CLMM:Towards a Collaborative Chinese University Laboratory Model

• Published in: Frontiers in Artificial Intelligence and Applications
• Main Author: Hu H.; Dolah N.A.; Ahmad N.D.
• Format: Conference paper
• Language: English
• Published: IOS Press BV 2024
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85216921351&doi=10.3233%2fFAIA241212&partnerID=40&md5=689085255037dd026327f6f02dbd25ad

With universities continually producing data in their laboratories, effective data management has become increasingly crucial. To meet this demand, the application of laboratory information management systems (LIMS) is becoming increasingly widespread. LIMS is a complex computing system used to manage laboratory data. There are currently a variety of LIMS to choose from, but most LIMS use proprietary codes, so the development cost is very high. At the same time, existing LIMS models usually only focus on functional requirements and ignore the specific means of functional implementation, which leads to difficulties for users in management. In addition, since LIMS are very complex, they are often designed to meet the needs of specific laboratories, which makes their versatility and reusability very poor. Therefore, this paper presents the Collaborative Laboratory Management Model(CLMM), which introduces advanced management ideas based on the LIMS model, aiming to make the model focus on both function and technology. CLMM integrates workflows, and users can create and manage workflows themselves. This not only improves the flexibility of the model, but also increases reusability, which can meet the needs of different types of laboratories. With the development of the model, we hope to improve the management efficiency of laboratories by managing the data of university laboratory information, equipment, instruments, etc., and contribute to the complex management work of universities. © 2024 The Authors.