A practical approach to constructing a knowledge graph for soil ecological research

Guillarme, Nicolas Le; Thuiller, Wilfried

doi:10.1016/j.ejsobi.2023.103497

Cited by 12 publications

(1 citation statement)

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“…Species interaction data can be acquired not only through new measurements but also from comprehensive databases, empirical knowledge and various sources of information across different spatial and temporal dimensions (Le Guillarme & Thuiller, 2023). The accumulation of this collective knowledge now enables us to draw generalisations about interactions across diverse environments and taxa.…”

Section: From Fundamental Knowledge and Data Integration To Metanetworkmentioning

confidence: 99%

Navigating the integration of biotic interactions in biogeography

Thuiller,

Calderón‐Sanou,

Chalmandrier

et al. 2023

Journal of Biogeography

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Biotic interactions are widely recognised as the backbone of ecological communities, but how best to study them is a subject of intense debate, especially at macro‐ecological scales. While some researchers claim that biotic interactions need to be observed directly, others use proxies and statistical approaches to infer them. Despite this ambiguity, studying and predicting the influence of biotic interactions on biogeographic patterns is a thriving area of research with crucial implications for conservation. Three distinct approaches are currently being explored. The first approach involves empirical observation and measurement of biotic interactions' effects on species demography in laboratory or field settings. While these findings contribute to theory and to understanding species' demographies, they can be challenging to generalise on a larger scale. The second approach centers on inferring biotic associations from observed co‐occurrences in space and time. The goal is to distinguish the environmental and biotic effects on species distributions. The third approach constructs extensive potential interaction networks, known as metanetworks, by leveraging existing knowledge about species ecology and interactions. This approach analyses local realisations of these networks using occurrence data and allows understanding large distributions of multi‐taxa assemblages. In this piece, we appraise these three approaches, highlighting their respective strengths and limitations. Instead of seeing them as conflicting, we advocate for their integration to enhance our understanding and expand applications in the emerging field of interaction biogeography. This integration shows promise for ecosystem understanding and management in the Anthropocene era.

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Section: From Fundamental Knowledge and Data Integration To Metanetworkmentioning

confidence: 99%

Navigating the integration of biotic interactions in biogeography

Thuiller,

Calderón‐Sanou,

Chalmandrier

et al. 2023

Journal of Biogeography

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The RML Ontology: A Community-Driven Modular Redesign After a Decade of Experience in Mapping Heterogeneous Data to RDF

Iglesias-Molina,

Van Assche,

Arenas-Guerrero

et al. 2023

Lecture Notes in Computer Science

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The Relational to RDF Mapping Language (R2RML) became a W3C Recommendation a decade ago. Despite its wide adoption, its potential applicability beyond relational databases was swiftly explored. As a result, several extensions and new mapping languages were proposed to tackle the limitations that surfaced as R2RML was applied in real-world use cases. Over the years, one of these languages, the RDF Mapping Language (RML), has gathered a large community of contributors, users, and compliant tools. So far, there has been no well-defined set of features for the mapping language, nor was there a consensus-marking ontology. Consequently, it has become challenging for non-experts to fully comprehend and utilize the full range of the language’s capabilities. After three years of work, the W3C Community Group on Knowledge Graph Construction proposes a new specification for RML. This paper presents the new modular RML ontology and the accompanying SHACL shapes that complement the specification. We discuss the motivations and challenges that emerged when extending R2RML, the methodology we followed to design the new ontology while ensuring its backward compatibility with R2RML, and the novel features which increase its expressiveness. The new ontology consolidates the potential of RML, empowers practitioners to define mapping rules for constructing RDF graphs that were previously unattainable, and allows developers to implement systems in adherence with [R2]RML.Resource type: Ontology/License: CC BY 4.0 InternationalDOI: 10.5281/zenodo.7918478/URL: http://w3id.org/rml/portal/

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