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With the expansion in the amount of data being produced as Linked Data (LD), the opportunity to build use cases has also increased. However, a crippling problem to the reliability of these use cases is the underlying poor data quality. Moreover, the ability to assess the quality of the consumed LD, based on the satisfaction of the consumers' quality requirements, significantly influences usability of such data for a given use case. In this paper, we propose a data quality assessment methodology specifically designed for LD. This methodology consists of three phases and six steps with specific emphasis on considering a use case. Copyright is held by the author/owner(s)
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Stored only when both papers are in the corpus — 24 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.