Systemic visual structures: Design solution for complexities of big data interfaces

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

The prime challenge for big data in handling variety, velocity and volume (3V) information is a complexity. In recent years, big data has been studied extensively from technology perspectives. However, far too little attention has been paid to the limited human cognitive to perceive and process the complexities, especially when the users as in the management team of organization need to digest the information collaboratively. The objective of this paper is to show how visual representation design can play an important role to facilitate this challenge. We term the challenge as collaborative complex cognitive activities (collaborative CCA) and is valuable for decision making, analytical reasoning, sense making, problem solving, learning and planning in the organization. In this research, we propose the systemic view as a fundamental to facilitate the collaborative CCA for big data. We attempt to extend the technical function of an overview to suffice the demonstration of systemic view through visual structure. By having this, we are able to view each information elements as part of the whole and giving them preparation to handle any emergence of ideas, information or tasks during the collaborative CCA. Finally, this paper also shows the result of the validation. We test the systemic view of visual structure demonstration through the experimental class with applying case studies in the real environment of the organization. The deductive qualitative analysis shows the benefits of the systemic view to clarify the main drivers and see the interconnection between various elements. Further than that, we find the potential of systemic visual structure to spark an innovation while performing collaborative CCA. Through this research, we hope to broaden the scope of visual representation to ensure the users are able to perceives, process and find values from the complexities of big data.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages25-37
Number of pages13
Volume9429
ISBN (Print)9783319259383, 9783319259383
DOIs
Publication statusPublished - 2015
Event4th International Visual Informatics Conference, IVIC 2015 - Bangi, Malaysia
Duration: 17 Nov 201519 Nov 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9429
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other4th International Visual Informatics Conference, IVIC 2015
CountryMalaysia
CityBangi
Period17/11/1519/11/15

Fingerprint

Demonstrations
Electric sparks
Qualitative Analysis
Interconnection
Innovation
Decision making
Driver
Preparation
Planning
Reasoning
Decision Making
Vision
Design
Big data
Term
Human
Class
Learning

Keywords

  • Big data interfaces
  • Complexities
  • Systemic
  • Visual representation

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Ya’Acob, S., Mohamad Ali, N., & Mat Nayan, N. (2015). Systemic visual structures: Design solution for complexities of big data interfaces. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9429, pp. 25-37). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9429). Springer Verlag. https://doi.org/10.1007/978-3-319-25939-0_3

Systemic visual structures : Design solution for complexities of big data interfaces. / Ya’Acob, Suraya; Mohamad Ali, Nazlena; Mat Nayan, Norshita.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 9429 Springer Verlag, 2015. p. 25-37 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9429).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Ya’Acob, S, Mohamad Ali, N & Mat Nayan, N 2015, Systemic visual structures: Design solution for complexities of big data interfaces. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 9429, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9429, Springer Verlag, pp. 25-37, 4th International Visual Informatics Conference, IVIC 2015, Bangi, Malaysia, 17/11/15. https://doi.org/10.1007/978-3-319-25939-0_3
Ya’Acob S, Mohamad Ali N, Mat Nayan N. Systemic visual structures: Design solution for complexities of big data interfaces. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 9429. Springer Verlag. 2015. p. 25-37. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-25939-0_3
Ya’Acob, Suraya ; Mohamad Ali, Nazlena ; Mat Nayan, Norshita. / Systemic visual structures : Design solution for complexities of big data interfaces. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 9429 Springer Verlag, 2015. pp. 25-37 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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