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Event Summary – Unlocking Research Potential: Effective Data Management for Transdisciplinary Success

The “Unlocking Research Potential: Effective Data Management for Transdisciplinary Success” sharing session successfully took place on Zoom on 12 March 2024 as part of the Research Data Academy series. The Ph.D. student sharing session was co-organized by the i-REACH project, Advanced Technologies Institute of HKU, Sau Po Centre of Ageing of HKU, and the HKU Libraries, aiming to provide HKU research students and early career researchers with opportunities in learning and exchanging knowledge on data management with transdisciplinary research team members.

Two guest speakers were HKU Ph.D. candidates working on the i-REACH project, a research effort to develop intelligent technology enabling “intelligent Robotic Elderly Assistant to Create Hope”. Using the project as an example, the speakers discussed multifaceted aspects of transdisciplinary research with focus on three key elements: effective communication, hardware and software data management, and hands-on data management with R and R Studio. 

 Figure 1 – Screenshot of Zoom sharing session

Ms. Clio Cheng, Ph.D. Candidate from the Department of Social Work & Social Administration, began the session by introducing the i-REACH project, highlighting the language barriers among project members, and sharing insightful tips for effective communication on transdisciplinary research. 

Mr. Kehan Zou, Ph.D. Candidate from the Department of Industrial and Manufacturing System Engineering, then delved into the challenges in data management for the i-REACH project which involves enormous amount of diverse and complex research data. He emphasized that as a good practice, data shall be stored in organised tree structure for easy retrieval. To avoid data contamination and data loss, researcher access to the original and processed data was restricted at different levels, and research data were backed up with triple copies. These practices were recommended to ensure the privacy and safety of the project data, especially for those with personal identifiers of study participants. 

Figure 2 – Three best data storage practices shared by Mr. Kehan Zou 

In the third part of the session, Clio provided a quick demonstration on using R and R Studio for data analysis and documentation. Quarto, a multi-language, next generation version of R Markdown, was recommended because of its functions in note-keeping, rendering reports in multiple formats and generating interactive visualisation. 

In the Q & A section, speakers discussed the judgemental issues in data cleaning and pointed out that data cleaning and preprocessing was one of the major areas the team had difficulties in. 

The sharing session recorded a total of 120 registrants, with 63 (53%) of them being academic staff, research staff, and research postgraduate students. 70 attended the session on the event day. The session undoubtedly provided participants with valuable knowledge on data management with the example of the transdisciplinary i-Reach project. We are pleased to have this opportunity in collaborating with the i-REACH project team on advocating research data management best practices among the HKU community and we would like to extend our gratitude to Clio and Kehan again for their insightful sharing.

More training sessions from Research Data Academy series are coming in April and May, focusing on skills in data collection, preprocessing, analysis, visualization, and sharing. For more details and registration, please visit the Research Data Academy webpage. Don’t miss the chance! 

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