Capturing the currency of DBpedia descriptions and get insight into their validity
Anisa Rula, Luca Panziera, Matteo Palmonari, Andrea Maurino · 2014
Abstract. An increasing amount of data is published and consumed on the Web according to the Linked Open Data (LOD) paradigm. In such scenario, capturing the age of data can provide insight about their validity under the hypothesis that more up-to-date data is, more likely is to be true. In this paper we present a model and a framework for assessing the currency of the data represented in one of the most important LOD datasets, DBpedia. Existing currency metrics are based on the notion of date of last modification, but often such information is not explic-itly provided by data producers. The proposed framework extrapolates such temporal metadata from time-labeled revisions of Wikipedia pages (from which data has been extracted). Experimental results demonstrate the usefulness of the framework and the effectiveness of the currency evaluation model to provide a reliable indicator of the validity of facts represented in DBpedia.