TY - JOUR
T1 - Visual analytics evaluation process
T2 - Practice guidelines for complex domain
AU - Ya'acob, Suraya
AU - Ali, Nazlena Mohamad
AU - Nayan, Norshita Mat
AU - Liang, Hai Ning
AU - Ahmad, Ibrahim
AU - Ibrahim, Roslina
AU - Bakar, Nur Azaliah Abu
N1 - Publisher Copyright:
© Faculty of Computer Science and Information Technology.
PY - 2019
Y1 - 2019
N2 - Visual analytics fundamentally influences the analytical process. Without proper guidance, the use of visual analytics in complex domain can become an obstacle that hides the usefulness of analytical data. Since evaluation is the only way to identify the effectiveness of visual analytics to represent analytical outcomes, misconception of the evaluation process will bury the relevancy of visualization to support valuable decision. Recently, the nature domain of data has changed and we are now dealing with data that is massive, ambiguous, and dynamic, is often processed in real time. Hence, the data is more complex and cognitive activities that visual analytics facilitates are also getting more complex. Thus, this research revisits the way to evaluate visual analytics in complex cognitive conditions that are natural, uncertain and context dependent. Governed by the Design Science Research Methodology (DSRM), there are three phases involve during the evaluation process; i). demonstration, ii). evaluation and iii). communication. The design process is embedded with the human-activity centered design approach to gain better understanding on the visual analytics users and the complex cognitive activities involved. Thus, the research proposes Focus Group Observation method in conducting the evaluation in authentic setting. By offering a set of evaluation recommendations, this research aims to enhance visual analytics among users. It also recommends the evaluation criteria, sampling strategy and participation, focus group tasks and settings and data management and analysis that are suitable for complex domain in visual analytics.
AB - Visual analytics fundamentally influences the analytical process. Without proper guidance, the use of visual analytics in complex domain can become an obstacle that hides the usefulness of analytical data. Since evaluation is the only way to identify the effectiveness of visual analytics to represent analytical outcomes, misconception of the evaluation process will bury the relevancy of visualization to support valuable decision. Recently, the nature domain of data has changed and we are now dealing with data that is massive, ambiguous, and dynamic, is often processed in real time. Hence, the data is more complex and cognitive activities that visual analytics facilitates are also getting more complex. Thus, this research revisits the way to evaluate visual analytics in complex cognitive conditions that are natural, uncertain and context dependent. Governed by the Design Science Research Methodology (DSRM), there are three phases involve during the evaluation process; i). demonstration, ii). evaluation and iii). communication. The design process is embedded with the human-activity centered design approach to gain better understanding on the visual analytics users and the complex cognitive activities involved. Thus, the research proposes Focus Group Observation method in conducting the evaluation in authentic setting. By offering a set of evaluation recommendations, this research aims to enhance visual analytics among users. It also recommends the evaluation criteria, sampling strategy and participation, focus group tasks and settings and data management and analysis that are suitable for complex domain in visual analytics.
KW - Complex cognitive activities
KW - Complex domain
KW - Evaluation process
KW - Human-activity centered design
KW - Visual analytics
UR - http://www.scopus.com/inward/record.url?scp=85086180548&partnerID=8YFLogxK
U2 - 10.22452/mjcs.sp2019no1.9
DO - 10.22452/mjcs.sp2019no1.9
M3 - Article
AN - SCOPUS:85086180548
SN - 0127-9084
VL - 2019
SP - 118
EP - 134
JO - Malaysian Journal of Computer Science
JF - Malaysian Journal of Computer Science
IS - SpecialIssue1
ER -