Development of scholarly data visualization framework for publication collaboration mapping using network-based technique

• Main Author: Nur Nazifa, Md Hasani
• Format: Thesis
• Language: English; English; English
• Published: 2025
• Subjects: LB2300 Higher Education
• Online Access: https://etd.uum.edu.my/11727/1/Depositpermission-not%20allow_s827691.pdf; https://etd.uum.edu.my/11727/2/s827691_01.pdf; https://etd.uum.edu.my/11727/3/s827691_02.pdf

Publication collaboration is pivotal for enhancing the visibility and impact of research. Universities worldwide seek to improve rankings position such as the QS World University Ranking, where publication quality and collaboration play a crucial role. Despite numerous studies on visualizing collaborations, integrating datasets from Scopus and internal university database to map collaboration and ranking relationships remains underexplored. This study attempts to address challenges in effective data visualization to enhance understanding and strategic planning for publication collaborations. Thus, this study aims to develop a scholarly data visualization framework integrating Scopus and internal university database to map publication collaborations. This framework seeks to enhance decision-making processes by enabling interactive exploration of collaboration networks and consequently recognize their impact on university rankings, specifically for Universiti Utara Malaysia (UUM) as a case study. The data integration from both Scopus and internal university database has been used in the development of a network-based visualization framework for publication collaboration mapping. Interactive tools, including statistical graphs and network maps were also established. Expert reviews and usability tests validated the framework's effectiveness, highlighting improved data coherence as well as the ability to identify collaboration patterns and trends. The developed framework enhances the visualization of publication collaborations significantly, enabling a clear identification of collaboration patterns at internal, national, and international levels. Notably, internal collaborations account for the largest percentage of the university's publication affiliations, comprising 60.29% of the total with 1,201 internal collaborations recorded. The framework also highlights areas requiring strategic attention, such as increasing collaboration with higher-ranked universities. For instance, collaborations with higherranked institutions constitute only 21% of the university’s total collaborations. Expert feedback further validated the framework, emphasizing its ability to provide valuable insights into collaboration trends and their implications for improving the university's rankings. Therefore, this study contributes a novel visualization framework that supports academic institutions in optimizing publication collaborations. The study demonstrates its practical implications in decision-making for improving publication impact and university rankings. Beyond theoretical contribution, the framework offers societal benefits by fostering strategic collaboration, enhancing publication quality, and supporting data-driven policies in higher education.