Microdata for Semantic Annotations: Quantitative Analysis of the Deployment of Educational Properties
Rosa Navarrete, Sergio Luján-Mora
2017 International Conference on Computational
Science and Computational Intelligence (CSCI’17), p. 1830-1831, Las Vegas (USA), December 14-16 2017. ISBN: 978-1-5386-2652-8. https://doi.org/10.1109/CSCI.2017.331
(CSCI'17b)
Congreso internacional / International conference
Resumen
The use of semantic annotations on web content aims to provide information able to be interpreted by search engines and other applications. According to recent publications, Microdata is one of the formats to provide these embedded annotations that has reached a broad adoption in different fields. Concurrently, Schema.org has become the accepted standard for embedded markup and recently has adopted specific vocabulary to describe educational content belonging to the Learning Resource Metadata Initiative (LRMI) specification. In this work, we present a quantitative analysis of the deployment of Microdata with educational LRMI properties conducted on datasets of web pages extracted from large-scale web corpus, obtained from web crawling, of three consecutive years. The results show a low trend of adoption of this technology as well as issues related to the misuse of the vocabulary.