The Linked Data Benchmark Council (LDBC): Driving competition and collaboration in the graph data management space

Graph data management is instrumental for several use cases such as recommendation, root cause analysis, financial fraud detection, and enterprise knowledge representation. Efficiently supporting these use cases yields a number of unique requirements, including the need for a concise query language and graph-aware query optimization techniques. The goal of the Linked Data Benchmark Council (LDBC) is to design a set of standard benchmarks that capture representative categories of graph data management problems, making the performance of systems comparable and facilitating competition among vendors. LDBC also conducts research on graph schemas and graph query languages. This paper introduces the LDBC organization and its work over the last decade

UK, USA and Canada: how do their pressure ulcer prevalence and incidence data compare?

Although prevalence and incidence figures for pressure ulcers vary widely across health-care settings, common trends can be identified. This review examines data from three countries

Validation of pressure ulcer risk assessment scales: a critique

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