To make their data usable, Linked Data producers need to provide a minimum level of homogeneity. But the task of finding the missing attributes for a specific list of entities is notoriously difficult to complete.
To make their data usable, Linked Data producers need to provide a minimum level of homogeneity. But the task of finding the missing attributes for a specific list of entities is notoriously difficult to complete.
We make the hypothesis that identifying subsets of items with a similar structure can help finding the cause of incompleteness and decide if and how it could to be solved.
We make the hypothesis that **identifying subsets of items with a similar structure can help finding the cause of incompleteness** and decide if and how it could to be solved.
Our visualisation tool “The Missing Path”, relies on dimensional reduction techniques to create a map of the entities based on missing attributes, revealing clusters. It let users inspect these clusters for diagnosing the reasons for incompleteness.
Our visualisation tool “The Missing Path”, relies on dimensional reduction techniques to create a map of the entities based on missing attributes, revealing clusters. It let users inspect these clusters for diagnosing the reasons for incompleteness.