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Semantic Annotation of Data Processing Pipelines in Scientific Publications. / Mesbah, Sepideh; Fragkeskos, Kyriakos; Lofi, Christoph; Bozzon, Alessandro; Houben, Geert-Jan.

The Semantic Web: 14th International Conference, ESWC 2017, Proceedings Part 1. ed. / Eva Blomqvist; Diana Maynard; Aldo Gangemi; Rinke Hoekstra; Pascal Hitzler; Olaf Hartig. Cham : Springer International Publishing AG, 2017. p. 321-336 (Lecture Notes in Computer Science; Vol. 10249).

Research output: Scientific - peer-reviewConference contribution

Harvard

Mesbah, S, Fragkeskos, K, Lofi, C, Bozzon, A & Houben, G-J 2017, Semantic Annotation of Data Processing Pipelines in Scientific Publications. in E Blomqvist, D Maynard, A Gangemi, R Hoekstra, P Hitzler & O Hartig (eds), The Semantic Web: 14th International Conference, ESWC 2017, Proceedings Part 1. Lecture Notes in Computer Science, vol. 10249, Springer International Publishing AG, Cham, pp. 321-336, Extended Semantic Web Conference, Portorož, Slovenia, 28/05/17. DOI: 10.1007/978-3-319-58068-5_20

APA

Mesbah, S., Fragkeskos, K., Lofi, C., Bozzon, A., & Houben, G-J. (2017). Semantic Annotation of Data Processing Pipelines in Scientific Publications. In E. Blomqvist, D. Maynard, A. Gangemi, R. Hoekstra, P. Hitzler, & O. Hartig (Eds.), The Semantic Web: 14th International Conference, ESWC 2017, Proceedings Part 1 (pp. 321-336). (Lecture Notes in Computer Science; Vol. 10249). Cham: Springer International Publishing AG. DOI: 10.1007/978-3-319-58068-5_20

Vancouver

Mesbah S, Fragkeskos K, Lofi C, Bozzon A, Houben G-J. Semantic Annotation of Data Processing Pipelines in Scientific Publications. In Blomqvist E, Maynard D, Gangemi A, Hoekstra R, Hitzler P, Hartig O, editors, The Semantic Web: 14th International Conference, ESWC 2017, Proceedings Part 1. Cham: Springer International Publishing AG. 2017. p. 321-336. (Lecture Notes in Computer Science). Available from, DOI: 10.1007/978-3-319-58068-5_20

Author

Mesbah, Sepideh ; Fragkeskos, Kyriakos ; Lofi, Christoph ; Bozzon, Alessandro ; Houben, Geert-Jan. / Semantic Annotation of Data Processing Pipelines in Scientific Publications. The Semantic Web: 14th International Conference, ESWC 2017, Proceedings Part 1. editor / Eva Blomqvist ; Diana Maynard ; Aldo Gangemi ; Rinke Hoekstra ; Pascal Hitzler ; Olaf Hartig. Cham : Springer International Publishing AG, 2017. pp. 321-336 (Lecture Notes in Computer Science).

BibTeX

@inbook{0f278790e7f4469c911a541f63ff4e01,
title = "Semantic Annotation of Data Processing Pipelines in Scientific Publications",
abstract = "Data processing pipelines are a core object of interest for data scientist and practitioners operating in a variety of data-related application domains. To effectively capitalise on the experience gained in the creation and adoption of such pipelines, the need arises for mechanisms able to capture knowledge about datasets of interest, data processing methods designed to achieve a given goal, and the performance achieved when applying such methods to the considered datasets. However, due to its distributed and often unstructured nature, this knowledge is not easily accessible. In this paper, we use (scientific) publications as source of knowledge about Data Processing Pipelines. We describe a method designed to classify sentences according to the nature of the contained information (i.e. scientific objective, dataset, method, software, result), and to extract relevant named entities. The extracted information is then semantically annotated and published as linked data in open knowledge repositories according to the DMS ontology for data processing metadata. To demonstrate the effectiveness and performance of our approach, we present the results of a quantitative and qualitative analysis performed on four different conference series.",
author = "Sepideh Mesbah and Kyriakos Fragkeskos and Christoph Lofi and Alessandro Bozzon and Geert-Jan Houben",
year = "2017",
month = "5",
doi = "10.1007/978-3-319-58068-5_20",
isbn = "978-3-319-58067-8",
series = "Lecture Notes in Computer Science",
publisher = "Springer International Publishing AG",
pages = "321--336",
editor = "Eva Blomqvist and Diana Maynard and Aldo Gangemi and Rinke Hoekstra and Pascal Hitzler and Olaf Hartig",
booktitle = "The Semantic Web",
address = "Switzerland",

}

RIS

TY - CHAP

T1 - Semantic Annotation of Data Processing Pipelines in Scientific Publications

AU - Mesbah,Sepideh

AU - Fragkeskos,Kyriakos

AU - Lofi,Christoph

AU - Bozzon,Alessandro

AU - Houben,Geert-Jan

PY - 2017/5/16

Y1 - 2017/5/16

N2 - Data processing pipelines are a core object of interest for data scientist and practitioners operating in a variety of data-related application domains. To effectively capitalise on the experience gained in the creation and adoption of such pipelines, the need arises for mechanisms able to capture knowledge about datasets of interest, data processing methods designed to achieve a given goal, and the performance achieved when applying such methods to the considered datasets. However, due to its distributed and often unstructured nature, this knowledge is not easily accessible. In this paper, we use (scientific) publications as source of knowledge about Data Processing Pipelines. We describe a method designed to classify sentences according to the nature of the contained information (i.e. scientific objective, dataset, method, software, result), and to extract relevant named entities. The extracted information is then semantically annotated and published as linked data in open knowledge repositories according to the DMS ontology for data processing metadata. To demonstrate the effectiveness and performance of our approach, we present the results of a quantitative and qualitative analysis performed on four different conference series.

AB - Data processing pipelines are a core object of interest for data scientist and practitioners operating in a variety of data-related application domains. To effectively capitalise on the experience gained in the creation and adoption of such pipelines, the need arises for mechanisms able to capture knowledge about datasets of interest, data processing methods designed to achieve a given goal, and the performance achieved when applying such methods to the considered datasets. However, due to its distributed and often unstructured nature, this knowledge is not easily accessible. In this paper, we use (scientific) publications as source of knowledge about Data Processing Pipelines. We describe a method designed to classify sentences according to the nature of the contained information (i.e. scientific objective, dataset, method, software, result), and to extract relevant named entities. The extracted information is then semantically annotated and published as linked data in open knowledge repositories according to the DMS ontology for data processing metadata. To demonstrate the effectiveness and performance of our approach, we present the results of a quantitative and qualitative analysis performed on four different conference series.

U2 - 10.1007/978-3-319-58068-5_20

DO - 10.1007/978-3-319-58068-5_20

M3 - Conference contribution

SN - 978-3-319-58067-8

T3 - Lecture Notes in Computer Science

SP - 321

EP - 336

BT - The Semantic Web

PB - Springer International Publishing AG

ER -

ID: 19689010