Don’t Let Data and Knowledge Leave the Lab When Employees Do

There is no doubt that well-managed commercial software platforms can be costly from a licensing standpoint. Therefore, many labs elect to build their own data management and provenance systems. However, the teams tasked with developing these tools almost never include the head of the laboratory, who is the single constant member of the lab, especially in academic settings. Instead, the job of building infrastructure is tasked primarily to graduate students, postdoctoral fellows, or staff bioinformaticians. By the natur101714_Steve_Cole-Getty_WomanLeavingOffice.large.jpge of their roles, they are transient through the lab, with their stays not lasting more than three to five years until they graduate, find tenure-track positions, or flee the lab for more lucrative positions at biotech and pharmaceutical companies.

When the person who built an ad hoc system leaves the lab, no one else may know how to maintain the system properly. This means simple things from instrumentation settings for an experiment, or more sensitive information such as data or instructions kept in a notebook, can be lost (not to mention what would happen if something breaks). Thus, with the loss of expertise comes a significant inefficiency in laboratory operations.

With a comprehensive commercial data management solution like Lab7’s Enterprise Science Platform (ESP), data and methods are never lost, not even if the lab elects to forgo annual license renewals. In addition, ESP software is deliberately designed to be user-friendly and adaptable to changing laboratory environments, from new lab members to lab protocols and analyses. ESP maintains a registry of all samples, data, and files that pass through the system, and it can retrieve any critical data a laboratory might require, even years after the data was originally generated.

Learn more about gaining efficiency in your lab by downloading our Five Strategies to Improve the Efficiency of Your Lab whitepaper. 

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This entry was posted in Big Data, Bioinformatics, Education, White Paper

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