What are the parameters that affect the construction of a knowledge graph?

Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review

Authors

  • David Chaves-Fraga
  • Kemele M. Endris
  • Enrique Iglesias
  • Oscar Corcho
  • Maria Esther Vidal

Research Organisations

External Research Organisations

  • Technical University of Madrid (UPM)
  • German National Library of Science and Technology (TIB)
  • University of Bonn
View graph of relations

Details

Original languageEnglish
Title of host publication On the Move to Meaningful Internet Systems: OTM 2019 Conferences
Subtitle of host publicationConfederated International Conferences: CoopIS, ODBASE, C&TC 2019, Rhodes, Greece, October 21–25, 2019, Proceedings
EditorsHervé Panetto, Christophe Debruyne, Martin Hepp, Dave Lewis, Claudio Agostino Ardagna, Robert Meersman
PublisherSpringer Nature Switzerland AG
Pages695-713
Number of pages19
Edition1.
ISBN (electronic)978-3-030-33246-4
ISBN (print)978-3-030-33245-7
Publication statusPublished - 11 Oct 2019
EventConfederated International Conferences on Cooperative Information Systems, CoopIS 2019, Ontologies, Databases, and Applications of Semantics, ODBASE 2019, and Cloud and Trusted Computing, C and TC, held as part of OTM 2019 - Rhodes, Greece
Duration: 21 Oct 2019 → 25 Oct 2019

Publication series

NameLecture Notes in Computer Science (LNCS)
Volume11877
ISSN (Print)0302-9743
ISSN (electronic)1611-3349

Abstract

A large number of datasets are made publicly available on a wide range of formats. Due to interoperability problems, the construction of RDF-based knowledge graphs (KG) using declarative mapping languages has emerged with the aim of integrating heterogeneous sources in a uniform way. Although the scientific community has actively contributed with several engines to solve the problem of knowledge graph construction, the lack of testbeds has prevented reproducible benchmarking of these engines. In this paper, we tackle the problem of evaluating knowledge graph creation, and analyze and empirically study a set of variables and configurations that impact on the behaviour of these engines (e.g. data size, data distribution, mapping complexity). The evaluation has been conducted on RMLMapper and the SDM-RDFizer, two state-of-the-art engines that interpret the RDF Mapping Language (RML) and transform (semi)-structured data into RDF knowledge graphs. The results allow us to discover unknown relations between these engines that cannot be observed in other configurations.

Keywords

    Knowledge graph construction, RDFizers, Testbeds

ASJC Scopus subject areas

Cite this

What are the parameters that affect the construction of a knowledge graph? / Chaves-Fraga, David; Endris, Kemele M.; Iglesias, Enrique et al.
On the Move to Meaningful Internet Systems: OTM 2019 Conferences : Confederated International Conferences: CoopIS, ODBASE, C&TC 2019, Rhodes, Greece, October 21–25, 2019, Proceedings. ed. / Hervé Panetto; Christophe Debruyne; Martin Hepp; Dave Lewis; Claudio Agostino Ardagna; Robert Meersman. 1. ed. Springer Nature Switzerland AG, 2019. p. 695-713 (Lecture Notes in Computer Science (LNCS); Vol. 11877).

Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review

Chaves-Fraga, D, Endris, KM, Iglesias, E, Corcho, O & Vidal, ME 2019, What are the parameters that affect the construction of a knowledge graph? in H Panetto, C Debruyne, M Hepp, D Lewis, C Agostino Ardagna & R Meersman (eds), On the Move to Meaningful Internet Systems: OTM 2019 Conferences : Confederated International Conferences: CoopIS, ODBASE, C&TC 2019, Rhodes, Greece, October 21–25, 2019, Proceedings. 1. edn, Lecture Notes in Computer Science (LNCS), vol. 11877, Springer Nature Switzerland AG, pp. 695-713, Confederated International Conferences on Cooperative Information Systems, CoopIS 2019, Ontologies, Databases, and Applications of Semantics, ODBASE 2019, and Cloud and Trusted Computing, C and TC, held as part of OTM 2019, Rhodes, Greece, 21 Oct 2019. https://doi.org/10.1007/978-3-030-33246-4_43
Chaves-Fraga, D., Endris, K. M., Iglesias, E., Corcho, O., & Vidal, M. E. (2019). What are the parameters that affect the construction of a knowledge graph? In H. Panetto, C. Debruyne, M. Hepp, D. Lewis, C. Agostino Ardagna, & R. Meersman (Eds.), On the Move to Meaningful Internet Systems: OTM 2019 Conferences : Confederated International Conferences: CoopIS, ODBASE, C&TC 2019, Rhodes, Greece, October 21–25, 2019, Proceedings (1. ed., pp. 695-713). (Lecture Notes in Computer Science (LNCS); Vol. 11877). Springer Nature Switzerland AG. https://doi.org/10.1007/978-3-030-33246-4_43
Chaves-Fraga D, Endris KM, Iglesias E, Corcho O, Vidal ME. What are the parameters that affect the construction of a knowledge graph? In Panetto H, Debruyne C, Hepp M, Lewis D, Agostino Ardagna C, Meersman R, editors, On the Move to Meaningful Internet Systems: OTM 2019 Conferences : Confederated International Conferences: CoopIS, ODBASE, C&TC 2019, Rhodes, Greece, October 21–25, 2019, Proceedings. 1. ed. Springer Nature Switzerland AG. 2019. p. 695-713. (Lecture Notes in Computer Science (LNCS)). doi: 10.1007/978-3-030-33246-4_43
Chaves-Fraga, David ; Endris, Kemele M. ; Iglesias, Enrique et al. / What are the parameters that affect the construction of a knowledge graph?. On the Move to Meaningful Internet Systems: OTM 2019 Conferences : Confederated International Conferences: CoopIS, ODBASE, C&TC 2019, Rhodes, Greece, October 21–25, 2019, Proceedings. editor / Hervé Panetto ; Christophe Debruyne ; Martin Hepp ; Dave Lewis ; Claudio Agostino Ardagna ; Robert Meersman. 1. ed. Springer Nature Switzerland AG, 2019. pp. 695-713 (Lecture Notes in Computer Science (LNCS)).
Download
@inproceedings{d721fb9f80ef4165b1443f3b29b1a881,
title = "What are the parameters that affect the construction of a knowledge graph?",
abstract = "A large number of datasets are made publicly available on a wide range of formats. Due to interoperability problems, the construction of RDF-based knowledge graphs (KG) using declarative mapping languages has emerged with the aim of integrating heterogeneous sources in a uniform way. Although the scientific community has actively contributed with several engines to solve the problem of knowledge graph construction, the lack of testbeds has prevented reproducible benchmarking of these engines. In this paper, we tackle the problem of evaluating knowledge graph creation, and analyze and empirically study a set of variables and configurations that impact on the behaviour of these engines (e.g. data size, data distribution, mapping complexity). The evaluation has been conducted on RMLMapper and the SDM-RDFizer, two state-of-the-art engines that interpret the RDF Mapping Language (RML) and transform (semi)-structured data into RDF knowledge graphs. The results allow us to discover unknown relations between these engines that cannot be observed in other configurations.",
keywords = "Knowledge graph construction, RDFizers, Testbeds",
author = "David Chaves-Fraga and Endris, {Kemele M.} and Enrique Iglesias and Oscar Corcho and Vidal, {Maria Esther}",
note = "Funding Information: This work is partially supported by the EU H2020 RIA funded This work is partially supported by the EU H2020 RIA funded project iASiS with grant agreement No. 727658, by the Ministerio de Econom?a, Indus-tria y Competitividad (Spain), by EU FEDER funds under DATOS 4.0: RETOS Y SOLUCIONES-UPM Spanish National Project (TIN2016-78011-C4-4-R), and by an FPI grant (BES-2017-082511).; Confederated International Conferences on Cooperative Information Systems, CoopIS 2019, Ontologies, Databases, and Applications of Semantics, ODBASE 2019, and Cloud and Trusted Computing, C and TC, held as part of OTM 2019 ; Conference date: 21-10-2019 Through 25-10-2019",
year = "2019",
month = oct,
day = "11",
doi = "10.1007/978-3-030-33246-4_43",
language = "English",
isbn = "978-3-030-33245-7",
series = "Lecture Notes in Computer Science (LNCS)",
publisher = "Springer Nature Switzerland AG",
pages = "695--713",
editor = "Herv{\'e} Panetto and Christophe Debruyne and Martin Hepp and Dave Lewis and {Agostino Ardagna}, Claudio and Robert Meersman",
booktitle = "On the Move to Meaningful Internet Systems: OTM 2019 Conferences",
address = "Switzerland",
edition = "1.",

}

Download

TY - GEN

T1 - What are the parameters that affect the construction of a knowledge graph?

AU - Chaves-Fraga, David

AU - Endris, Kemele M.

AU - Iglesias, Enrique

AU - Corcho, Oscar

AU - Vidal, Maria Esther

N1 - Funding Information: This work is partially supported by the EU H2020 RIA funded This work is partially supported by the EU H2020 RIA funded project iASiS with grant agreement No. 727658, by the Ministerio de Econom?a, Indus-tria y Competitividad (Spain), by EU FEDER funds under DATOS 4.0: RETOS Y SOLUCIONES-UPM Spanish National Project (TIN2016-78011-C4-4-R), and by an FPI grant (BES-2017-082511).

PY - 2019/10/11

Y1 - 2019/10/11

N2 - A large number of datasets are made publicly available on a wide range of formats. Due to interoperability problems, the construction of RDF-based knowledge graphs (KG) using declarative mapping languages has emerged with the aim of integrating heterogeneous sources in a uniform way. Although the scientific community has actively contributed with several engines to solve the problem of knowledge graph construction, the lack of testbeds has prevented reproducible benchmarking of these engines. In this paper, we tackle the problem of evaluating knowledge graph creation, and analyze and empirically study a set of variables and configurations that impact on the behaviour of these engines (e.g. data size, data distribution, mapping complexity). The evaluation has been conducted on RMLMapper and the SDM-RDFizer, two state-of-the-art engines that interpret the RDF Mapping Language (RML) and transform (semi)-structured data into RDF knowledge graphs. The results allow us to discover unknown relations between these engines that cannot be observed in other configurations.

AB - A large number of datasets are made publicly available on a wide range of formats. Due to interoperability problems, the construction of RDF-based knowledge graphs (KG) using declarative mapping languages has emerged with the aim of integrating heterogeneous sources in a uniform way. Although the scientific community has actively contributed with several engines to solve the problem of knowledge graph construction, the lack of testbeds has prevented reproducible benchmarking of these engines. In this paper, we tackle the problem of evaluating knowledge graph creation, and analyze and empirically study a set of variables and configurations that impact on the behaviour of these engines (e.g. data size, data distribution, mapping complexity). The evaluation has been conducted on RMLMapper and the SDM-RDFizer, two state-of-the-art engines that interpret the RDF Mapping Language (RML) and transform (semi)-structured data into RDF knowledge graphs. The results allow us to discover unknown relations between these engines that cannot be observed in other configurations.

KW - Knowledge graph construction

KW - RDFizers

KW - Testbeds

UR - http://www.scopus.com/inward/record.url?scp=85077852880&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-33246-4_43

DO - 10.1007/978-3-030-33246-4_43

M3 - Conference contribution

AN - SCOPUS:85077852880

SN - 978-3-030-33245-7

T3 - Lecture Notes in Computer Science (LNCS)

SP - 695

EP - 713

BT - On the Move to Meaningful Internet Systems: OTM 2019 Conferences

A2 - Panetto, Hervé

A2 - Debruyne, Christophe

A2 - Hepp, Martin

A2 - Lewis, Dave

A2 - Agostino Ardagna, Claudio

A2 - Meersman, Robert

PB - Springer Nature Switzerland AG

T2 - Confederated International Conferences on Cooperative Information Systems, CoopIS 2019, Ontologies, Databases, and Applications of Semantics, ODBASE 2019, and Cloud and Trusted Computing, C and TC, held as part of OTM 2019

Y2 - 21 October 2019 through 25 October 2019

ER -