Biodiversity Data Research Articles

Towards a Distributed System for Essential Variables for the Southern Ocean

The Southern Ocean (SO), delinated to the north by the Antarctic convergence, is a unique environment that experiences rapid change in some areas while remaining relatively untouched by human activities. At the same time, these ecosystems are under severe threat from climate change and other stressors. While our understanding of SO biological processes (e.g., species distributions, feeding ecology, reproduction) has greatly improved in recent years, biological data for the region remains patchy, sparse, and unstandardised depending on the taxonomic group (Griffiths et al. 2014). Due to the scarcity of standardised observations and data, it is difficult to model and predict SO ecosystem responses to climate change, which is often accompanied by other anthropogenic pressures, such as fishing and tourism. Understanding the dynamics and change in the SO necessitates a comprehensive system of observations, data management, scientific analysis, and ensuing policy recommendations. It should be built as much as feasible from current platforms and standards, and it should be visible, verifiable and shared in accordance with the FAIR (Findable, Accessible, Interoperable, and Reusable) principles (Van de Putte and Griffiths 2021). For this we need to identify the stakeholders' needs, sources of data, the algorithms for analysing the data and the infrastructure on which to run the algorithms (Benson and Brooks 2018). Existing synergistic methods for identifying selected variables for (life) monitoring include Essential Biodiversity Variables (EBVs; Pereira and Ferrier 2013), Essential Ocean Variables (EOVs; Miloslavich and Bax 2018), Essential Climate Variables (ECVs; Bojinski and Verstraete 2014), and ecosystem Essential Ocean Variables (eEOVs; Constable and Costa 2016). (For an overview see Muller-Karger and Miloslavich 2018.) These variables, can be integrated into the Southern Ocean Observation System (SOOS) and SOOSmap but also national or global systems (e.g., Group on Earth Observations-Biodiversty Observation Network (GEO-BON)). The resulting data products can in turn be used to inform policy makers. The use of Essential Variables (EVs) marks a significant step forward in the monitoring and assessment of SO ecosystems. However, these EVs will necessitate prioritising certain variables and data collection. Here we present the outcomes of a workshop organised in August 2023 that aimed to outline the set Essential Variables and workflows required for a distributed system that can translate biodiversity data (and environmental data) into policy-relevant data products. The goals of the workshop were: Create an inventory of EVs relevant for the Southern Ocean based on existing efforts by the GEO-BON and the Marine Biodiversity Observation Network (MBON). Identify data requirements and data gaps for calculating such EVs and prioritise EVs to work on. Identify existing workflows and tools. Develop a framework for developing the workflows required to turn public biodiversity data into relevant EVs. Create an inventory of EVs relevant for the Southern Ocean based on existing efforts by the GEO-BON and the Marine Biodiversity Observation Network (MBON). Identify data requirements and data gaps for calculating such EVs and prioritise EVs to work on. Identify existing workflows and tools. Develop a framework for developing the workflows required to turn public biodiversity data into relevant EVs.

An Australian Model of Cooperative Data Publishing to OBIS and GBIF

The Australian Commonwealth Science and Industrial Research Organisation (CSIRO) hosts both the Australian Ocean Biodiversity Information System (OBIS) and Global Biodiversity Information Facility (GBIF) nodes within the National Collections and Marine Infrastructure (NCMI) business unit. OBIS-AU is led by the NCMI Information and Data Centre and publishes marine biodiversity data in the Darwin Core (DwC) standard via an Integrated Publishing Toolkit (IPT), with over 450 marine datasets at present. The Australian GBIF node is hosted by a separate team at the Atlas of Living Australia (ALA), a national-scale biodiversity analytical and knowledge delivery portal. The ALA aggregates and publishes over 800 terrestrial and marine datasets from a wide variety of research institutes, museums and collections, governments and citizen science agencies, including OBIS-AU. Many OBIS-AU published datasets are harvested and republished by ALA and vice-versa. OBIS-AU identifies, performs Quality Control and formats marine biodiversity and observation data, then publishes directly to the OBIS international data repository and portal, using GBIF IPT technology. The ALA data processing pipeline harvests, aggregates and enhances datasets from many sources with authoritative taxonomic and spatial reference data before passing the data on to GBIF. OBIS-AU and ALA are working together to ensure that the publication pathways for any datasets managed by both (with potential for duplication of records and incomplete metadata harvests) are rationalised and that a single collaborative workflow across both units is followed for publication to GBIF. Recently, the data management groups have established an agreement to cooperatively publish marine data and eDNA data. OBIS-AU have commenced publishing datasets directly to GBIF with ALA endorsement. We present the convergent evolution of OBIS and GBIF data publishing in Australia, adaptive data workflows to maintain data and metadata integrity, challenges encountered, how domain expertise ensures data quality and the benefits of sharing data skills and code, especially in publishing eDNA data types in DwC (using the DNA-derived data extension) and exploring the new CamTrap Data Package using Frictionless data. We also present the work that both data groups are doing toward adopting the GBIF new Unified Data model for publishing data. This Australian case study demonstrates the strengths of collaborative data publishing and offers a model that minimises replication of data in global aggregators through the development of regional integrated data publishing pipelines.

Connecting National and International Data Infrastructures in Biodiversity Research

NFDI4Biodiversity is a consortium within the German National Research Data Infrastructure (NFDI) dedicated to data and services for biodiversity research and ecology. In the domain, well-developed international networks exist, with quite mature tools and data standards. These are used and disseminated in the NFDI4Biodiversity project in order to mobilise and publish data collected by national stakeholders according to the FAIR Guiding Principles for scientific data management and stewardship.The consortium partners provide methods and tools for archiving, publishing, searching and analysing data that are suitable for everyday use and have been tried and tested in practice. The consortium also functions as a forum for technical and legal matters of data and data-related workflows. In this way, the consortium is providing added value to the community regarding access to modern technologies and a comprehensive stock of biodiversity and environmental data.

The Impossible Museum: A national infrastructure to digitise the UK’s natural science collections

The Distributed System of Scientific Collections UK (DiSSCo United Kingdom, Smith et al. 2022) is a proposal to the UK Research and Innovation (UKRI) Infrastructure Programme to revolutionise how we manage, share and use the UK’s natural science collections, creating a distributed network that provides a step change in research infrastructure for the UK. While the physical integration of such a collection would be almost inconceivable, its digital integration is within reach. Building on the UK Natural History Museum’s (NHM) digitisation programme and in partnership with more than 90 collection-holding institutions across the length and breadth of the UK, DiSSCo UK seeks to unlock the full scientific, economic and social benefits of the UK’s natural science collections, which are presently constrained by the limits of physical access. With just 8% of the UK’s 137 million specimens currently available digitally, their role in the emerging biodiversity data revolution is diminished. Through nationally coordinated action, DiSSCo UK seeks to massively accelerate the digitisation of these collections and the impact of these data. Five options to digitise UK collections are presently under consideration. These options iterate across the collection groups, number and type of institution, technical infrastructure level and "catalysis" to capitalise on the benefits of unlocking data and accelerating data production. Subject to UKRI approval, the full business cases for a preferred option will go through an 18–24 month approval process starting November 2023, unlocking tens to hundreds of millions of pounds of investment in UK collections. We will outline the strategic case, options and operational model for DISSCo UK, updating on our coordination, digitisation and catalysis activities.

A Novel Part in the Swiss Army Knife for Linking Biodiversity Data: The digital specimen identifier service

Digital specimens are new information objects on the internet, which act as digital surrogates of the physical objects they represent. They are designed to be extended with data derived from the specimen like genetic, morphological and chemical data, and with data that puts the specimen in context of its gathering event and the environment it was derived from. This requires linking the digital specimens and their related entities to information about agents, locations, publications, taxa and environmental information. To establish reliable links and (re-)connect data to specimens, a new framework is needed, which creates persistent identifiers (PIDs) for the digital specimen and its related entities. These PIDs should be actionable by machines but also can be used by humans for data citation and communication purposes. The framework that enables this is a new PID infrastructure, produced by the European Commission-funded BiCIKL project (Biodiversity Community Integrated Knowledge Library), creates persistent and actionable identifiers. It is a generic PID infrastructure that will be used by the Distributed System for Scientific Collections research infrastructure (DiSSCo), but it can also be used by other infrastructures and institutions. PIDs minted by DiSSCo will be linked to the digital specimens and samples provided through DiSSCo. The new PIDs are a key element in enabling the concept of Digital Extended Specimens (Webster et al. 2021) and provide unique and resolvable references to enable bidirectional linking. DiSSCo has done extensive work to select the most appropriate PID scheme (Hardisty et al. 2021) and to design a PID infrastructure for the pan-European specimens. The draft design has been discussed with technical specialists in the joint DiSSCo and Consortium of European Taxonomic Facilities (CETAF) community, with international stakeholders like the Global Biodiversity Information Facility (GBIF) and Integrated Digitized Biocollections (iDigBio) and was discussed at the 2022 conference of the Society for the Preservation of Natural History Collections (SPNHC). A first implementation was demonstrated in the Biodiversity Information Standards (TDWG) annual conference in 2022 and illustrated key elements in the design. To be able to provide digital specimen identifiers as DOIs (Digital Object Identifiers), a pilot project was started in 2023 with DataCite to investigate if Digital Specimen DOIs in the new PID infrastructure can be created using the DataCite service. The pilot aim was to create metadata crosswalks to the DataCite schema in consultation with the DataCite Metadata Working Group, to evaluate synergies with the IGSN (International Generic Sample Number) metadata schema, to develop and test PID kernel metadata registration, and to evaluate performance and the impact of using DataCite services. There are around two billion specimens and creating PIDs for them as DOIs requires creating DOIs at an unprecedented scale. Also, PID kernel metadata registration is new for DOIs. The included metadata for specimens will complement existing Biodiversity Information Standards such as Darwin Core, and supports the new MIDS (Minimum Information about a digital specimen) standard that is under development. The design, development and testing of the new PID infrastructure is being done as part of the BiCIKL project that aims to foster collaboration between infrastructures and develop bidirectional connections (Penev et al. 2022). In the session, we will demonstrate the results in development of the PID infrastructure as part of the BiCIKL toolbox to link biodiversity data and to discuss the progress with creating digital specimen DOIs.

Can Biodiversity Data Scientists Document Volunteer and Professional Collaborations and Contributions in the Biodiversity Data Enterprise?

The collection, archiving and use of biodiversity data depend on a network of pipelines herein called the Biodiversity Data Enterprise (BDE) and best understood globally through the work of the Global Biodiversity Information Facility (GBIF). Efforts to sustain and grow the BDE require information about the data pipeline and the infrastructure that supports it. A host of metrics from GBIF, including institutional participation (member countries, institutional contributors, data publishers), biodiversity coverage (occurrence records, species, geographic extent, data sets) and data usage (records downloaded, published papers using the data) (Miller 2021), document the rapid growth and successes of the BDE (GBIF Secretariat 2022). Heberling et al. (2021) make a convincing case that the data integration process is working. The Biodiversity Information Standards' (TDWG) Basis of Record term provides information about the underlying infrastructure. It categorizes the kinds of processes*1 that teams undertake to capture biodiversity information and GBIF quantifies their contributions*2 (Table 1). Currently 83.4% of observations come from human observations, of which 63% are of birds. Museum preserved specimens account for 9.5% of records. In both cases, a combination of volunteers (who make observations, collect specimens, digitize specimens, transcribe specimen labels) and professionals work together to make records available. To better understand how the BDE is working, we suggest that it would be of value to know the number of contributions and contributors and their hours of engagement for each data set. This can help the community address questions such as, "How many volunteers do we need to document birds in a given area?" or "How much professional support is required to run a camera trap network?" For example, millions of observations were made by tens of thousands of observers in two recent BioBlitz events, one called Big Day, focusing on birds, sponsored by the Cornell Laboratory of Ornithology and the other called the City Nature Challenge, addressing all taxa, sponsored jointly by the California Academy of Sciences and the Natural History Musuems of Los Angeles County (Table 2). In our presentation we will suggest approaches to deriving metrics that could be used to document the collaborations and contribution of volunteers and staff using examples from both Human Observation (eBird, iNaturalist) and Preserved Specimen (DigiVol, Notes from Nature) record types. The goal of the exercise is to start a conversation about how such metrics can further the development of the BDE.

Towards the Atlas of Living Flanders, a Challenging Path

In Belgium, a federal country in the heart of Europe, the competencies for nature conservation and nature policy lie within the regions. The Research Institute for Nature and Forest (INBO) is an independent research institute, funded by the Flemish regional government, which underpins and evaluates biodiversity policy and management by means of applied scientific research, and sharing of data and knowledge. One of the 12 strategic goals in the 2009-2015 INBO strategic planning was that: 'INBO manages data and makes them accessible. It looks into appropriate data gathering methods and means by which to disseminate data and make them readily available'. Since 2009, the INBO has steadily evolved into a research institute with a strong emphasis on open data and open science. In 2010 INBO became a data publisher for the Global Biodiversity Information Facility (GBIF), adopted an open data and open access policy and is known for being an open science institute in Flanders, Belgium. In 2021, a question arose from the council of ministers on the possibility and availability of a public portal for biodiversity data. The goal of this portal should be to ensure findability, availability, and optimal usability of biodiversity data, initially for policy makers, but also for the wider public. With the Living Atlas project already high on our radar, an analysis project, funded by the Flemish government, started in December 2021. All the entities in the department of 'Environment' contributed to a requirements and feasibility study, a proof of concept (POC) Living Atlas for Flanders was set up and the required budget was calculated. During the requirements and feasibility study we questioned the agency for nature and forest (ANB), the Flanders Environment Agency (VMM), Flemish land agency (VLM) and the Department of Environment with the help of a professional inquiry agency IPSOS on the possible relevance for policy of a Flemish biodiversity portal, the need of high resolution data (geographical and temporal scale) and the availability of biodiversity data in Flanders, focussed on key species, protected species and other Flemish priority species. During the technical proof of concept, we tested the Living Atlases (LA) software suite as the most mature candidate for a Flemish Living Atlas. We checked how we could set up a LA installation in our own Amazon Web Services (AWS) environment, evaluated all the used technologies, estimated the maintenance and infrastructure cost, the needed profiles and the number of full-time equivalent personnel we would need to run a performant Atlas of Living Flanders. The goal of this talk is to inform the audience on the steps we took, the hurdles we encountered and how we are trying to convince our policy makers of the benefits of an Atlas of Living Flanders.

DiversityIndia Meets: Pioneering citizen science through collaborative data mobilization

DiversityIndia, founded in 2001, is an online community dedicated to promoting meaningful discussions and facilitating the exchange of diverse perspectives on lesser-known taxonomic groups, including butterflies, moths, dragonflies, spiders, and more. The core idea behind DiversityIndia is to establish a network of like-minded individuals who possess a deep passion for these subjects and actively participate in various aspects of biodiversity observation and research. Initially, the taxonomic focus of DiversityIndia centered around butterflies, which led to the creation of the ButterflyIndia Yahoo email group. The group quickly gained recognition for its significant contributions in sharing valuable insights about butterflies, including information about their habitats and lesser-known species. ButterflyIndia also played a vital role in facilitating connections among scientists and researchers who were dedicated to studying Lepidoptera. As a result of its collaborative efforts, the group actively contributed to major book projects and web portals, further enhancing the knowledge and resources available to the butterfly research community. As time progressed, the group expanded its presence to include various social media platforms like Orkut, Facebook, Flickr and more, thereby expanding its influence and reach. The realization of a significant need for empirical research on butterflies, requiring the involvement of both specialists and enthusiasts across diverse habitats, led to the first ButterflyIndia Meet in 2004 at Shendurney, Kerala. This pioneering concept garnered immense success, attracting participants from diverse regions of the country and backgrounds. Since then, several ButterflyIndia Meets have been organized, resulting in the documentation of numerous butterfly species. Building upon this success, DragonflyIndia and SpiderIndia were established with similar objectives and have successfully coordinated multiple gatherings (Fig. 1). One of the most notable DiversityIndia Meets occurred in April 2022, held in Sundarbans, West Bengal. This particular meet marked a significant milestone as the documented dataset, comprising information on all taxonomic groups observed during the event, was published through the Global Biodiversity Information Facility (GBIF) (Roy et al. 2022). This publication allowed for wider accessibility and utilization of the valuable biodiversity data collected during the meet. In addition to the Sundarbans meet, ongoing efforts are currently underway to gather occurrence data from all the previous meetings conducted by DiversityIndia (Table 1). The aim is to compile and mobilize this data on GBIF as datasets, involving active participation from the members who attended these meetings. This endeavor seeks to maximize the availability and usefulness of the biodiversity information gathered through the various DiversityIndia Meets over time. According to the published records so far (Global Biodiversity Information Facility 2023), there are 1663 documented occurrences from 859 taxa belonging to 14 taxonomic classes, covering various biogeographies in India. These records provide valuable insights into the biodiversity of the country. DiversityIndia has indeed played a pioneering role in online citizen science in India, and its origins can be traced back to the original Yahoo groups. By bringing together specialists and enthusiasts alike, this community has successfully contributed to the comprehensive documentation and understanding of India's rich biodiversity. The collective efforts of the members serve as a testament to the enduring impact of citizen science in pushing the boundaries of our knowledge regarding the natural world.

Will a Local Portal using Global Data Encourage the Mainstreaming of Biodiversity Informatics in Asia? In Taiwan, We Say Yes

Five years ago, the value of biodiversity open data was scarcely recognized in Taiwan. This posed a significant challenge to the Taiwan Biodiversity Infomation Facility (TaiBIF), our national node of the Global Biodiversity Information Facility (GBIF), in its sustained efforts to enhance data publishing capacities. Notably, non-academic entities, both governmental and industrial, were reluctant to invest resources in data management and publication, questioning the benefits beyond purely research-oriented returns. At the time, Taiwan had fewer than a million published records domestically, while GBIF held around 3 million occurrence records for Taiwan, largely unused by local users. We speculated that this discrepancy in data usage stemmed from three factors: (1) lack of species names in the local language within the occurrence data, (2) missing locally important species attributes, such as conservation status and national red list categories, and (3) absence of a culturally relatable local portal promoting biodiversity data usage. To address these issues, we launched the Taiwan Biodiversity Network (TBN) website in 2018, localizing global data from GBIF and integrating missing information from local data sources. Collaborating with wildlife illustrators, we designed a user-friendly data interface to lessen the system's technical or academic barriers. This effort led to a doubling of website visitors and data download requests annually, and in recent years, biodiversity open data has become a vital component in environmental impact assessments. This upward trend heightened the recognition of the value of biodiversity open data, inciting organizations, such as initially data-conservative government agencies and private sectors with no obligatory data-sharing, to invest in data management and mobilization. This advancement also catalyzed the formation of the Taiwan Biodiversity Information Alliance (TBIA), actively promoting cross-organizational collaborations on data integration. Today, Taiwan offers more than 19 million globally accessible occurrence records and data for more than 28,000 species. While the surge in data volume can certainly be credited to the active local citizen science community, we believe the expanded coverage of species and data types is a result of a growing community supportive of biodiversity open data. This was made possible by the establishment of a local portal that effectively bridged the gap between global data and local needs. We hope our experience will motivate other Asian countries to create analogous local portals using global open data sources like GBIF, illustrating the value of biodiversity open data to decision-makers and overcoming resource limitations that impede investments in biodiversity informatics.

Harmonised Data is Actionable Data: DiSSCo’s solution to data mapping

Predictability is one of the core requirements for creating machine actionable data. The better predictable the data, the more generic the service acting on the data can be. The more generic the service, the easier we can exchange ideas, collaborate on initiatives and leverage machines to do the work. It is essential for implementing the FAIR Principles (Findable, Accessible, Interoperable, Reproducible), as it provides the “I” for Interoperability (Jacobsen et al. 2020). The FAIR principles emphasise machine actionability because the amount of data generated is far too large for humans to handle. While Biodiversity Information Standards (TDWG) standards have massively improved the standardisation of biodiversity data, there is still room for improvement. Within the Distributed System of Scientific Collections (DiSSCo), we aim to harmonise all scientific data derived from European specimen collections, including geological specimens, into a single data specification. We call this data specification the open Digital Specimen (openDS). It is being built on top of existing and developing biodiversity information standards such as Darwin Core (DwC), Minimal Information Digital Specimen (MIDS), Latimer Core, Access to Biological Collection Data (ABCD) Schema, Extension for Geosciences (EFG) and also on the new Global Biodiversity Information Facility (GBIF) Unified Model. In openDS we leverage the existing standards within the TDWG community but combine these with stricter constraints and controlled vocabularies, with the aim to improve the FAIRness of the data. This will not only make the data easier to use, but will also increase its quality and machine actionability. As the first step towards this the harmonisation of terms, we make sure that similar values use the same term in a standard as key. This enables the next step in which we harmonise the values. We can transform free-text values into standardised or controlled vocabularies. For example: instead of using the names J. Doe, John Doe and J. Doe sr. for a collector, we aim to standardise these to J. Doe, with a person identifier that connects this name with more information about the collector. Biodiversity information standards such as DwC were developed to lower the bar for data sharing. The downside of including minimal restraints and flexibility is that they provide room for ambiguity, leading to multiple ways of interpretation. This limits interoperability and hampers machine actionability. In DiSSCo, data will come from different sources that use different biodiversity information standards. To cover this, we need to harmonise terms between these standards. To complicate things further, different serialisation methods are used for data exchange. Darwin Core Archives (DwC-A; GBIF 2021) use Comma-separated values (CSV) files. ABCD(EFG) exposed through Biological Collection Access Service (BioCASe) uses XML. And most custom formats use JavaScript Object Notation (JSON). In this lightning talk, we will dive into DiSSCo’s technical implementation of the harmonisation process. DiSSCo currently supports two biodiversity information standards, DwC and ABCD(EFG), and maps the data to our openDS specification on a record-by-record basis. We will highlight some of the more problematic mappings, but also show how a harmonised model massively simplifies generic actions, such as the calculation of MIDS levels, which provide information about digitisation completeness of a specimen. We will conclude by having a quick look at the next steps and hope to start a discussion about controlled vocabularies. The development of high quality, standardised data based on a strict specification with controlled vocabularies, rooted in community accepted standards, can have a huge impact on biodiversity research and is an essential step towards scaling up research with computational support.

Invasions, Plagues, and Epidemics: The Atlas of Living Australia’s deep dive into biosecurity

Early detection of new incursions of species of biosecurity concern is crucial to protecting Australia’s environment, agriculture, and cultural heritage. As Australia’s largest biodiversity data repository, the Atlas of Living Australia (ALA) is often the first platform where new species incursions are recorded. The ALA holds records of more than 2,380 exotic species and over 1.9 million occurrences of pests, weeds, and diseases—many of which are reported though citizen science. However, until recently there has been no systematic mechanism for notifying relevant biosecurity authorities of potential biosecurity threats. To address this, the ALA partnered with the (Australian) Commonwealth Department of Agriculture, Fisheries and Forestry to develop the Biosecurity Alerts System. Two years on, the project has demonstrated the benefits of biosecurity alerts, but significant barriers exist as we now work to expand this system to State and Territory biosecurity agencies, and seek new sources of biosecurity data. In our presentation, we discuss a brief history of invasive alien species in Australia, the Biosecurity Alerts System, and how we are approaching issues with taxonomy, data standards, and cultural sensitivities in aggregating biosecurity data. We conclude by detailing our progress in expanding the alerts system and tackling systemic issues to help elevate Australia’s biosecurity system.

Promoting High-Quality Data in OBIS: Insights from the OBIS Data Quality Assessment and Enhancement Project Team

The Ocean Biodiversity Information System (OBIS) (Klein et al. 2019) is a global database of marine biodiversity and associated environmental data, which provides critical information to researchers and policymakers worldwide. Ensuring the accuracy and consistency of the data in OBIS is essential for its usefulness and value, not only to the scientific community but also to the science-policy interface. The OBIS Data Quality Assessment and Enhancement Project Team (QCPT), formed in 2019 by the OBIS steering group, aims to assess and enhance data quality. It has been working on three categories of activities for this purpose: Data quality enhancement and management The OBIS QCPT organized data laundry events to identify and address data quality issues of published OBIS datasets. Furthermore, individual OBIS nodes were invited to give their data-processing presentations in the monthly meetings to foster knowledge sharing and collaborative problem-solving focused on data quality. Data quality issues and solutions highlighted in the presentations and data laundry events were documented in a dedicated GitHub repository as GitHub issues. The solutions for data quality issues and marine-specific pre-publication quality control tools, designed to identify the data quality issues, were provided as feedback to the OBIS Capacity Development Task Team. These inputs were used to create training resources (see OBIS manual, upcoming OBIS training course hosted on OceanTeacher Global Academy) aimed at preventing these issues. Standardization of OBIS data processing pipeline As OBIS uses the Darwin Core standard (Wieczorek et al. 2012), the use of standardized tests and assertions in the data processing pipeline is encouraged. To achieve this, the OBIS QCPT aligned OBIS quality checks with a subset of core tests and assertions (Chapman et al. 2020) developed by the Biodiversity Information Standards (TDWG) Biodiversity Data Quality (BDQ) Task Group 2 (TG2) (Chapman et al. 2020) as tracked in this GitHub issue. Not all default parameters of the core tests and assertions are optimal for marine biodiversity data. The OBIS QCPT met monthly to determine suitable parameters for customizing the tests. The pipeline produces a data quality report for each dataset with quality flags that indicate potential data quality issues, enabling node managers and data providers to review the flagged records. Community engagement The OBIS QCPT led a survey among data users to gather insights into OBIS data quality issues and bridge the gap between the current implementation and user expectations. The survey findings enabled OBIS to prioritize issues to be addressed, as summarized in Section 2.2.2 of the 11th OBIS Steering Group meeting report. In addition to engaging with data users, the OBIS QCPT also served as a platform to discuss questions related to the use of Darwin Core from the nodes and provided feedback for the term discussions. In summary, the OBIS QCPT improves marine species data reliability and usability through transparent and participatory approaches, fostering continuous improvement. Collaborative efforts, standardized procedures, and knowledge sharing advance OBIS' mission of providing high quality biodiversity data for research, conservation, and ocean management.

TaxonWorks in its 10th Year: What’s new, what’s next?

TaxonWorks in its 10th Year: What’s new, what’s next?

Improved Sharing and Linkage of Taxonomic Data with the Taxon Concept Standard (TCS)

The term ‘taxonomic backbone’ is often used to indicate the compromise taxonomies that form the taxonomic backbone of systems like the Global Biodiversity Information Facility (GBIF) and the Atlas of Living Australia (ALA). However, the term can also be seen in the broader sense as the entire expansive and continually evolving body of taxonomic work that underpins all biodiversity data and the linkage of all the different concepts that are used in various parts of the world and by various groups of people. The Taxon Concept Schema (TCS; Hyam and Kennedy 2006), which was ratified as a TDWG standard in 2005, came forth from the need of providers of taxonomic information for a mechanism to exchange data with other providers and users. Additionally, there was the knowledge that taxon names make poor identifiers for taxa and that more than names are needed for effective sharing and linking of biodiversity data. The same name can be associated with multiple taxon concepts or definitions, especially when a name has been around for a long time or is used in a heavily revised group. In order for others to know what a name means, people who use a name should also indicate which concept of that name is being used. Traditionally, the Latin ‘sensu’ or `sec.` have been used for this purpose; in TCS, an ‘according to’ property is used. The taxon concept, along with a language to relate different concepts, which is also in TCS, was later introduced to a systematic audience in an article by Franz and Peet (2009). Unfortunately, TCS has never enjoyed wide adoption and since Darwin Core (Wieczorek et al. 2012) was ratified in 2009, sharing of taxonomic information has mostly been done with the Darwin Core Taxon class. However, various issues with the Darwin Core Taxon class (e.g., Darwin Core and RDF/OWL Task Groups 2015) have made us look at TCS again and in 2020 the Taxonomic Names and Concepts Interest Group was formally renamed the TCS Maintenance Group. In 2021, a TCS 2 Task Group was established with the goal to update TCS to a Vocabulary Standard (like Darwin Core) that can be maintained under the TDWG Vocabulary Maintenance Specification (Vocabulary Maintenance Specification Task Group 2017). As it currently stands, TCS 2 (TCS 2 Task Group 2023) has two classes for dealing with taxonomy, the Taxon Concept and Taxon Relationship classes, and two classes for dealing with nomenclature, the Taxon Name and Nomenclatural Type classes. TCS 2 describes objects that are present and known in the domain and uses terms that are used in the domain (e.g., Greuter et al. 2011, Hawksworth 2010), so is easily understood by practitioners in the domain and other users of taxonomic information, as well as data specialists and developers. At the same time, it is in accordance with the OpenBiodiv Ontology (Senderov et al. 2018) and the Simple Knowledge Organization System (SKOS; Miles and Bechhofer 2009). TCS 2 can be used to mark up taxon concepts of any type, including taxonomic treatments, checklists, field guides, as well as systems like the Catalogue of Life and AviBase. Once marked up as TCS, concepts of all types look the same and therefore a small standard of under 40 terms can be used to share and link all taxonomic information and to link to other types of biodiversity data, for example occurrence data or descriptive data.

Are debt-for-nature swaps scalable: Which nature, how much debt, and who pays?

With the ongoing sovereign debt and biodiversity crises in many emerging economies, applications of debt-for-nature swaps as a dual solution for sovereign debt and nature conservation have been re-emerging. We analyze how debt-for-nature swaps (DNS) can be scaled to protect biodiversity priority areas and reduce debt burden. We build a dataset for biodiversity conservation and debt restructuring in 67 countries at risk of sovereign debt distress and show that they hold over 22% of global biodiversity priority areas, 82.96% of which are unprotected. Furthermore, we show that for 35 of the 67 countries, using conservative cost estimates, 100% of unprotected biodiversity priority areas could be protected for a fraction of debt; for the remaining countries, applying DNS would allow the protection of 11–13% of currently unprotected biodiversity priority areas. By applying interdisciplinary research combining fundamental biodiversity and economic data and methods merging, the research contributes methodologically and practically to the understanding of debt-for-nature swaps for emerging economies.

Towards a dynamic checklist of lichen-forming, lichenicolous and allied fungi of Ecuador – using the Consortium of Lichen Herbaria to manage fungal biodiversity in a megadiverse country

AbstractA checklist of Lichen-forming, Lichenicolous and Allied Fungi of Ecuador is presented with a total of 2599 species, of which 39 are reported for the first time from the country. The names of three species, Hypotrachyna montufariensis, H. subpartita and Sticta hypoglabra, previously not validly published, are validated. Pertusaria oahuensis, originally introduced by Magnusson as ‘ad interim’, is validated as Lepra oahuensis. The form Leucodermia leucomelos f. albociliata is validated. Two new combinations, Fissurina tectigera and F. timida, are made, and Physcia mobergii is introduced as a replacement name for the illegitimate P. lobulata Moberg non (Flörke) Arnold. In an initial step, the checklist was compiled by reviewing literature records of Ecuadorian lichen biota spanning from the late 19th century to the present day. Subsequently, records were added based on vouchers from 56 collections participating in the Consortium of Lichen Herbaria, a Symbiota-based biodiversity platform with particular focus on, but not exclusive to, North and South America. Symbiota provides sophisticated tools to manage biodiversity data, such as occurrence records, a taxonomic thesaurus, and checklists. The thesaurus keeps track of frequently changing names, distinguishing taxa currently accepted from ones considered synonyms. The software also provides tools to create and manage checklists, with an emphasis on selecting vouchers based on occurrence records that can be verified for identification accuracy. Advantages and limitations of creating checklists in Symbiota versus traditional ways of compiling these lists are discussed. Traditional checklists are well suited to document current knowledge as a ‘snapshot in time’. They are important baselines, frequently used by ecologists and conservation scientists as an established naming convention for citing species reported from a country. Compiling these lists, however, requires an immense effort, only to inadequately address the dynamic nature of scientific discovery. Traditional checklists are thus quickly out of date, particularly in groups with rapidly changing taxonomy, such as lichenized fungi. Especially in megadiverse countries, where new species and new occurrences continue to be discovered, traditional checklists are not easily updated; these lists necessarily fall short of efficiently managing immense data sets, and they rely primarily on secondary evidence (i.e. literature records rather than specimens). Ideally, best practices make use of dynamic database platforms such as Symbiota to assess occurrence records based both on literature citations and voucher specimens. Using modern data management tools comes with a learning curve. Systems like Symbiota are not necessarily intuitive and their functionality can still be improved, especially when handling literature records. However, online biodiversity data platforms have much potential in more efficiently managing and assessing large biodiversity data sets, particularly when investigating the lichen biota of megadiverse countries such as Ecuador.

Building the Australian National Species List

The Australian National Species List (AuNSL) is a unified, nationally accepted, taxonomy for the native and naturalised biota of Australia. It is derived from a set of taxon-focussed resources including the Australian Plant Name Index and Australian Plant Census, the Australian Faunal Directory, and similar lists of fungi, lichens and bryophytes. These resources share a common infrastructure, contribute to the single national taxonomy (AuNSL), but retain their independent curation practices and online presentation. The AuNSL is now the core national infrastructure providing names and taxonomy for significant biodiversity data infrastructures including the Atlas of Living Australia, the Terrestrial Ecosystem Research Network, the Biodiversity Data Repository, and the Species Profile and Threats Database. As the go-to resource for names and taxonomy for Australia’s unique biodiversity, the AuNSL must be constantly updated to reflect taxonomic and nomenclatural change. For some taxonomic groups, the AuNSL is substantially complete, and the incorporation of new taxa and other novelties occurs with little time lag. For other taxonomic groups the data are patchy and updates sporadic. Like similar projects, the AuNSL would benefit from improvements to taxonomic data publishing and sharing. Such improvements have the potential to enable automated, real-time ingestion for new taxonomic and nomenclatural data, allowing curator time to be re-directed to backfilling the historical data from a dispersed and complex literature. Ideally, the AuNSL will be able to benefit from advances in automated approaches to processing the historical data, including via the sharing of standardised representations of such data. Here we outline the AuNSL data model, editor functionality, and describe our approach to sharing our data via existing and emerging standards such as Darwin Core and Taxon Concept Schema (TCS2). We then describe what we, as consumers of taxonomic data from published works, really need from publishers of new, and reprocessed historical data. In brief, we need structured taxonomic data conforming to an adequate standard.

Mapping.bio: Piloting FAIR semantic mappings for biodiversity digital twins

Biodiversity research has a strong focus on the links between environment and functional traits, e.g., to assess how anthropogenic drivers of change impact ecological systems (Díaz et al. 2013). Interoperable exchange and integration of such data is enabled through the use of ontologies that provide ”meaning” to data and enable downstream processing involving learning and inference over graph-structured models of these data (Kulmanov et al. 2020). However, the development of thematically similar semantic artifacts, e.g., the Environmental Ontology (ENVO, Buttigieg et al. 2016) and the Semantic Web for Earth and Environment Technology Ontology (SWEET, DiGiuseppe et al. 2014), in biodiversity-related disciplines (e.g., environmental genomics and earth observation) can introduce substantial conceptual overlaps, and highlights the need for bridging technologies to facilitate reuse of biodiversity data across those knowledge fields (Karam et al. 2020). A recent design study, funded by the European Open Science Cloud (EOSC), proposes a framework to create, document and publish mappings and crosswalks linking different semantic artifacts within a particular scientific community and across scientific domains under the label of "Flexible Semantic Mapping Framework" (SEMAF, Broeder et al. 2021). SEMAF puts a strong emphasis on so-called pragmatic mappings, i.e., mappings that are driven by specific interoperability goals such as translations between specific observation measurements (e.g., sensor configurations) and metadata descriptions. Within the Horizon Europe Project “Biodiversity Digital Twin for Advanced Modelling, Simulation and Prediction Capabilities" (BioDT), a mapping tool leveraging SEMAF is currently under development: Mapping.bio provides a lightweight web service to read semantic artifacts, visualize them, add mappings as graphical connections and store the mappings as FAIR (Findable, Accessible, Interoperable Reusable) Digital Objects (FDOs, De Smedt et al. 2020) in a repository. To foster reusability, sustainably and long-term availability of digital objects, mapping.bio features mappings compliant with the Simple Standard for Sharing Ontological Mappings (SSSOM, Matentzoglu et al. 2022), a machine-interpretable and extensible vocabulary enabling the self-contained exploration and processing of annotated mappings by machines (machine actionability, Jacobsen et al. 2020).

Blue button (Cnidaria: Hydrozoa) distribution and trends in the Mexican Atlantic, based on field surveys and open-access data

Access to digital technology and software allows the production of a significant amount of biodiversity data, including citizens' species records, combined with field monitoring and standardized surveys, which are valuable to biological sciences; these data can help to know the distribution of organisms like medusozoans. We compiled records of the presence of Porpita porpita from open-access databases, scientific articles, and field observations to know their current distribution on the Mexican Atlantic for the first time. The yearly records of P. porpita increased over time, adding up to 22 records, of which 18 were assigned to citizen science. Most records correspond to 2011-2022, from April to May, and the Veracruz and Quintana Roo states. The records of the species in warm months and states with long shores can be related to an increase in touristic activities and observations by citizens. On the Mexican Atlantic, it is suggested that the use of digital technological devices under citizen science practices for recording P. porpita and its compilation in open-access databases acts as the principal method for tracking the distribution of this species. This work evidenced the need for a solid research framework of knowledge for P. porpita in the Mexican Atlantic, and future research could combine citizen science records and fieldwork records and improve the relationship between biological and oceanographic data to understand their spatial-temporal distribution patterns.

FAIR Principles and TDWG Standards: The case of morphological description of taxa and specimens

Sharing data is crucial in biodiversity research as well as in all scientific domains. Biodiversity Information Standards (TDWG) validates and makes available a set of standards to facilitate the sharing of biodiversity data. Of the 23 standards listed in alphabetical order, each has a status, a category, and a short description. But these standards are designed for very different purposes, which we will discuss by linking them to the FAIR principles (Findable, Accessible, Interoperable, and Reusable) . The FAIR principles (Wilkinson et al. 2016) focus on the ability of machines to automatically find and use the digital data. It is therefore crucial that software for editing, acquiring and using data, shares defined standards that are made available to all. TDWG has been working in this direction for over 30 years. Pioneers in biodiversity informatics, such as Richard Pankhust (Pankhurst 1970), Mike Dallwitz (Dallwitz 1974, Dallwitz 1980) and Jacques Lebbe (Lebbe et al. 1987) worked specifically on taxon identification with computers and how to represent morphological descriptions of taxa and specimens. Some TDWG standards, such as ABCD (Access to Biological Collection Data; Access to Biological Collections Data Task Group 2005), TCS (Taxonomic Concept Transfer Schema; Taxonomic Names Subgroup 2006) or SDD (Structured Descriptive Data; Structure of Descriptive Data (SDD) Subgroup 2006) are expressed by an XML schema covering a formal data model. Other standards, as Floristic Regions of the World (Takhtajan 1986), or Vocabulary Maintenance Standard (VMS; Vocabulary Maintenance Specification Task Group 2017) concern vocabularies or a collection of standardized terms. The Plant Occurrence and Status Scheme (POSS; World Conservation Monitoring Centre 1995) provides both, a list of accepted terms, and a data model (list of fields). In case of morpho-anatomical data describing taxa or specimens, TDWG offers two standards: DELTA (DEscription Language for TAxonomy, Dallwitz 2006) and SDD (Structured Descriptive Data, Hagedorn 2007). In order to further the discussion on morphological description data sharing, we would like to clarify what is meant by the term standard. We'll be looking at the concepts of guidelines, rules, defined format, referential list of terms, data schema, model, metamodel, protocols, which are all terms linked to this notion of standard and FAIR principles. Perhaps this reflection will lead us to propose criteria for better classifying TDWG standards.