On the Feasibility of Crawling Linked Data Sets for Reusable Defect Corrections.

Current linked open data standards have encouraged thepublication of a large number of data sets on the publicWeb. While some data providers put a lot of energy andresources into maintaining high quality data, others do not,meaning that the quality of the data in many LOD sourcesis variable and unpredictable. This makes the constructionof novel applications on top of the data more difficult andexpensive than it otherwise would be. However, these same data standards also open up possibilitiesfor new ways of managing information quality (IQ). Inthis paper, we propose one such approach, the IQ-bot, andpresent the results of our study of its feasibility. An IQ-botis a 3rd party component that crawls the Web of data,looking for changes that have been made to data sets, andinferring from them where a correction to a data defect hasbeen made. These corrections can then potentially be madeavailable for application to other databases showing evidenceof the presence of the same data defect. In this way, the benefits of the curation effort put into a small number of datasets can be propagated throughout the Web of data.