Understanding big picture and its challenges

Experts and decision makers perspectives

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

8 Citations (Scopus)

Abstract

The big picture of an organization plays an important role in providing insight into the decision making process. Thus, the objectives of this paper are to investigate how experts and decision makers obtain the features of the big picture, and then identify related challenges (problems and issues). Data analysis and interpretation show that experts and decision makers gain the big picture through a process of collaboration. Basically there are four main sequences in the collaboration process of constructing the big picture. These are: (i) understanding the big picture requirements, (ii) extracting content from the tools, (iii) collaborating on pieces of information and (iv) using the collaborative information for decision making. In addition, the challenges of attaining the big picture were identified and then clustered into the 3 main components from the perspective of knowledge visualization (KV) on user perception, namely cognition, perception and communication. Data was collected using semi structured interviews following qualitative methods. The sketching technique was used in the one-to-one interviews to represent mental models which are important for later use in the design stage.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages311-322
Number of pages12
Volume8237 LNCS
DOIs
Publication statusPublished - 2013
Event3rd International Visual Informatics Conference, IVIC 2013 - Selangor
Duration: 13 Nov 201315 Nov 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8237 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other3rd International Visual Informatics Conference, IVIC 2013
CitySelangor
Period13/11/1315/11/13

Fingerprint

Decision making
Decision Making
Qualitative Methods
Mental Models
Sketching
Visualization
Cognition
Communication
Data analysis
Requirements
Collaboration
Perception
Interpretation
Knowledge
Design

Keywords

  • big picture
  • cognition and perception
  • knowledge visualization

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Ya'acob, S., Mohamad Ali, N., & Mat Nayan, N. (2013). Understanding big picture and its challenges: Experts and decision makers perspectives. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8237 LNCS, pp. 311-322). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8237 LNCS). https://doi.org/10.1007/978-3-319-02958-0_29

Understanding big picture and its challenges : Experts and decision makers perspectives. / 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. 8237 LNCS 2013. p. 311-322 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8237 LNCS).

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

Ya'acob, S, Mohamad Ali, N & Mat Nayan, N 2013, Understanding big picture and its challenges: Experts and decision makers perspectives. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 8237 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8237 LNCS, pp. 311-322, 3rd International Visual Informatics Conference, IVIC 2013, Selangor, 13/11/13. https://doi.org/10.1007/978-3-319-02958-0_29
Ya'acob S, Mohamad Ali N, Mat Nayan N. Understanding big picture and its challenges: Experts and decision makers perspectives. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8237 LNCS. 2013. p. 311-322. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-02958-0_29
Ya'acob, Suraya ; Mohamad Ali, Nazlena ; Mat Nayan, Norshita. / Understanding big picture and its challenges : Experts and decision makers perspectives. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8237 LNCS 2013. pp. 311-322 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{9631b26970e1417181f2b5a2cfc4589e,
title = "Understanding big picture and its challenges: Experts and decision makers perspectives",
abstract = "The big picture of an organization plays an important role in providing insight into the decision making process. Thus, the objectives of this paper are to investigate how experts and decision makers obtain the features of the big picture, and then identify related challenges (problems and issues). Data analysis and interpretation show that experts and decision makers gain the big picture through a process of collaboration. Basically there are four main sequences in the collaboration process of constructing the big picture. These are: (i) understanding the big picture requirements, (ii) extracting content from the tools, (iii) collaborating on pieces of information and (iv) using the collaborative information for decision making. In addition, the challenges of attaining the big picture were identified and then clustered into the 3 main components from the perspective of knowledge visualization (KV) on user perception, namely cognition, perception and communication. Data was collected using semi structured interviews following qualitative methods. The sketching technique was used in the one-to-one interviews to represent mental models which are important for later use in the design stage.",
keywords = "big picture, cognition and perception, knowledge visualization",
author = "Suraya Ya'acob and {Mohamad Ali}, Nazlena and {Mat Nayan}, Norshita",
year = "2013",
doi = "10.1007/978-3-319-02958-0_29",
language = "English",
isbn = "9783319029573",
volume = "8237 LNCS",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "311--322",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

}

TY - GEN

T1 - Understanding big picture and its challenges

T2 - Experts and decision makers perspectives

AU - Ya'acob, Suraya

AU - Mohamad Ali, Nazlena

AU - Mat Nayan, Norshita

PY - 2013

Y1 - 2013

N2 - The big picture of an organization plays an important role in providing insight into the decision making process. Thus, the objectives of this paper are to investigate how experts and decision makers obtain the features of the big picture, and then identify related challenges (problems and issues). Data analysis and interpretation show that experts and decision makers gain the big picture through a process of collaboration. Basically there are four main sequences in the collaboration process of constructing the big picture. These are: (i) understanding the big picture requirements, (ii) extracting content from the tools, (iii) collaborating on pieces of information and (iv) using the collaborative information for decision making. In addition, the challenges of attaining the big picture were identified and then clustered into the 3 main components from the perspective of knowledge visualization (KV) on user perception, namely cognition, perception and communication. Data was collected using semi structured interviews following qualitative methods. The sketching technique was used in the one-to-one interviews to represent mental models which are important for later use in the design stage.

AB - The big picture of an organization plays an important role in providing insight into the decision making process. Thus, the objectives of this paper are to investigate how experts and decision makers obtain the features of the big picture, and then identify related challenges (problems and issues). Data analysis and interpretation show that experts and decision makers gain the big picture through a process of collaboration. Basically there are four main sequences in the collaboration process of constructing the big picture. These are: (i) understanding the big picture requirements, (ii) extracting content from the tools, (iii) collaborating on pieces of information and (iv) using the collaborative information for decision making. In addition, the challenges of attaining the big picture were identified and then clustered into the 3 main components from the perspective of knowledge visualization (KV) on user perception, namely cognition, perception and communication. Data was collected using semi structured interviews following qualitative methods. The sketching technique was used in the one-to-one interviews to represent mental models which are important for later use in the design stage.

KW - big picture

KW - cognition and perception

KW - knowledge visualization

UR - http://www.scopus.com/inward/record.url?scp=84887128129&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84887128129&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-02958-0_29

DO - 10.1007/978-3-319-02958-0_29

M3 - Conference contribution

SN - 9783319029573

VL - 8237 LNCS

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 311

EP - 322

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ER -