Title
Feta: Federated Query Tracking For Linked Data
Abstract
Following the principles of Linked Data (LD), data providers are producing thousands of interlinked datasets in multiple domains including life science, government, social networking, media and publications. Federated query engines allow data consumers to query several datasets through a federation of SPARQL endpoints. However, data providers just receive subqueries resulting from the decomposition of the original federated query. Consequently, they do not know how their data are crossed with other datasets of the federation. In this paper, we propose FETA, a Federated quEry TrAcking system for LD. We consider that data providers collaborate by sharing their query logs. Then, from a federated log, FETA infers Basic Graph Patterns (BGPs) containing joined triple patterns, executed among endpoints. We experimented FETA with logs produced by FedBench queries executed with Anapsid and FedX federated query engines. Experiments show that FETA is able to infer BGPs of joined triple patterns with a good precision and recall.
Year
DOI
Venue
2016
10.1007/978-3-319-44406-2_24
DATABASE AND EXPERT SYSTEMS APPLICATIONS, DEXA 2016, PT II
Keywords
Field
DocType
Linked data, Federated query processing, Log analysis, Usage control
Query optimization,Web search query,Data mining,Graph patterns,Query expansion,Computer science,Precision and recall,Tracking system,Linked data,SPARQL,Database
Conference
Volume
ISSN
Citations 
9828
0302-9743
1
PageRank 
References 
Authors
0.43
9
4
Name
Order
Citations
PageRank
George Nassopoulos110.43
Patricia Serrano-alvarado214217.21
Pascal Molli367058.93
Emmanuel Desmontils44711.19