Analysing Large Inconsistent Knowledge Graphs Using Anti-patterns

Abstract

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Observing LOD: Its Knowledge Domains and the Varying Behavior of Ontologies Across Them

“…This classification system is available online as a Simple Knowledge Organisation System (SKOS). 4 We reduce the dataset classification task to a text classification task by creating a ''Virtual Text Document'' (VTD) for each LOD dataset. To create a reference training/testing corpus we extend the Topic Profiling Benchmark (TPB) [13] (which includes 198 datasets) to maximise its represented knowledge domains, with datasets retrieved from LOD.…”

“…Another notion of pattern is extracted by ABSTAT-HD [25] which summarises large knowledge graphs as sets of Abstract Knowledge Patterns (AKPs) of the form ⟨subjectType, predicate, objectType⟩. In [4], the authors introduce an approach to identify anti-patterns and errors in large KGs such as DBpedia and YAGO. The method developed in this paper may be used in combination with these approaches e.g.…”

“…History of America and History of Americas from Library of Congress). The resulting classification system is summarised in Table 3 and is available online as a SKOS vocabulary 4 . It consists of 59 concepts generalised by 6 (additional) concepts.…”

“…Following a similar approach, relevant effort has been spent to observe ontology design practices. For example, in [4], resources such as DBpedia [5] and YAGO (Yet Another Great Ontology) [6] are analysed to identify common modelling patterns that sometimes show anti-patterns or errors. The results of these studies is crucial to inform knowledge engineering methodologies and to improve the quality of common practices and guidelines.…”