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  1. Proceedings of the 4th International Workshop on Semantic Web Information Management (SWIM '12)
  2. Pay-as-you-go data integration for linked data: opportunities, challenges and architectures
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Automatic scaling of selective SPARQL joins using the TIRAMOLA system
Towards benefit-based RDF source selection for SPARQL queries
Pay-as-you-go data integration for linked data: opportunities, challenges and architectures
Named entity recognition and disambiguation using linked data and graph-based centrality scoring
To nest or not to nest, when and how much: representing intermediate results of graph pattern queries in MapReduce based processing
Type inference methods and performance for data in an RDBMS
A decentralized infrastructure for the efficient management of resources in the web of data
SPOVC: a scalable RDF store using horizontal partitioning and column oriented DBMS
SPARQL query answering with bitmap indexes
Abstract framework for social ontologies and folksonomized ontologies

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Pay-as-you-go data integration for linked data: opportunities, challenges and architectures

Content Provider ACM Digital Library
Author Paton, Norman W. Hedeler, Cornelia Parsia, Bijan Christodoulou, Klitos Fernandes, Alvaro A. A.
Abstract Linked Data (LD) provides principles for publishing data that underpin the development of an emerging web of data. LD follows the web in providing low barriers to entry: publishers can make their data available using a small set of standard technologies, and consumers can search for and browse published data using generic tools. Like the web, consumers frequently consume data in broadly the form in which it was published; this will be satisfactory in some cases, but the diversity of publishers means that the data required to support a task may be stored in many different sources, and described in many different ways. As such, although RDF provides a syntactically homogeneous language for describing data, sources typically manifest a wide range of heterogeneities, in terms of how data on a concept is represented. This paper makes the case that many aspects of both publication and consumption of LD stand to benefit from a pay-as-you-go approach to data integration. Specifically, the paper: (i) identifies a collection of opportunities for applying pay-as-you-go techniques to LD; (ii) describes some preliminary experiences applying a pay-as-you-go data integration system to LD; and (iii) presents some open issues that need to be addressed to enable the full benefits of pay-as-you go integration to be realised.
Starting Page 1
Ending Page 8
Page Count 8
File Format PDF
ISBN 9781450314466
DOI 10.1145/2237867.2237870
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2012-05-20
Publisher Place New York
Access Restriction Subscribed
Content Type Text
Resource Type Article
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