Abstract
Although soil ecology has benefited from recent advances in describing the functional and trophic traits of soil organisms, data reuse for large-scale soil food-web reconstructions still faces challenges. These obstacles include: (1) most data on the trophic interactions and feeding behaviour of soil organisms being scattered across disparate repositories, without well-established standard for describing and structuring trophic datasets; (2) the existence of various competing terms, rather than consensus, to delineate feeding-related concepts such as diets, trophic groups, feeding processes, resource types, leading to ambiguities that hinder meaningful data integration from different studies; (3) considerable divergence in the trophic classification of numerous soil organisms, or even the lack of such classifications, leading to discrepancies in the resolution of reconstructed food webs and complicating the reuse and comparison of food-web models within synthetic studies. To address these issues, we introduce the Soil Food Web Ontology, a novel formal conceptual framework designed to foster agreement on the trophic ecology of soil organisms. This ontology represents a collaborative and ongoing endeavour aimed at establishing consensus and formal definitions for the array of concepts relevant to soil trophic ecology. Its primary objective is to enhance the accessibility, interpretation, combination, reuse, and automated processing of trophic data. By harmonising the terminology and fundamental principles of soil trophic ecology, we anticipate that the Soil Food Web Ontology will improve knowledge management within the field. It will help soil ecologists to better harness existing information regarding the feeding behaviours of soil organisms, facilitate more robust trophic classifications, streamline the reconstruction of soil food webs, and ultimately render food-web research more inclusive, reusable and reproducible.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
The manuscript has been completely revised to make it more accessible to the target audience.
https://github.com/soilfoodwebontology/sfwo/releases/tag/v2023-08-23
Box 1. Glossary
- Automated reasoning
- the process of automatically computing logical inferences.
- Axiomatization
- the process of providing logical definitions of ontology classes in the form of logical axioms, i.e. logical statements that describe the relationships between concepts.
- Class
- the description of a concept in an ontology. Classes in an ontology are organised into a taxonomy using the subsumption (subClassOf) relation.
- Data heterogeneity
- differences in semantics (terminologies, meaning, interpretation), schema (data structures, formats), and syntax (models, languages) between data from possibly different data sources.
- Knowledge graph
- a knowledge base that uses a graph-structured data model to integrate data.
- Named entity recognition
- the task of automatically detecting and classifying mentions of entities of interest (e.g., taxa, food resources, diets) in text.
- OWL ontology
- a formal representation of concepts within a domain of interest (e.g., ecology) and relationships between those concepts, encoded using a formal ontology language such as the Web Ontology Language (OWL). OWL is the World Wide Web Consortium’s (W3C) standard for authoring ontologies. It is based on a subset of first-order logic.
- Property
- the description of a relation in an ontology. This can be a relation between two classes (object property) or between a class and a data type value (datatype property). Properties in an ontology are organised into their own taxonomy using the subPropertyOf relation.
- Reasoner
- or reasoning engine, a piece of software that can perform automated reasoning.
- Relational machine learning
- a subdiscipline of artificial intelligence and machine learning that is concerned with the statistical analysis of relational (graph-structured) data.
- Semantic annotation
- the process of linking data to classes in an ontology.
- Semantic data integration
- the process of combining data from different sources into a single, unified view using ontologies.
- Top-level ontology
- or upper ontology, an ontology which consists of very general terms that are common across all domains. Upper ontologies support interoperability among a large number of domain-specific ontologies by providing a common starting point for the formulation of definitions.
Box 2. Abbreviations
- BETSI
- Biological and Ecological Traits of Soil Invertebrates
- BFO
- Basic Formal Ontology
- BIOfid
- Specialised Information Service Biodiversity Research
- GloBI
- Global Biotic Interactions
- IRI
- Internationalized Resource Identifier
- NCBI
- National Center for Biotechnology Information
- NER
- Named Entity Recognition
- OWL
- Web Ontology Language
- OBO
- Open Biomedical Ontologies
- PATO
- Phenotype And Trait Ontology
- PCO
- Population and Community Ontology
- RO
- Relations Ontology
- SFWO
- Soil Food Web Ontology
- T
- SITA-Thesaurus for Soil Invertebrate Trait-based Approaches