It is this final requirement that glues RDF graphs to other RDF graphs, and which puts the “web” in semantic web. Objects can be either literals or URIs, but subjects and predicates must be URIs. The subjects and objects represent nodes in the graph, and the predicates represent directed arcs from subjects into objects. On the semantic web, knowledge graphs are constructed using the Resource Description Framework (RDF) - a family of W3C specifications in which graphs are specified by collections of triples. Knowledge graphs unite data silos using linked data technologies. Here, we describe a workshop that brought together biodiversity data professionals of diverse backgrounds to explore the utility of biodiversity knowledge graphs. The need for dataset integration has led biodiversity scientists in search of solutions. The knowledge that could be gleaned by organizing and uniting these resources is immense. Further, these complementary datasets are often held in private data stores or in disconnected public repositories (so-called “data silos”). First, generation of all of this data has led to a “data deluge,” with more data being generated than can be managed or assessed and not enough bioinformaticians to handle these massive datasets ( Bell et al.

While this is an auspicious development for the advancement of knowledge of biodiversity on earth, several problems have emerged. Natural Science collection digitization, genomic sample sequencing, and field survey data collection have accelerated in pace in recent years, thanks to focused investments and increasing efficiency of workflows, among other factors ( Hobern et al. The workshop was held at Agriculture and Agri-Food Canada’s Experimental Farm in Ottawa, Ontario, Canada from Oct.

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