Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/179972
Title: The digital lab manager: automating research support
Authors: Rihm, Simon D.
Tan, Yong Ren
Ang, Wilson
Hofmeister, Markus
Deng, Xinhong
Laksana, Michael Teguh
Quek, Hou Yee
Bai, Jiaru
Pascazio, Laura
Siong, Sim Chun
Akroyd, Jethro
Mosbach, Sebastian
Kraft, Markus
Keywords: Other
Issue Date: 2024
Source: Rihm, S. D., Tan, Y. R., Ang, W., Hofmeister, M., Deng, X., Laksana, M. T., Quek, H. Y., Bai, J., Pascazio, L., Siong, S. C., Akroyd, J., Mosbach, S. & Kraft, M. (2024). The digital lab manager: automating research support. SLAS Technology, 29(3), 100135-. https://dx.doi.org/10.1016/j.slast.2024.100135
Project: CREATE 
Journal: SLAS Technology
Abstract: Laboratory management automation is essential for achieving interoperability in the domain of experimental research and accelerating scientific discovery. The integration of resources and the sharing of knowledge across organisations enable scientific discoveries to be accelerated by increasing the productivity of laboratories, optimising funding efficiency, and addressing emerging global challenges. This paper presents a novel framework for digitalising and automating the administration of research laboratories through The World Avatar, an all-encompassing dynamic knowledge graph. This Digital Laboratory Framework serves as a flexible tool, enabling users to efficiently leverage data from diverse systems and formats without being confined to a specific software or protocol. Establishing dedicated ontologies and agents and combining them with technologies such as QR codes, RFID tags, and mobile apps, enabled us to develop modular applications that tackle some key challenges related to lab management. Here, we showcase an automated tracking and intervention system for explosive chemicals as well as an easy-to-use mobile application for asset management and information retrieval. Implementing these, we have achieved semantic linking of BIM and BMS data with laboratory inventory and chemical knowledge. Our approach can capture the crucial data points and reduce inventory processing time. All data provenance is recorded following the FAIR principles, ensuring its accessibility and interoperability.
URI: https://hdl.handle.net/10356/179972
ISSN: 2472-6303
DOI: 10.1016/j.slast.2024.100135
Schools: School of Chemical and Biomedical Engineering 
Organisations: Cambridge Centre for Advanced Research and Education in Singapore
Rights: © 2024 The Author(s). Published by Elsevier Inc. on behalf of Society for Laboratory Automation and Screening. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCBE Journal Articles

Files in This Item:
File Description SizeFormat 
PIIS2472630324000177.pdf2.69 MBAdobe PDFView/Open

SCOPUSTM   
Citations 50

3
Updated on Mar 8, 2025

Page view(s)

73
Updated on Mar 15, 2025

Download(s)

10
Updated on Mar 15, 2025

Google ScholarTM

Check

Altmetric


Plumx

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.