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A semantic approach to enable data integration for the domain of flood risk management

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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A semantic approach to enable data integration for the domain of flood risk management. / Nundloll, Vatsala; Lamb, Rob; Hankin, Barry et al.
In: Environmental Challenges, Vol. 3, 100064, 30.04.2021.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Nundloll, V, Lamb, R, Hankin, B & Blair, G 2021, 'A semantic approach to enable data integration for the domain of flood risk management', Environmental Challenges, vol. 3, 100064. https://doi.org/10.1016/j.envc.2021.100064

APA

Nundloll, V., Lamb, R., Hankin, B., & Blair, G. (2021). A semantic approach to enable data integration for the domain of flood risk management. Environmental Challenges, 3, Article 100064. https://doi.org/10.1016/j.envc.2021.100064

Vancouver

Nundloll V, Lamb R, Hankin B, Blair G. A semantic approach to enable data integration for the domain of flood risk management. Environmental Challenges. 2021 Apr 30;3:100064. Epub 2021 Mar 2. doi: 10.1016/j.envc.2021.100064

Author

Nundloll, Vatsala ; Lamb, Rob ; Hankin, Barry et al. / A semantic approach to enable data integration for the domain of flood risk management. In: Environmental Challenges. 2021 ; Vol. 3.

Bibtex

@article{9fef61812a2f4153b1786ad26fe5a814,
title = "A semantic approach to enable data integration for the domain of flood risk management",
abstract = "With so many things around us continuously producing and processing data, be it mobile phones, or sensors attached to devices, or satellites sitting thousands of kilometres above our heads, data is becoming increasingly heterogeneous. Scientists are inevitably faced with data challenges, coined as the 4 V{\textquoteright}s of data - volume, variety, velocity and veracity. In this paper, we address the issue of data variety. The task of integrating and querying such heterogeneous data is further compounded if the data is in unstructured form. We hence propose an approach using Semantic Web and Natural Language Processing techniques to resolve the heterogeneity arising in data formats, bring together structured and unstructured data and provide a unified data model to query from disparate data sets.",
keywords = "Ontologies, Structured data, Unstructured data, Semantic integration, Natural language processing, Flood risk management",
author = "Vatsala Nundloll and Rob Lamb and Barry Hankin and Gordon Blair",
year = "2021",
month = apr,
day = "30",
doi = "10.1016/j.envc.2021.100064",
language = "English",
volume = "3",
journal = "Environmental Challenges",
issn = "2667-0100",
publisher = "Elsevier BV",

}

RIS

TY - JOUR

T1 - A semantic approach to enable data integration for the domain of flood risk management

AU - Nundloll, Vatsala

AU - Lamb, Rob

AU - Hankin, Barry

AU - Blair, Gordon

PY - 2021/4/30

Y1 - 2021/4/30

N2 - With so many things around us continuously producing and processing data, be it mobile phones, or sensors attached to devices, or satellites sitting thousands of kilometres above our heads, data is becoming increasingly heterogeneous. Scientists are inevitably faced with data challenges, coined as the 4 V’s of data - volume, variety, velocity and veracity. In this paper, we address the issue of data variety. The task of integrating and querying such heterogeneous data is further compounded if the data is in unstructured form. We hence propose an approach using Semantic Web and Natural Language Processing techniques to resolve the heterogeneity arising in data formats, bring together structured and unstructured data and provide a unified data model to query from disparate data sets.

AB - With so many things around us continuously producing and processing data, be it mobile phones, or sensors attached to devices, or satellites sitting thousands of kilometres above our heads, data is becoming increasingly heterogeneous. Scientists are inevitably faced with data challenges, coined as the 4 V’s of data - volume, variety, velocity and veracity. In this paper, we address the issue of data variety. The task of integrating and querying such heterogeneous data is further compounded if the data is in unstructured form. We hence propose an approach using Semantic Web and Natural Language Processing techniques to resolve the heterogeneity arising in data formats, bring together structured and unstructured data and provide a unified data model to query from disparate data sets.

KW - Ontologies

KW - Structured data

KW - Unstructured data

KW - Semantic integration

KW - Natural language processing

KW - Flood risk management

U2 - 10.1016/j.envc.2021.100064

DO - 10.1016/j.envc.2021.100064

M3 - Journal article

VL - 3

JO - Environmental Challenges

JF - Environmental Challenges

SN - 2667-0100

M1 - 100064

ER -