Exploring Future Challenges for Big Data in the Humanitarian Domain. / Bell, David; Lycett, Mark; Marshan, Alaa; Monaghan, Asmat.

In: Journal of Business Research, 13.10.2020.

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Exploring Future Challenges for Big Data in the Humanitarian Domain. / Bell, David; Lycett, Mark; Marshan, Alaa; Monaghan, Asmat.

In: Journal of Business Research, 13.10.2020.

Research output: Contribution to journalArticlepeer-review

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Bell, David ; Lycett, Mark ; Marshan, Alaa ; Monaghan, Asmat. / Exploring Future Challenges for Big Data in the Humanitarian Domain. In: Journal of Business Research. 2020.

BibTeX

@article{1463475de0954b3ba3fc05e605303fe2,
title = "Exploring Future Challenges for Big Data in the Humanitarian Domain",
abstract = "This paper examines the challenges of leveraging big data in the humanitarian sector in support of UN Sustainable Development Goal 17 “Partnerships for the Goals”. The full promise of Big Data is underpinned by a tacit assumption that the heterogeneous {\textquoteleft}exhaust trail{\textquoteright} of data is contextually relevant and sufficiently granular to be mined for value. This promise, however, relies on relationality – that patterns can be derived from combining different pieces of data that are of corresponding detail or that there are effective mechanisms to resolve differences in detail. Here, we present empirical work integrating eight heterogeneous datasets from the humanitarian domain to provide evidence of the inherent challenge of complexity resulting from differing levels of data granularity. In clarifying this challenge, we explore the reasons why it is manifest, discuss strategies for addressing it and, as our principal contribution, identify five propositions to guide future research.",
keywords = "Big Data, Veracity, Granularity, Heterogeneous datasets, Humanitarian, Value",
author = "David Bell and Mark Lycett and Alaa Marshan and Asmat Monaghan",
year = "2020",
month = oct,
day = "13",
doi = "10.1016/j.jbusres.2020.09.035",
language = "English",
journal = "Journal of Business Research",
issn = "0148-2963",
publisher = "Elsevier Inc.",

}

RIS

TY - JOUR

T1 - Exploring Future Challenges for Big Data in the Humanitarian Domain

AU - Bell, David

AU - Lycett, Mark

AU - Marshan, Alaa

AU - Monaghan, Asmat

PY - 2020/10/13

Y1 - 2020/10/13

N2 - This paper examines the challenges of leveraging big data in the humanitarian sector in support of UN Sustainable Development Goal 17 “Partnerships for the Goals”. The full promise of Big Data is underpinned by a tacit assumption that the heterogeneous ‘exhaust trail’ of data is contextually relevant and sufficiently granular to be mined for value. This promise, however, relies on relationality – that patterns can be derived from combining different pieces of data that are of corresponding detail or that there are effective mechanisms to resolve differences in detail. Here, we present empirical work integrating eight heterogeneous datasets from the humanitarian domain to provide evidence of the inherent challenge of complexity resulting from differing levels of data granularity. In clarifying this challenge, we explore the reasons why it is manifest, discuss strategies for addressing it and, as our principal contribution, identify five propositions to guide future research.

AB - This paper examines the challenges of leveraging big data in the humanitarian sector in support of UN Sustainable Development Goal 17 “Partnerships for the Goals”. The full promise of Big Data is underpinned by a tacit assumption that the heterogeneous ‘exhaust trail’ of data is contextually relevant and sufficiently granular to be mined for value. This promise, however, relies on relationality – that patterns can be derived from combining different pieces of data that are of corresponding detail or that there are effective mechanisms to resolve differences in detail. Here, we present empirical work integrating eight heterogeneous datasets from the humanitarian domain to provide evidence of the inherent challenge of complexity resulting from differing levels of data granularity. In clarifying this challenge, we explore the reasons why it is manifest, discuss strategies for addressing it and, as our principal contribution, identify five propositions to guide future research.

KW - Big Data

KW - Veracity

KW - Granularity

KW - Heterogeneous datasets

KW - Humanitarian

KW - Value

U2 - 10.1016/j.jbusres.2020.09.035

DO - 10.1016/j.jbusres.2020.09.035

M3 - Article

JO - Journal of Business Research

JF - Journal of Business Research

SN - 0148-2963

ER -