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The digital lab manager: Automating research support.

Simon D Rihm1, Yong Ren Tan2, Wilson Ang2

  • 1CARES, Cambridge Centre for Advanced Research and Education in Singapore, 1 CREATE Way, CREATE Tower, #05-05, 138602, Singapore; Department of Chemical Engineering and Biotechnology, University of Cambridge, Philipppa Fawcett Drive, Cambridge, CB3 0AS, United Kingdom; Department of Chemical & Biomolecular Engineering, National University of Singapore, 4 Engineering Drive 4, 117585, Singapore.

SLAS Technology
|May 4, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a novel Digital Laboratory Framework using The World Avatar knowledge graph to automate lab management. This enhances research productivity and data interoperability, accelerating scientific discovery.

Keywords:
Asset trackingDynamic knowledge graphsLIMSLab managementLaboratory automationRFID

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Area of Science:

  • Scientific research
  • Laboratory management
  • Digital transformation

Background:

  • Laboratory management automation is crucial for interoperability and accelerating scientific discovery.
  • Integrating resources and knowledge sharing across organizations boosts productivity and funding efficiency.
  • Addressing global challenges requires optimized laboratory operations.

Purpose of the Study:

  • To present a novel framework for digitalizing and automating research laboratory administration.
  • To enable efficient data leverage from diverse systems and formats.
  • To develop modular applications for key lab management challenges.

Main Methods:

  • Utilizing The World Avatar, a dynamic knowledge graph, for a novel Digital Laboratory Framework.
  • Establishing dedicated ontologies and agents combined with QR codes, RFID tags, and mobile apps.
  • Implementing modular applications for automated tracking of explosive chemicals and asset management.

Main Results:

  • Achieved semantic linking of Building Information Modeling (BIM) and Building Management System (BMS) data with laboratory inventory and chemical knowledge.
  • Demonstrated reduced inventory processing time and capture of crucial data points.
  • Ensured data provenance recording following FAIR principles for accessibility and interoperability.

Conclusions:

  • The Digital Laboratory Framework effectively automates and digitalizes lab administration.
  • The approach enhances data interoperability and accelerates scientific discovery.
  • FAIR data principles are upheld, ensuring data accessibility and reusability.