Browse Prior Art Database

A System and Method to Assist User to Write SPARQL Query

IP.com Disclosure Number: IPCOM000180749D
Original Publication Date: 2009-Mar-16
Included in the Prior Art Database: 2009-Mar-16
Document File: 7 page(s) / 117K

Publishing Venue

IBM

Abstract

With the development of semantic web, RDF data management becomes an increasingly important task. Different from the relational data, RDF data is in the form of . For RDF data, SPARQL is the query language recommended by W3C. A SPARQL query consists of the patterns that the RDF data needs to follow. We call such patterns as triple patterns. For an end user, writing a SPARQL query is rather difficult. For helping user to write an RDF query, the existing approach is to list the options in a menu and let user to select a vocabulary. However, such options are all the predicates or classes appearing in the ontology. For the RDF data with complex meta-data, it is hard for user to browse a large number of options and make the selection. We propose a novel framework to solve this problem. Based on the ontology information and the triple pattern(s) that has already been input, we apply reasoning to check whether the option is valid against the query context. As a result, only the options that are valid to the context are preserved and shown to the end users as the recommended options.

This text was extracted from a PDF file.
At least one non-text object (such as an image or picture) has been suppressed.
This is the abbreviated version, containing approximately 34% of the total text.

Page 1 of 7

A System and Method to Assist User to Write SPARQL Query

1. Background: What is the problem solved by your invention? Describe known solutions to this problem(if any). What are the drawbacks of such known solutions, or why is an additional solution required? Cite any relevant technical documents or references.

With the development of semantic web, RDF data management becomes an increasingly important task. Different from the relational data, RDF data is in the form of

. For RDF data,SPARQL is the query language recommended by W3C. ASPARQL query consists of the patterns that the RDF data needs to follow. We call such patterns as triple patterns. For an end user,

writing a SPARQL query is rather difficult. Given a complex domain, user

often does not know the vocabularies that can be used in the triple patterns. Fortunately, RDF data also has its "schema" or meta-data,

which is called

ontology. Formally, ontology is an explicit specification of shared conceptualization. For helping user to write an RDF query, the existing approach is to list the options in a menu and let user to select a vocabulary. However, such options are all the predicates orclasses appearing in the ontology. For the RDF data with complex meta-data, it is hard for user to browse a large number of options and make the selection. So,

what is required is to let the system aware the context

of user's query and narrow down the number of options by only listing the real meaningful/valid ones.

Reference:
[1]. Resource description framework (rdf).http://

www.

w3.org/rdf/.

[2].Sparql query language for rdf. http://

www.

w3.org/tr/rdf-sparql-query/.

[3].OWL Web Ontology Language Reference. http://www.w3.org

/TR

/owl-ref

/

[4].Kaufmann, E., Bernstein, A., Zumstein, R.: Querix: A Natural Language Interface to Query Ontologies Based on Clarification Dialogs. In ISWC. 2006
[5].Wang, C.; Xiong, M.; Zhou, Q.; and Yu, Y. PANTO: A Portable Natural Language Interface to Ontologies. In ISWC. 2007.
[6].E. Oren, R. Delbru, and S. Decker. Extending faceted navigation for RDF data. In ISWC. 2006.
[7].Zhou, Q., Wang, C., Xiong, M., Wang, H., Yu, Y.: SPARK: Adapting Keyword Query to Semantic Search.In ISWC. 2007.

2. Summary of Invention: Briefly describe the coreidea of your invention (saving the details for questions #3 below). Describe the advantage(s) of using your invention instead of the known solutionsdescribed above.

This disclosure propose a novel framework to help user to writing SPARQL query over RDF data. The motivation of our work is to solve the problems listed in the background section.

Our approach helps user to build the SPARQL query gradually as follows. First,

we require user to input one triple pattern at a time. W

                                                                                     hen user writes the triple pattern, the system will takes user's incomplete input and generate all candidate triple patterns. Then, for each...