Intro

As the popularity of linked open data (LOD) grows, more and more heterogeneous data sets are being integrated, which calls for potential users to use a complex query language, e.g., SPARQL, for search on the data sets. However, as SPARQL is not easy to write even for experienced users, many groups are developing assistive methods, e.g., visual SPARQL editor.

In the Linked Open Data Question-Answering (LODQA) project, we focus on natural language as a human-friendly representational means of search queries. It would obviously be convenient if search queries expressed in natural language could be converted to SPARQL queries. Together with speech recognition system, it would be even more powerful in the era of mobile computing. We can also think about a harmonic use with other assistive SPARQL authoring methods: a SPARQL query may be drafted using a natural language query processing system, then precisely revised using a visual editor.

With extensive potential in mind, LODQA focuses on developing a natural language query processing system as an open source project.