Novel techniques for querying structured data on the web

Abstract

The rapid growth of structured data on the Web has created a high demand for making this content more reusable and consumable. Companies are competing not only on gathering structured content and making it public, but also on encouraging people to reuse and profit from this content. Many companies have made their content publicly accessible not only through APIs but also started to widely adopt web metadata standards such as XML, RDF, RDFa, and microformats. This trend of structured data on the Web (Data Web) is shifting the focus of Web technologies towards new paradigms of structured-data retrieval. Traditional search engines cannot serve such data as the results of a keyword-based query will not be precise or clean, because the query itself is still ambiguous although the underlying data is structured. On the other side, traditional structured querying languages cannot be used directly as data on the Data Web is heterogeneous, large, distributed, schema-free, and not intuitive for web users. To expose the massive amount of structured data on the Web to its full potential, people should be able to query and combine this data easily and effectively.