Data stories and dashboard development: a case study of an aviation schedule and delay causes

In this case study, five key processes in modelling a data story of aviation data patterns during COVID-19 have been executed. It started with the collection of secondary data from relevant sources. Data inspection, transformation, and preparation activities, including data cleaning, filtering, and...

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發表在:IOP Conference Series: Earth and Environmental Science
主要作者: 2-s2.0-85152937878
格式: Conference paper
語言:English
出版: Institute of Physics 2023
在線閱讀:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85152937878&doi=10.1088%2f1755-1315%2f1151%2f1%2f012049&partnerID=40&md5=b7bbd680796c5be8b905c4b8ea5b27c0
id Salleh S.S.; Shukri A.S.; Othman N.I.; Saad N.S.M.
spelling Salleh S.S.; Shukri A.S.; Othman N.I.; Saad N.S.M.
2-s2.0-85152937878
Data stories and dashboard development: a case study of an aviation schedule and delay causes
2023
IOP Conference Series: Earth and Environmental Science
1151
1
10.1088/1755-1315/1151/1/012049
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85152937878&doi=10.1088%2f1755-1315%2f1151%2f1%2f012049&partnerID=40&md5=b7bbd680796c5be8b905c4b8ea5b27c0
In this case study, five key processes in modelling a data story of aviation data patterns during COVID-19 have been executed. It started with the collection of secondary data from relevant sources. Data inspection, transformation, and preparation activities, including data cleaning, filtering, and sampling, are all included in this work. Iterative exploratory data analysis (EDA) has been conducted to determine the pattern of each independent attribute, followed by an assessment after the data story is modelled and integrated on a dashboard. The questionnaire has been distributed and the visuals were assessed by giving respondents a few tasks to interpret stories based on their comprehension. The result shows that the data stories have been interpreted in a similar narrative by all the respondents. The overall mean score is 4.71, and this significantly shows that the respondents agree and strongly agree that the visual objects help in communicating patterns and stories. The overall process gives researchers experience and guidelines for future work. Overall, the objectives of the study have been met. Nevertheless, it gives researchers a lot of experience in interpreting data, cleansing and transformation, analysis, modelling the visualisation by selecting suitable charts, and integrating the objects together into a dashboard. © 2023 American Institute of Physics Inc.. All rights reserved.
Institute of Physics
17551307
English
Conference paper
All Open Access; Gold Open Access
author 2-s2.0-85152937878
spellingShingle 2-s2.0-85152937878
Data stories and dashboard development: a case study of an aviation schedule and delay causes
author_facet 2-s2.0-85152937878
author_sort 2-s2.0-85152937878
title Data stories and dashboard development: a case study of an aviation schedule and delay causes
title_short Data stories and dashboard development: a case study of an aviation schedule and delay causes
title_full Data stories and dashboard development: a case study of an aviation schedule and delay causes
title_fullStr Data stories and dashboard development: a case study of an aviation schedule and delay causes
title_full_unstemmed Data stories and dashboard development: a case study of an aviation schedule and delay causes
title_sort Data stories and dashboard development: a case study of an aviation schedule and delay causes
publishDate 2023
container_title IOP Conference Series: Earth and Environmental Science
container_volume 1151
container_issue 1
doi_str_mv 10.1088/1755-1315/1151/1/012049
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85152937878&doi=10.1088%2f1755-1315%2f1151%2f1%2f012049&partnerID=40&md5=b7bbd680796c5be8b905c4b8ea5b27c0
description In this case study, five key processes in modelling a data story of aviation data patterns during COVID-19 have been executed. It started with the collection of secondary data from relevant sources. Data inspection, transformation, and preparation activities, including data cleaning, filtering, and sampling, are all included in this work. Iterative exploratory data analysis (EDA) has been conducted to determine the pattern of each independent attribute, followed by an assessment after the data story is modelled and integrated on a dashboard. The questionnaire has been distributed and the visuals were assessed by giving respondents a few tasks to interpret stories based on their comprehension. The result shows that the data stories have been interpreted in a similar narrative by all the respondents. The overall mean score is 4.71, and this significantly shows that the respondents agree and strongly agree that the visual objects help in communicating patterns and stories. The overall process gives researchers experience and guidelines for future work. Overall, the objectives of the study have been met. Nevertheless, it gives researchers a lot of experience in interpreting data, cleansing and transformation, analysis, modelling the visualisation by selecting suitable charts, and integrating the objects together into a dashboard. © 2023 American Institute of Physics Inc.. All rights reserved.
publisher Institute of Physics
issn 17551307
language English
format Conference paper
accesstype All Open Access; Gold Open Access
record_format scopus
collection Scopus
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