Requirements of Data Visualisation Tools to Analyse Big Data: A Structured Literature Review

Lowe, Joy; Matthee, Machdel

doi:10.1007/978-3-030-44999-5_39

Cited by 8 publications

(7 citation statements)

References 37 publications

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“…Visualization can also give a better understanding of relationships (Li et al, 2016). (Lowe & Matthee 2020) have performed a systematic review of the literature, identifying the requirements of visualization tools, classifying them into six groups: dimensionality reduction, data reduction, scalability and readability, interactivity, rapid retrieval of results, and user assistance.…”

Section: Review Of Literaturementioning

confidence: 99%

Visualization, Serious Games and Decision Making

Benitez

Herrera²,

Pacheco³

et al. 2022

ECGBL

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One of the most important objectives of serious games is to detonate behavioral changes of participants. Serious games generate engagement, they are meaningful, entertaining, and immersive. However, when the game represents a complex system, it contains a great number of variables and the relationship between its decision components are not entirely clear. Consequently, it is necessary to offer a set of tools that increase the data visualization of the players and help in the decision-making process must be provided. In our university, logistics professors have designed a simulator for logistics decision making. On the one hand, the game has gained acceptance from the student community, but on the other hand, several students do not accomplish a satisfactory performance. Therefore, these students fail to notice lots of variable interrelationships in the game, and they do not develop the skill required to follow a good decision-making process. The goal is two folded. On the one hand, the improvement of the participant's comprehension of a complex logistical system must be reached. On the other hand, the clarity on the decision-making process has to be laid out. A set of visualization support tools were created to accomplish those objectives. Neither of the tools aim to influence the decision-making process nor to show decision alternatives to the participant, but to highlight a few key performance indicators, constraints, and data that the students can use when making the decisions. In this paper it is presented how the participants have improved their understanding about the logistic system represented in the game, when the support tools are used. Moreover, their motivation has increased, they are more involved and committed to learn. Overall, their decision-making strategies have been modified and they have shown a better comprehension of the game structure. This paper contributes to underline the importance of visualization in student's learning, considering that currently big data, industry 4.0, as well as internet of things have gained a significant relevance in our everyday life. The design of strategic games involving these new variables are necessary. The more complex a system, the greater the number of visualization tools to strengthen the comprehension of the system are required.

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Section: Review Of Literaturementioning

confidence: 99%

Visualization, Serious Games and Decision Making

Benitez

Herrera²,

Pacheco³

et al. 2022

ECGBL

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“…Schrittzahl, Herzschlag oder UV-Strahlung, selbst überwachen und die Ergebnisse zur Verbesserung des Gesundheitsverhaltens und auch langfristig zur Verbesserung des Gesundheitszustands nutzen können [1]. [6,20], Data Literacy [16,25], Effizienzsteigerung [1,2,35], Ethik und Zugang [10,24,27,35], Risikoanalyse und Prognose [3,12,28,30,33]. Verschiedene Studien belegen das Potenzial von Big Data im Gesundheitsbereich.…”

Section: Hintergrund Und Fragestellungunclassified

Big Data in der Gesundheitsförderung und Prävention

Spranger

Niederberger

2021

Präv Gesundheitsf

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Zusammenfassung Hintergrund Die Nutzung großer und vielfältiger Datenmengen (Big Data) kann zur Gewinnung gesundheitsbezogener Erkenntnisse führen. Die Relevanz untermauern aktuelle Erfordernisse, bspw. in Zusammenhang mit der Digitalisierung, der Gesundheitsversorgung in Ausnahmesituationen und der zunehmenden Bedeutung von Personalisierungsprozessen in der Gesundheitsforschung. Das Potenzial von Big Data zur Erforschung vulnerabler Gruppen ist strittig, jedoch vor dem Hintergrund relativ stabiler sozialbedingter gesundheitlicher Ungleichheit besonders relevant. Ziel der Arbeit In der Studie wird untersucht, wie Expert*innen im Bereich der Analyse von Gesundheitsdaten das Potenzial von Big Data in der Gesundheitsförderung und Prävention, insbesondere zur Erforschung vulnerabler Gruppen, einschätzen. Material und Methode In einer Delphi-Studie wurden Expert*innen in zwei Runden mit einem Onlinefragebogen befragt, um Konsens und Dissens über das Potenzial von Big Data zu identifizieren. Ergebnisse und Schlussfolgerung Aus Sicht der Expert*innen birgt Big Data ein Potenzial für die Gesundheitsförderung und Prävention, insbesondere im klinischen Setting und durch die Personalisierung gesundheitsbezogener Maßnahmen. Vor allem Menschen mit seltenen Erkrankungen und ältere Personen könnten durch Big-Data-Analysen profitieren, bspw. durch beschleunigte Diagnoseprozesse oder personalisierte digitale Gesundheitsanwendungen. Uneinig sind sich die Expert*innen über den Umfang, in welchem es Forschungseinrichtungen, Krankenversicherungen oder Unternehmen, erlaubt sein soll, derartige Daten zu nutzen oder zu teilen.

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“…Interactivity with end-users: This requirement represents the ability for an end-user to intuitively comprehend the data, perceive the underlying patterns, and interact with information displayed on control room screens [18].…”

Section: A Presentation and Visualisationmentioning

confidence: 99%

“…Scalability / readability: This requirement represents the scalability and readability of real-time data across all screen sizes and in all contexts [18].…”

Section: A Presentation and Visualisationmentioning

confidence: 99%

Understanding the End-Users and Technical Requirements for Real-Time Streaming Data Analytics and Visualisation

Dinmohammadi

Wilson

2021

2021 26th International Conference on Automation and Computing (ICAC)

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Today's digital world deals with tremendous amounts of data with high complexity and velocity. The data being generated continuously from a variety of sources at very high speeds is considered as streaming data. The number of technologies to ingest, explore, analyze, and visualize the streaming data is growing rapidly across many industries. However, the use of real-time technologies in the Architecture, Engineering & Construction (AEC) sector is still at its early stages of development and further research is needed to make the tools truly commercial. The AEC is a data-intensive, project-based industry that relies on real-time information to help projects stay on schedule and enable companies to cut costs. The technologies supporting real-time data capability in the AEC sector must satisfy several key functional and nonfunctional requirements. This paper aims to identify and prioritize both end-users and technical requirements for AEC businesses when adopting a real-time streaming data analytics and visualization technology in their production control rooms. To this aim, an expert questionnaire survey is conducted to investigate the requirements in four distinct areas, namely: (i) data collection and ingestion, (ii) stream processing, (iii) real-time analytics, and (iv) presentation and visualization. A five-level Likert scale is used in the questionnaire to allow respondents to indicate their perceptions on the importance of each of the identified requirements. The survey is distributed using Qualtrics online tool to over twenty organizations all over the world and the responses are analyzed using SPSS statistical software. The findings of the study reveal that 'interactivity' and 'user assistance' are the most important requirements from the end-users' perspective, whereas 'fast data processing', 'real-time reporting', 'scalable data processing', and 'dashboard connectivity' are the most important requirements from the technology developers' perspective. The findings of this research can help stakeholders and researchers get a better picture of the current challenges facing the AEC sector in terms of streaming data analytics and provide insight into the possible directions of future technological changes.

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Requirements of Data Visualisation Tools to Analyse Big Data: A Structured Literature Review

Cited by 8 publications

References 37 publications

Visualization, Serious Games and Decision Making

Visualization, Serious Games and Decision Making

Big Data in der Gesundheitsförderung und Prävention

Understanding the End-Users and Technical Requirements for Real-Time Streaming Data Analytics and Visualisation

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