SEAL: semantically enriched authoring in LATEX-A model for scientific discourse

Imran Ihsan; Mohib Ullah; Rafi Ullah Khan; M. Irfan Uddin; Abdullah Alharbi; Wael Alosaimi

doi:10.1109/ACCESS.2022.3145954

SEAL: semantically enriched authoring in LATEX-A model for scientific discourse

Imran Ihsan^*, Mohib Ullah, Rafi Ullah Khan, M. Irfan Uddin, Abdullah Alharbi, Wael Alosaimi

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

3 Citations (Scopus)

80 Downloads (Pure)

Abstract

Semantic tags can enrich citation graphs by inter-connecting papers with citation reasons. One of the best sources of knowledge to tell the reason for citation is the author himself. Integrating these reasons in an authoring system can help authors to choose a reason while citing. We examined various Human and Automatic authoring systems for integration of citation reasons. However, to the best of our knowledge, no such system exists that facilities authors to integrate the reasons while citing. Same is the case with Cite Packages. This research proposes integration of CCRO:Citations' Context and Reasons Ontology's (Ihsan and Qadir, 2019) taxonomic hierarchy of reasons within document. We have developed a CCRO Package to semantically tag citations with reasons and to create an intra-discourse relation between research articles. Furthermore, embedding these structures within RDF Data Store enables the creation of knowledge graphs that become a foundation artifact for the Semantic Scientific Discourse.

Original language	English
Pages (from-to)	13525-13535
Number of pages	11
Journal	IEEE Access
Volume	10
DOIs	https://doi.org/10.1109/ACCESS.2022.3145954
Publication status	Published - 2022
Externally published	Yes

Bibliographical note

Copyright the Author(s). Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

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Publisher version (open access)Final published version, 2.52 MBLicence: CC BY

Cite this

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title = "SEAL: semantically enriched authoring in LATEX-A model for scientific discourse",

abstract = "Semantic tags can enrich citation graphs by inter-connecting papers with citation reasons. One of the best sources of knowledge to tell the reason for citation is the author himself. Integrating these reasons in an authoring system can help authors to choose a reason while citing. We examined various Human and Automatic authoring systems for integration of citation reasons. However, to the best of our knowledge, no such system exists that facilities authors to integrate the reasons while citing. Same is the case with Cite Packages. This research proposes integration of CCRO:Citations' Context and Reasons Ontology's (Ihsan and Qadir, 2019) taxonomic hierarchy of reasons within document. We have developed a CCRO Package to semantically tag citations with reasons and to create an intra-discourse relation between research articles. Furthermore, embedding these structures within RDF Data Store enables the creation of knowledge graphs that become a foundation artifact for the Semantic Scientific Discourse.",

author = "Imran Ihsan and Mohib Ullah and Khan, {Rafi Ullah} and Uddin, {M. Irfan} and Abdullah Alharbi and Wael Alosaimi",

note = "Copyright the Author(s). Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.",

year = "2022",

doi = "10.1109/ACCESS.2022.3145954",

language = "English",

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T2 - semantically enriched authoring in LATEX-A model for scientific discourse

AU - Ihsan, Imran

AU - Ullah, Mohib

AU - Khan, Rafi Ullah

AU - Uddin, M. Irfan

AU - Alharbi, Abdullah

AU - Alosaimi, Wael

N1 - Copyright the Author(s). Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

PY - 2022

Y1 - 2022

N2 - Semantic tags can enrich citation graphs by inter-connecting papers with citation reasons. One of the best sources of knowledge to tell the reason for citation is the author himself. Integrating these reasons in an authoring system can help authors to choose a reason while citing. We examined various Human and Automatic authoring systems for integration of citation reasons. However, to the best of our knowledge, no such system exists that facilities authors to integrate the reasons while citing. Same is the case with Cite Packages. This research proposes integration of CCRO:Citations' Context and Reasons Ontology's (Ihsan and Qadir, 2019) taxonomic hierarchy of reasons within document. We have developed a CCRO Package to semantically tag citations with reasons and to create an intra-discourse relation between research articles. Furthermore, embedding these structures within RDF Data Store enables the creation of knowledge graphs that become a foundation artifact for the Semantic Scientific Discourse.

AB - Semantic tags can enrich citation graphs by inter-connecting papers with citation reasons. One of the best sources of knowledge to tell the reason for citation is the author himself. Integrating these reasons in an authoring system can help authors to choose a reason while citing. We examined various Human and Automatic authoring systems for integration of citation reasons. However, to the best of our knowledge, no such system exists that facilities authors to integrate the reasons while citing. Same is the case with Cite Packages. This research proposes integration of CCRO:Citations' Context and Reasons Ontology's (Ihsan and Qadir, 2019) taxonomic hierarchy of reasons within document. We have developed a CCRO Package to semantically tag citations with reasons and to create an intra-discourse relation between research articles. Furthermore, embedding these structures within RDF Data Store enables the creation of knowledge graphs that become a foundation artifact for the Semantic Scientific Discourse.

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JO - IEEE Access

JF - IEEE Access

ER -

SEAL: semantically enriched authoring in LATEX-A model for scientific discourse

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