Standard

Creating Core Ontology for Social Sciences Empirical Data Integration. / Кудрявцев, Дмитрий Вячеславович; Гаврилова, Татьяна Альбертовна; Беглер, Алёна Маратовна.

Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K2020) - Volume 2: KEOD. 2020. p. 267-274.

Research output: Chapter in Book/Report/Conference proceeding › Article in an anthology › Research › peer-review

Harvard

Кудрявцев, ДВ, Гаврилова, ТА & Беглер, АМ 2020, Creating Core Ontology for Social Sciences Empirical Data Integration. in Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K2020) - Volume 2: KEOD. pp. 267-274, 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, 2/11/20.

APA

Кудрявцев, Д. В., Гаврилова, Т. А., & Беглер, А. М. (2020). Creating Core Ontology for Social Sciences Empirical Data Integration. In Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K2020) - Volume 2: KEOD (pp. 267-274)

Vancouver

Кудрявцев ДВ, Гаврилова ТА, Беглер АМ. Creating Core Ontology for Social Sciences Empirical Data Integration. In Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K2020) - Volume 2: KEOD. 2020. p. 267-274

Author

Кудрявцев, Дмитрий Вячеславович ; Гаврилова, Татьяна Альбертовна ; Беглер, Алёна Маратовна. / Creating Core Ontology for Social Sciences Empirical Data Integration. Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K2020) - Volume 2: KEOD. 2020. pp. 267-274

BibTeX

@inbook{3f25a4ae394c4a16aba202ea58020379,
title = "Creating Core Ontology for Social Sciences Empirical Data Integration",
abstract = "There exist several dozens of metadata standards for empirical research data, making it difficult for users to choose and apply such standards. Consequently, the integration of datasets from similar empirical studies for further knowledge acquisition is highly constrained. To resolve this problem, an ontology for social science research data integration (Empirion-core) has been developed. The ontology reuses existing data integration schemas: DDI-RDF Discovery Vocabulary, Generic Statistical Information Model, Core Ontology for Scientific Research Activities, Data Catalog Vocabulary, and DCMI Metadata Terms. It consists of five subontologies that provide concepts for empirical datasets description: Information resource ontology, Research activity ontology, Research coverage ontology, Measurement ontology, and Sampling ontology.",
keywords = "Ontology Reuse, Empirical Data Integration, Empirical Research Datasets, Knowledge Engineering",
author = "Кудрявцев, {Дмитрий Вячеславович} and Гаврилова, {Татьяна Альбертовна} and Беглер, {Алёна Маратовна}",
note = " Kudryavtsev, D. Creating Core Ontology for Social Sciences Empirical Data Integration / D. Kudryavtsev, T. Gavrilova, A. Begler // Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K2020) - Volume 2: KEOD, 2020. - P. 267-274.; 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, KEOD ; Conference date: 02-11-2020",
year = "2020",
language = "English",
pages = "267--274",
booktitle = "Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K2020) - Volume 2: KEOD",
url = "http://www.keod.ic3k.org/?y=2020",

}

RIS

TY - CHAP

T1 - Creating Core Ontology for Social Sciences Empirical Data Integration

AU - Кудрявцев, Дмитрий Вячеславович

AU - Гаврилова, Татьяна Альбертовна

AU - Беглер, Алёна Маратовна

N1 - Conference code: 12

PY - 2020

Y1 - 2020

N2 - There exist several dozens of metadata standards for empirical research data, making it difficult for users to choose and apply such standards. Consequently, the integration of datasets from similar empirical studies for further knowledge acquisition is highly constrained. To resolve this problem, an ontology for social science research data integration (Empirion-core) has been developed. The ontology reuses existing data integration schemas: DDI-RDF Discovery Vocabulary, Generic Statistical Information Model, Core Ontology for Scientific Research Activities, Data Catalog Vocabulary, and DCMI Metadata Terms. It consists of five subontologies that provide concepts for empirical datasets description: Information resource ontology, Research activity ontology, Research coverage ontology, Measurement ontology, and Sampling ontology.

AB - There exist several dozens of metadata standards for empirical research data, making it difficult for users to choose and apply such standards. Consequently, the integration of datasets from similar empirical studies for further knowledge acquisition is highly constrained. To resolve this problem, an ontology for social science research data integration (Empirion-core) has been developed. The ontology reuses existing data integration schemas: DDI-RDF Discovery Vocabulary, Generic Statistical Information Model, Core Ontology for Scientific Research Activities, Data Catalog Vocabulary, and DCMI Metadata Terms. It consists of five subontologies that provide concepts for empirical datasets description: Information resource ontology, Research activity ontology, Research coverage ontology, Measurement ontology, and Sampling ontology.

KW - Ontology Reuse

KW - Empirical Data Integration

KW - Empirical Research Datasets

KW - Knowledge Engineering

M3 - Article in an anthology

SP - 267

EP - 274

BT - Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K2020) - Volume 2: KEOD

T2 - 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management

Y2 - 2 November 2020

ER -

ID: 75121324