Plant data visualisation using network graphs

Background The amount of plant data such as taxonomical classification, morphological characteristics, ecological attributes and geological distribution in textual and image forms has increased rapidly due to emerging research and technologies. Therefore, it is crucial for experts as well as the pub...

Full description

Bibliographic Details
Main Authors: Afrina Adlyna Mohamad-Matrol, Siow-Wee Chang, Arpah Abu
Format: Article
Language:English
Published: PeerJ Inc. 2018-08-01
Series:PeerJ
Subjects:
Online Access:https://peerj.com/articles/5579.pdf
_version_ 1797424338650005504
author Afrina Adlyna Mohamad-Matrol
Siow-Wee Chang
Arpah Abu
author_facet Afrina Adlyna Mohamad-Matrol
Siow-Wee Chang
Arpah Abu
author_sort Afrina Adlyna Mohamad-Matrol
collection DOAJ
description Background The amount of plant data such as taxonomical classification, morphological characteristics, ecological attributes and geological distribution in textual and image forms has increased rapidly due to emerging research and technologies. Therefore, it is crucial for experts as well as the public to discern meaningful relationships from this vast amount of data using appropriate methods. The data are often presented in lengthy texts and tables, which make gaining new insights difficult. The study proposes a visual-based representation to display data to users in a meaningful way. This method emphasises the relationships between different data sets. Method This study involves four main steps which translate text-based results from Extensible Markup Language (XML) serialisation format into graphs. The four steps include: (1) conversion of ontological dataset as graph model data; (2) query from graph model data; (3) transformation of text-based results in XML serialisation format into a graphical form; and (4) display of results to the user via a graphical user interface (GUI). Ontological data for plants and samples of trees and shrubs were used as the dataset to demonstrate how plant-based data could be integrated into the proposed data visualisation. Results A visualisation system named plant visualisation system was developed. This system provides a GUI that enables users to perform the query process, as well as a graphical viewer to display the results of the query in the form of a network graph. The efficiency of the developed visualisation system was measured by performing two types of user evaluations: a usability heuristics evaluation, and a query and visualisation evaluation. Discussion The relationships between the data were visualised, enabling the users to easily infer the knowledge and correlations between data. The results from the user evaluation show that the proposed visualisation system is suitable for both expert and novice users, with or without computer skills. This technique demonstrates the practicability of using a computer assisted-tool by providing cognitive analysis for understanding relationships between data. Therefore, the results benefit not only botanists, but also novice users, especially those that are interested to know more about plants.
first_indexed 2024-03-09T08:00:48Z
format Article
id doaj.art-a205cc9c905542bfb4cecd28b8de7e0f
institution Directory Open Access Journal
issn 2167-8359
language English
last_indexed 2024-03-09T08:00:48Z
publishDate 2018-08-01
publisher PeerJ Inc.
record_format Article
series PeerJ
spelling doaj.art-a205cc9c905542bfb4cecd28b8de7e0f2023-12-03T00:47:36ZengPeerJ Inc.PeerJ2167-83592018-08-016e557910.7717/peerj.5579Plant data visualisation using network graphsAfrina Adlyna Mohamad-Matrol0Siow-Wee Chang1Arpah Abu2Institute of Biological Sciences, Faculty of Science, University of Malaya, Kuala Lumpur, MalaysiaInstitute of Biological Sciences, Faculty of Science, University of Malaya, Kuala Lumpur, MalaysiaInstitute of Biological Sciences, Faculty of Science, University of Malaya, Kuala Lumpur, MalaysiaBackground The amount of plant data such as taxonomical classification, morphological characteristics, ecological attributes and geological distribution in textual and image forms has increased rapidly due to emerging research and technologies. Therefore, it is crucial for experts as well as the public to discern meaningful relationships from this vast amount of data using appropriate methods. The data are often presented in lengthy texts and tables, which make gaining new insights difficult. The study proposes a visual-based representation to display data to users in a meaningful way. This method emphasises the relationships between different data sets. Method This study involves four main steps which translate text-based results from Extensible Markup Language (XML) serialisation format into graphs. The four steps include: (1) conversion of ontological dataset as graph model data; (2) query from graph model data; (3) transformation of text-based results in XML serialisation format into a graphical form; and (4) display of results to the user via a graphical user interface (GUI). Ontological data for plants and samples of trees and shrubs were used as the dataset to demonstrate how plant-based data could be integrated into the proposed data visualisation. Results A visualisation system named plant visualisation system was developed. This system provides a GUI that enables users to perform the query process, as well as a graphical viewer to display the results of the query in the form of a network graph. The efficiency of the developed visualisation system was measured by performing two types of user evaluations: a usability heuristics evaluation, and a query and visualisation evaluation. Discussion The relationships between the data were visualised, enabling the users to easily infer the knowledge and correlations between data. The results from the user evaluation show that the proposed visualisation system is suitable for both expert and novice users, with or without computer skills. This technique demonstrates the practicability of using a computer assisted-tool by providing cognitive analysis for understanding relationships between data. Therefore, the results benefit not only botanists, but also novice users, especially those that are interested to know more about plants.https://peerj.com/articles/5579.pdfNetwork graphData visualisationOntologyPlantVizPlant knowledge
spellingShingle Afrina Adlyna Mohamad-Matrol
Siow-Wee Chang
Arpah Abu
Plant data visualisation using network graphs
PeerJ
Network graph
Data visualisation
Ontology
PlantViz
Plant knowledge
title Plant data visualisation using network graphs
title_full Plant data visualisation using network graphs
title_fullStr Plant data visualisation using network graphs
title_full_unstemmed Plant data visualisation using network graphs
title_short Plant data visualisation using network graphs
title_sort plant data visualisation using network graphs
topic Network graph
Data visualisation
Ontology
PlantViz
Plant knowledge
url https://peerj.com/articles/5579.pdf
work_keys_str_mv AT afrinaadlynamohamadmatrol plantdatavisualisationusingnetworkgraphs
AT siowweechang plantdatavisualisationusingnetworkgraphs
AT arpahabu plantdatavisualisationusingnetworkgraphs