Abstract

With the rapid accumulation of biodiversity data, data integration has emerged as a hot topic in soil ecology. Data integration has indeed the potential to advance our knowledge of global patterns in soil biodiversity by facilitating large-scale meta-analytical studies of soil ecosystems. However, ecologists are still poorly equipped when it comes to integrating disparate datasets. In recent years, knowledge graphs have emerged as a powerful tool for integrating large amounts of distributed heterogeneous data while making these data more easily interpretable by humans and computers. This paper presents a practical approach to constructing a biodiversity knowledge graph from heterogeneous and distributed (semi-)structured data sources. To illustrate our approach, we integrate several datasets on the trophic ecology of soil organisms into a trophic knowledge graph and show how both explicit and implicit information can be retrieved from the graph to support multi-trophic studies.

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