Assessing trust with PageRank in the Web of Data
Abstract
While a number of quality metrics have been successfully proposed for datasets in the Web of Data, there is a lack of trust metrics that can be computed for any given dataset. We argue that reuse of data can be seen as an act of trust. In the SemanticWeb environment, datasets regularly include terms from other sources, and each of these connections express a degree of trust on that source. However, determining what is a dataset in this context is not straightforward. We use the concept of Pay-Level Domain to differentiate datasets, and consider usage of external terms as connections among them. Using these connections we compute the PageRank value for each dataset. This process has been performed for more than 300 datasets, extracted from the LOD Laundromat.
Domains
Modeling and SimulationOrigin | Files produced by the author(s) |
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