The smart laboratory

Tis chapter discusses what we mean by a ‘smart laboratory’ and its role in an integrated business process. We also look at the evolution of computerised laboratory data and information management; the relationships between laboratory instruments and automation (data acquisition); laboratory informatics systems (information management); and higher-level enterprise systems and how they align with knowledge management initiatives. Te progressive ‘digitisation’ of the

laboratory offers an unprecedented opportunity not only to increase laboratory efficiency and productivity, but also to move towards ‘predictive science’, where accumulated explicit knowledge and computer algorithms can be exploited to bring about greater understanding of materials, products, and processes.

Tere is no specific definition of a ‘smart laboratory’. Te term is oſten used in different contexts to imply either that a laboratory is designed in a way to optimise its physical layout, that it incorporates the latest technology to control the laboratory environment, or that the laboratory is using the latest technology to manage its scientific activities. For the purposes of this publication, it is the latter definition that applies. Te incorporation of information

technology into all aspects of laboratory operations has resulted in fundamental changes


in laboratory work. Prior to about 1900, most scientific innovation and development was either embedded in an industrial process, or was an outcome of academic or privately initiated research. Te introduction of industrial R&D laboratories heralded a new era of innovation and development dependent on the skills, knowledge and creativity of individual scientists. Te evolution has continued into the ‘information age’ with a growing dependence on information technology, both as an integral part of the scientific process, and as a means of managing scientific information and knowledge. Laboratory information has traditionally

been managed on paper, typically in the form of the paper laboratory notebook, worksheets and reports. Tis provided a simple and portable means of recording ideas, hypotheses, descriptions of laboratory apparatus and laboratory procedures, results, observations, and conclusions. As such, the lab notebook served as both a scientific and business record. However, the introduction of digital technologies to the laboratory has brought about significant change. From the basic application of computational

power to undertake scientific calculations at unprecedented speeds, to the current situation of extensive and sophisticated laboratory automation, black box measurement devices, and multiuser information management systems, technology is causing glassware and paper notebooks to become increasingly rare

“A smart laboratory deploys modern tools and technologies to improve the efficiency of the scientific method”

in the laboratory landscape. Te evolution of sophisticated lab instrumentation, data and information management systems, and electronic record keeping has brought about a revolution in the process of acquiring and managing laboratory data and information. However, the underlying principles of the scientific method are unchanged, supporting the formulation, testing, and modification of hypotheses by means of systematic observation, measurement, and experimentation. In our context, a smart laboratory seeks to deploy modern tools and technologies to improve the efficiency of the scientific method by providing seamless integration of systems, searchable repositories of data of proven integrity, authenticity and reliability, and the elimination of mindless and unproductive paper-based processes. At the heart of the smart laboratory is a

simple model (see Figure 1) that defines the conceptual, multi-layered relationship between data, information, and knowledge. Te triangle represents the different

layers of abstraction that exist in laboratory workflows. Tese are almost always handled by different systems. Te ‘experiment’ level is the

Dmitry Kalinovsky/

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