Description: Aim: We aimed to apply ontological techniques to address semantic ambiguities in protected area and conservation informatics. By doing so, we aimed to create a coherent, machine-actionable semantic representation of the biogeographic areas (which often overlap protected areas) to support more efficient and standardized informatics, supporting research and decision-making. We present BIOREALM, the first informatic ontology for comparative biogeography. Location: Global. Taxon: Any taxon can be integrated in BIOREALM. Methods: We convert a cladogram of biogeographic areas—generated by a process known as bioregionalization—into a series of ontological classes. Areas of endemism are treated as formal objects related by hierarchical relationships and constrained by a condition of monophyly. We use semantic web approaches to extend the Environment Ontology (ENVO) with classes for (often semantically confounded) biogeographic entities, including biogeographic areas, areas of endemism and endemic areas. We applied this approach to a bioregionalization of Australia as a case study. In all, 20 subregions which are part of the Austral Bioregionalisation Atlas have been selected for the study and integrated in BIOREALM. Results: We have created an ontology—formatted in the Web Ontology Language and adhering to the practices of the Open Biomedical and Biological Ontology Foundry—which provides a rigorous, extensible and machine-actionable framework that can improve biogeographic analyses and interoperability between systems. One main class and 20 individuals per class were implemented. Main Conclusions: BIOREALM encodes a model-theoretic view of endemism using semantic web approaches, offering new avenues to express and analyse biogeographic units. This approach offers a means to identify monophyletic biogeographic areas for conservation, based on specific combinations of monophyletic endemic taxa. Such an ontology provides knowledge representation solutions which supports interoperability along the FAIR (Findable, Accessible, Interoperable, Reusable) principles, thus fostering more consistent ecological informatics.

Description: Omic BON is a thematic Biodiversity Observation Network under the Group on Earth Observations Biodiversity Observation Network (GEO BON), focused on coordinating the observation of biomolecules in organisms and the environment. Our founding partners include representatives from national, regional, and global observing systems; standards organizations; and data and sample management infrastructures. By coordinating observing strategies, methods, and data flows, Omic BON will facilitate the co-creation of a global omics meta-observatory to generate actionable knowledge. Here, we present key elements of Omic BON's founding charter and first activities.

Description: The standardization of data, encompassing both primary and contextual information (metadata), plays a pivotal role in facilitating data (re-)use, integration, and knowledge generation. However, the biodiversity and omics communities, converging on omics biodiversity data, have historically developed and adopted their own distinct standards, hindering effective (meta)data integration and collaboration. In response to this challenge, the Task Group (TG) for Sustainable DwC-MIxS Interoperability was established. Convening experts from the Biodiversity Information Standards (TDWG) and the Genomic Standards Consortium (GSC) alongside external stakeholders, the TG aimed to promote sustainable interoperability between the Minimum Information about any (x) Sequence (MIxS) and Darwin Core (DwC) specifications. To achieve this goal, the TG utilized the Simple Standard for Sharing Ontology Mappings (SSSOM) to create a comprehensive mapping of DwC keys to MIxS keys. This mapping, combined with the development of the MIxS-DwC extension, enables the incorporation of MIxS core terms into DwC-compliant metadata records, facilitating seamless data exchange between MIxS and DwC user communities. Through the implementation of this translation layer, data produced in either MIxS- or DwCcompliant formats can now be efficiently brokered, breaking down silos and fostering closer collaboration between the biodiversity and omics communities. To ensure its sustainability and lasting impact, TDWG and GSC have both signed a Memorandum of Understanding (MoU) on creating a continuous model to synchronize their standards. These achievements mark a significant step forward in enhancing data sharing and utilization across domains, thereby unlocking new opportunities for scientific discovery and advancement.

Description: In the current context of Biodiversity loss and climate change, it is more than ever necessary to adapt and develop our scientific practices to face these present-day global issues. Scientists, particularly biologists, have to define new protocols to optimize the tremendous amount of new data being generated and to analyse them. Monitoring Biodiversity is a complex problem because of its multiple facets and cross-domains links. The creation and use of ontologies to conceptualize those different aspects of Biodiversity is an efficient means for key stakeholders and policies makers to promote consistency and reliability of systems. For this purpose, the Environment Ontology (ENVO; http://www.environmentontology.org) is a community ontology for the concise and controlled description of environments. It is interoperating with other domain ontologies closely linked to the representation of biodiversity in order to better interface with efforts such as Darwin Core and initiatives to promote the achievement of the United Nations’ Sustainable Development Goals (SDGs). As part of the ENVO consortium, BiGAEOn is an ontology for biogeographic areas specifically. Biogeographic areas are the basic units used in Comparative Biogeography to produce classifications of biogeographic areas, here, bioregionalisation. BiGAEOn model describe and harmonize biogeographic entities (e.g. areas of endemism, endemic areas…) as well as their relationships. Hence, it provides a rigorous and simple framework that improves biogeographic analyses and interoperability between systems. In particular, BiGAEOn integrates formal descriptions of WWF ecoregions (http://www.worldwildlife.org). In this presentation, we will illustrate how our ontology fits current debates with a case study on Australia, since it’s the actual scene of the bioregionalisation revival.

Description: Climate change, habitat destruction, and myriad other ecological stressors will impact us all and have already contributed to what is being labeled the sixth wave of extinction (Ceballos et al. 2015, Régnier et al. 2015). As a countering force, conservation biology strives to identify those areas of the planet most worthy of protecting due to their unique natural value (Dudley and Stolton 2008). Despite their value, criticisms (Camillo and Peter 2011) have been leveled at 1) the social cost of maintaining protected status (Lele et al. 2010) and 2) instances of continued biodiversity decline despite protection regimes (Craigie et al. 2010, Dudley et al. 2014). At present, the selection and delimitation of protected areas is an intuitive and often subjective process, leading to ambiguities in the semantics behind and across their definitions. Thus, we propose that the application of ontological techniques to the ambiguities in protected area semantics is a timely contribution to conservation informatics. We hold that coherent semantic representation of the biogeographic areas which overlap protected areas (often designated empirically) will provide more efficient and standardized informatics, supporting research and decision-making processes. Our approach draws from comparative biogeography, which seeks to classify biogeographic areas based on their natural properties in a process known as bioregionalisation. In particular, we convert a cladogram of biogeographic areas (similar to cladogram of taxa) into a series of ontological classes, each corresponding to a monophyletic clade of areas. In this model, areas of endemism are treated as formal objects related by hierarchical relationships and constrained by the monophyly condition (Ung 2018). This approach unifies a model-theoretic view of endemism with the semantic web and therefore, offering new possibilities to communicate the biogeographic units conservation. We use semantic web standards (RDF and OWL) expressed through interoperable "Open Biological and Biomedical Ontology (OBO) Foundry" and Library resources to model areas of endemism as evolutionary entities for comparative biogeography. This aligns with current efforts in the OBO Foundry to extend their semantic coverage to the domains of Earth and ecosystem science. Due to our work’s heavy reliance on environmental semantics, we base our work on the Environment Ontology (ENVO), extending it with often confounded biogeographic entities including biogeographic areas, such as areas of endemism and endemic areas, as well as their relationships. Hence, we seek to provide a rigorous and simple framework that improves biogeographic analyses and interoperability between systems.