数字化实验室管理员:研究支持自动化

IF 2.5 4区 医学 Q3 BIOCHEMICAL RESEARCH METHODS SLAS Technology Pub Date : 2024-05-03 DOI:10.1016/j.slast.2024.100135
Simon D. Rihm , Yong Ren Tan , Wilson Ang , Markus Hofmeister , Xinhong Deng , Michael Teguh Laksana , Hou Yee Quek , Jiaru Bai , Laura Pascazio , Sim Chun Siong , Jethro Akroyd , Sebastian Mosbach , Markus Kraft
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引用次数: 0

摘要

实验室管理自动化对于实现实验研究领域的互操作性和加速科学发现至关重要。跨组织的资源整合和知识共享可以提高实验室的生产力,优化资金使用效率,应对新出现的全球性挑战,从而加速科学发现。本文提出了一个新颖的框架,通过 "世界阿凡达"(一个包罗万象的动态知识图谱)实现研究实验室管理的数字化和自动化。这个数字实验室框架是一个灵活的工具,使用户能够有效地利用来自不同系统和格式的数据,而不必局限于特定的软件或协议。建立专用的本体和代理,并将它们与 QR 码、RFID 标签和移动应用程序等技术相结合,使我们能够开发模块化应用程序,以应对与实验室管理相关的一些关键挑战。在这里,我们展示了一个爆炸性化学品自动跟踪和干预系统,以及一个用于资产管理和信息检索的易于使用的移动应用程序。通过实施这些系统,我们实现了 BIM 和 BMS 数据与实验室库存和化学知识的语义链接。我们的方法可以捕捉关键数据点,减少库存处理时间。所有数据出处都按照 FAIR 原则进行记录,确保其可访问性和互操作性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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The digital lab manager: Automating research support

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.

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来源期刊
SLAS Technology
SLAS Technology Computer Science-Computer Science Applications
CiteScore
6.30
自引率
7.40%
发文量
47
审稿时长
106 days
期刊介绍: SLAS Technology emphasizes scientific and technical advances that enable and improve life sciences research and development; drug-delivery; diagnostics; biomedical and molecular imaging; and personalized and precision medicine. This includes high-throughput and other laboratory automation technologies; micro/nanotechnologies; analytical, separation and quantitative techniques; synthetic chemistry and biology; informatics (data analysis, statistics, bio, genomic and chemoinformatics); and more.
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