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ABSTRACT
This article is motivated by the importance of building web data mashups. Building on the remarkable success of Web 2.0 mashups, and specially Yahoo Pipes, we generalize the idea of mashups and regard the Internet as a database. Each internet data source is seen as a table, and a mashup is seen as a query on these tables. We assume that web data sources are represented in RDF, and SPARQL is the query language. We propose a query-by-diagram language called MashQL. The goal is to allow people to build data mashups diagrammatically. In the background, MashQL queries are translated into and executed as SPARQL queries. The novelty of MashQL is that it allows querying a data source without any prior understanding of the schema or the structure of this source. Users also do not need any knowledge about RDF/SPARQL to get started.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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INDEX TERMS
Primary Classification:
H.
Information Systems
H.3
INFORMATION STORAGE AND RETRIEVAL
H.3.3
Information Search and Retrieval
Subjects:
Query formulation
Additional Classification:
H.
Information Systems
H.3
INFORMATION STORAGE AND RETRIEVAL
H.3.3
Information Search and Retrieval
Subjects:
Information filtering;
Retrieval models
General Terms:
Design,
Human Factors,
Languages,
Management
Keywords:
RDF,
SPARQL,
Web 2.0,
Web 3.0,
data web,
linked data,
mashups,
query pipelines,
query-by-diagram,
semantic web
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