Traffic analytics for linked data publishers

Luca Costabello; Pierre Yves Vandenbussche; Gofran Shukair; Corine Deliot; Neil Wilson

doi:10.1007/978-3-319-58068-5_1

Traffic analytics for linked data publishers

Luca Costabello, Pierre Yves Vandenbussche, Gofran Shukair, Corine Deliot, Neil Wilson

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

We present a traffic analytics platform for servers that publish Linked Data. To the best of our knowledge, this is the first system that mines access logs of registered Linked Data servers to extract traffic insights on daily basis and without human intervention. The framework extracts Linked Data-specific traffic metrics from log records of HTTP lookups and SPARQL queries, and provides insights not available in traditional web analytics tools. Among all, we detect visitor sessions with a variant of hierarchical agglomerative clustering. We also identify workload peaks of SPARQL endpoints by detecting heavy and light SPARQL queries with supervised learning. The platform has been tested on 13 months of access logs of the British National Bibliography RDF dataset.

Original language	English
Title of host publication	The Semantic Web - 14th International Conference, ESWC 2017, Proceedings
Editors	Diana Maynard, Aldo Gangemi, Rinke Hoekstra, Eva Blomqvist, Olaf Hartig, Pascal Hitzler
Publisher	Springer Verlag
Pages	3-18
Number of pages	16
ISBN (Print)	9783319580678
DOIs	https://doi.org/10.1007/978-3-319-58068-5_1
State	Published - 2017
Externally published	Yes
Event	14th Extended Semantic Web Conference, ESWC 2017 - Portoroz, Slovenia Duration: May 28 2017 → Jun 1 2017

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10249 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	14th Extended Semantic Web Conference, ESWC 2017
Country/Territory	Slovenia
City	Portoroz
Period	05/28/17 → 06/1/17

Keywords

Data publication
Linked data
SPARQL
Traffic analytics

Access to Document

10.1007/978-3-319-58068-5_1

Cite this

Costabello, L., Vandenbussche, P. Y., Shukair, G., Deliot, C., & Wilson, N. (2017). Traffic analytics for linked data publishers. In D. Maynard, A. Gangemi, R. Hoekstra, E. Blomqvist, O. Hartig, & P. Hitzler (Eds.), The Semantic Web - 14th International Conference, ESWC 2017, Proceedings (pp. 3-18). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10249 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-58068-5_1

Costabello, Luca ; Vandenbussche, Pierre Yves ; Shukair, Gofran et al. / Traffic analytics for linked data publishers. The Semantic Web - 14th International Conference, ESWC 2017, Proceedings. editor / Diana Maynard ; Aldo Gangemi ; Rinke Hoekstra ; Eva Blomqvist ; Olaf Hartig ; Pascal Hitzler. Springer Verlag, 2017. pp. 3-18 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Traffic analytics for linked data publishers",

abstract = "We present a traffic analytics platform for servers that publish Linked Data. To the best of our knowledge, this is the first system that mines access logs of registered Linked Data servers to extract traffic insights on daily basis and without human intervention. The framework extracts Linked Data-specific traffic metrics from log records of HTTP lookups and SPARQL queries, and provides insights not available in traditional web analytics tools. Among all, we detect visitor sessions with a variant of hierarchical agglomerative clustering. We also identify workload peaks of SPARQL endpoints by detecting heavy and light SPARQL queries with supervised learning. The platform has been tested on 13 months of access logs of the British National Bibliography RDF dataset.",

keywords = "Data publication, Linked data, SPARQL, Traffic analytics",

author = "Luca Costabello and Vandenbussche, {Pierre Yves} and Gofran Shukair and Corine Deliot and Neil Wilson",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 14th Extended Semantic Web Conference, ESWC 2017 ; Conference date: 28-05-2017 Through 01-06-2017",

year = "2017",

doi = "10.1007/978-3-319-58068-5_1",

language = "Ingl{\'e}s",

isbn = "9783319580678",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "3--18",

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Costabello, L, Vandenbussche, PY, Shukair, G, Deliot, C & Wilson, N 2017, Traffic analytics for linked data publishers. in D Maynard, A Gangemi, R Hoekstra, E Blomqvist, O Hartig & P Hitzler (eds), The Semantic Web - 14th International Conference, ESWC 2017, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10249 LNCS, Springer Verlag, pp. 3-18, 14th Extended Semantic Web Conference, ESWC 2017, Portoroz, Slovenia, 05/28/17. https://doi.org/10.1007/978-3-319-58068-5_1

Traffic analytics for linked data publishers. / Costabello, Luca; Vandenbussche, Pierre Yves; Shukair, Gofran et al.
The Semantic Web - 14th International Conference, ESWC 2017, Proceedings. ed. / Diana Maynard; Aldo Gangemi; Rinke Hoekstra; Eva Blomqvist; Olaf Hartig; Pascal Hitzler. Springer Verlag, 2017. p. 3-18 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10249 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Traffic analytics for linked data publishers

AU - Costabello, Luca

AU - Vandenbussche, Pierre Yves

AU - Shukair, Gofran

AU - Deliot, Corine

AU - Wilson, Neil

N1 - Publisher Copyright: © Springer International Publishing AG 2017.

PY - 2017

Y1 - 2017

N2 - We present a traffic analytics platform for servers that publish Linked Data. To the best of our knowledge, this is the first system that mines access logs of registered Linked Data servers to extract traffic insights on daily basis and without human intervention. The framework extracts Linked Data-specific traffic metrics from log records of HTTP lookups and SPARQL queries, and provides insights not available in traditional web analytics tools. Among all, we detect visitor sessions with a variant of hierarchical agglomerative clustering. We also identify workload peaks of SPARQL endpoints by detecting heavy and light SPARQL queries with supervised learning. The platform has been tested on 13 months of access logs of the British National Bibliography RDF dataset.

AB - We present a traffic analytics platform for servers that publish Linked Data. To the best of our knowledge, this is the first system that mines access logs of registered Linked Data servers to extract traffic insights on daily basis and without human intervention. The framework extracts Linked Data-specific traffic metrics from log records of HTTP lookups and SPARQL queries, and provides insights not available in traditional web analytics tools. Among all, we detect visitor sessions with a variant of hierarchical agglomerative clustering. We also identify workload peaks of SPARQL endpoints by detecting heavy and light SPARQL queries with supervised learning. The platform has been tested on 13 months of access logs of the British National Bibliography RDF dataset.

KW - Data publication

KW - Linked data

KW - SPARQL

KW - Traffic analytics

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U2 - 10.1007/978-3-319-58068-5_1

DO - 10.1007/978-3-319-58068-5_1

M3 - Contribución a la conferencia

AN - SCOPUS:85020041816

SN - 9783319580678

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 3

EP - 18

BT - The Semantic Web - 14th International Conference, ESWC 2017, Proceedings

A2 - Maynard, Diana

A2 - Gangemi, Aldo

A2 - Hoekstra, Rinke

A2 - Blomqvist, Eva

A2 - Hartig, Olaf

A2 - Hitzler, Pascal

PB - Springer Verlag

T2 - 14th Extended Semantic Web Conference, ESWC 2017

Y2 - 28 May 2017 through 1 June 2017

ER -

Costabello L, Vandenbussche PY, Shukair G, Deliot C, Wilson N. Traffic analytics for linked data publishers. In Maynard D, Gangemi A, Hoekstra R, Blomqvist E, Hartig O, Hitzler P, editors, The Semantic Web - 14th International Conference, ESWC 2017, Proceedings. Springer Verlag. 2017. p. 3-18. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-58068-5_1

Traffic analytics for linked data publishers

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