Towards 5G/6G Data Harmonization through NLP and Semantic Web Technologies

Mandeep Singh; Moatasim  Mahmoud; Stamatia Rizuo; Zaharias D.  Zaharis; Wenyan Wu; Vladimir K.  Poulkov; Pavlos I.  Lazaridis

doi:10.1109/ATOMS60779.2024.10921618

Towards 5G/6G Data Harmonization through NLP and Semantic Web Technologies

Mandeep Singh, Moatasim Mahmoud, Stamatia Rizuo, Zaharias D. Zaharis, Wenyan Wu, Vladimir K. Poulkov, Pavlos I. Lazaridis

College of Engineering

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

Abstract

Telecommunication systems utilize several mechanisms to collect data from 5G/6G-enabled IoT. In the 5G/6G community, various AI techniques and tools are applied to 5G/6G data to monitor, predict, and make decisions. Therefore, 5G/6G data must be interoperable for monitoring, prediction, and decision support systems. However, 5G/6G data are typically mapped in local data models for local applications, which poses challenges to using them in different or cross-domain applications due to a lack of interoperability issues. In this paper, we propose an approach to support and enhance the interoperability of 5G/6G data through NLP and Semantic Web technologies to achieve 5G/6G data harmonization

Original language	English
Title of host publication	2024 Advanced Topics on Measurement and Simulation (ATOMS)
ISBN (Electronic)	9798350358377
DOIs	https://doi.org/10.1109/ATOMS60779.2024.10921618
Publication status	Published (VoR) - 19 Mar 2024

Keywords

Semantic Web
data harmonization
5G/6G
NLP

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10.1109/ATOMS60779.2024.10921618

Cite this

@inproceedings{f44283269cf7455b92988783fbb0a864,

title = "Towards 5G/6G Data Harmonization through NLP and Semantic Web Technologies",

abstract = "Telecommunication systems utilize several mechanisms to collect data from 5G/6G-enabled IoT. In the 5G/6G community, various AI techniques and tools are applied to 5G/6G data to monitor, predict, and make decisions. Therefore, 5G/6G data must be interoperable for monitoring, prediction, and decision support systems. However, 5G/6G data are typically mapped in local data models for local applications, which poses challenges to using them in different or cross-domain applications due to a lack of interoperability issues. In this paper, we propose an approach to support and enhance the interoperability of 5G/6G data through NLP and Semantic Web technologies to achieve 5G/6G data harmonization",

keywords = "Semantic Web, data harmonization, 5G/6G, NLP",

author = "Mandeep Singh and Moatasim Mahmoud and Stamatia Rizuo and Zaharis, {Zaharias D.} and Wenyan Wu and Poulkov, {Vladimir K.} and Lazaridis, {Pavlos I.}",

year = "2024",

month = mar,

day = "19",

doi = "10.1109/ATOMS60779.2024.10921618",

language = "English",

booktitle = "2024 Advanced Topics on Measurement and Simulation (ATOMS)",

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T1 - Towards 5G/6G Data Harmonization through NLP and Semantic Web Technologies

AU - Singh, Mandeep

AU - Mahmoud, Moatasim

AU - Rizuo, Stamatia

AU - Zaharis, Zaharias D.

AU - Wu, Wenyan

AU - Poulkov, Vladimir K.

AU - Lazaridis, Pavlos I.

PY - 2024/3/19

Y1 - 2024/3/19

N2 - Telecommunication systems utilize several mechanisms to collect data from 5G/6G-enabled IoT. In the 5G/6G community, various AI techniques and tools are applied to 5G/6G data to monitor, predict, and make decisions. Therefore, 5G/6G data must be interoperable for monitoring, prediction, and decision support systems. However, 5G/6G data are typically mapped in local data models for local applications, which poses challenges to using them in different or cross-domain applications due to a lack of interoperability issues. In this paper, we propose an approach to support and enhance the interoperability of 5G/6G data through NLP and Semantic Web technologies to achieve 5G/6G data harmonization

AB - Telecommunication systems utilize several mechanisms to collect data from 5G/6G-enabled IoT. In the 5G/6G community, various AI techniques and tools are applied to 5G/6G data to monitor, predict, and make decisions. Therefore, 5G/6G data must be interoperable for monitoring, prediction, and decision support systems. However, 5G/6G data are typically mapped in local data models for local applications, which poses challenges to using them in different or cross-domain applications due to a lack of interoperability issues. In this paper, we propose an approach to support and enhance the interoperability of 5G/6G data through NLP and Semantic Web technologies to achieve 5G/6G data harmonization

KW - Semantic Web

KW - data harmonization

KW - 5G/6G

KW - NLP

U2 - 10.1109/ATOMS60779.2024.10921618

DO - 10.1109/ATOMS60779.2024.10921618

M3 - Conference contribution

BT - 2024 Advanced Topics on Measurement and Simulation (ATOMS)

ER -

Towards 5G/6G Data Harmonization through NLP and Semantic Web Technologies

Abstract

Keywords

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