now, interactions are only of the type ‘biotically interacts with’ because it is a bi-directional one (e.g. ‘Species A interacts with Species B’ is equivalent to ‘Species B interacts with Species A’).
In the future, we plan to expand the capacity of the workflow to recognise interaction types in more detail. This could be implemented by applying part of speech tagging to establish the subject and object of an interaction.
In addition to being accessible via an API and as archives, biotic interactions indexed by GloBI are available as Linked Open Data and can be accessed via a SPARQL endpoint. Hence, we plan on creating a user-friendly service for federated querying of GloBI and OpenBiodiv biodiversity data.
This collaborative project is an example of the benefits of open and FAIR data, enabling the enhancement of biodiversity data through the integration between Pensoft and GloBI. Transformation of knowledge contained in existing scholarly works into giant, searchable knowledge graphs increases the visibility and attributed re-use of scientific publications.
References
Jorrit H. Poelen, James D. Simons and Chris J. Mungall. (2014). Global Biotic Interactions: An open infrastructure to share and analyze species-interaction datasets. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2014.08.005.
Additional Information
The work has been partially supported by the International Training Network (ITN) IGNITE funded by the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 764840.
A colony of what is apparently a new species of the genus Hipposideros found in an abandoned gold mine in Western Kenya Photo by B. D. Patterson / Field Museum
Newly published findings about the phylogenetics and systematics of some previously known, but also other yet to be identified species of Old World Leaf-nosed bats, provide the first contribution to a recently launched collection of research articles, whose task is to help scientists from across disciplines to better understand potential hosts and vectors of zoonotic diseases, such as the Coronavirus. Bats and pangolins are among the animals already identified to be particularly potent vehicles of life-threatening viruses, including the infamous SARS-CoV-2.
The article, publicly available in the peer-reviewed scholarly journal ZooKeys, also pilots a new generation of Linked Open Data (LOD) publishing practices, invented and implemented to facilitate ongoing scientific collaborations in times of urgency like those we experience today with the COVID-19 pandemic currently ravaging across over 230 countries around the globe.
In their study, an international team of scientists, led by Dr Bruce Patterson, Field Museum‘s MacArthur curator of mammals, point to the existence of numerous, yet to be described species of leaf-nosed bats inhabiting the biodiversity hotspots of East Africa and Southeast Asia. In order to expedite future discoveries about the identity, biology and ecology of those bats, they provide key insights into the genetics and relations within their higher groupings, as well as further information about their geographic distribution.
“Leaf-nosed bats carry coronaviruses–not the strain that’s affecting humans right now, but this is certainly not the last time a virus will be transmitted from a wild mammal to humans. If we have better knowledge of what these bats are, we’ll be better prepared if that happens,”
says Dr Terrence Demos, a post-doctoral researcher in Patterson’s lab and a principal author of the paper.
One of the possibly three new to science bat species, previously referred to as Hipposideros caffer or Sundevall’s leaf-nosed bat Photo by B. D. Patterson / Field Museum
“With COVID-19, we have a virus that’s running amok in the human population. It originated in a horseshoe bat in China. There are 25 or 30 species of horseshoe bats in China, and no one can determine which one was involved. We owe it to ourselves to learn more about them and their relatives,”
comments Patterson.
In order to ensure that scientists from across disciplines, including biologists, but also virologists and epidemiologists, in addition to health and policy officials and decision-makers have the scientific data and evidence at hand, Patterson and his team supplemented their research publication with a particularly valuable appendix table. There, in a conveniently organized table format, everyone can access fundamental raw genetic data about each studied specimen, as well as its precise identification, origin and the natural history collection it is preserved. However, what makes those data particularly useful for researchers looking to make ground-breaking and potentially life-saving discoveries is that all that information is linked to other types of data stored at various databases and repositories contributed by scientists from anywhere in the world.
Furthermore, in this case, those linked and publicly available data or Linked Open Data (LOD) are published in specific code languages, so that they are “understandable” for computers. Thus, when a researcher seeks to access data associated with a particular specimen he/she finds in the table, he/she can immediately access additional data stored at external data repositories by means of a single algorithm. Alternatively, another researcher might want to retrieve all pathogens extracted from tissues from specimens of a specific animal species or from particular populations inhabiting a certain geographical range and so on.
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The data publication and dissemination approach piloted in this new study was elaborated by the science publisher and technology provider Pensoft and the digitisation company Plazi for the purposes of a special collection of research papers reporting on novel findings concerning the biology of bats and pangolins in the scholarly journal ZooKeys. By targeting the two most likely ‘culprits’ at the roots of the Coronavirus outbreak in 2020: bats and pangolins, the article collection aligns with the agenda of the COVID-19 Joint Task Force, a recent call for contributions made by the Consortium of European Taxonomic Facilities (CETAF), the Distributed System for Scientific Collections (DiSSCo) and the Integrated Digitized Biocollections (iDigBio).
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Original source:
Patterson BD, Webala PW, Lavery TH, Agwanda BR, Goodman SM, Kerbis Peterhans JC, Demos TC (2020) Evolutionary relationships and population genetics of the Afrotropical leaf-nosed bats (Chiroptera, Hipposideridae). ZooKeys 929: 117-161. https://doi.org/10.3897/zookeys.929.50240
