LABORATORY INFORMATICSSPONSORED CONTENT
With laboratories creating ever-increasing amounts of data, it is critical to employ the correct strategy to ensure effective data management, writes Robert Roe
Managing biological data
The challenges of deriving insights from research data are often created at the point of recording and storing data from initial experiments. If an organisation is creating data silos which contain disparate file formats and data types, then going back to this data and using it for secondary research becomes challenging. Recording data in this way can lead to inefficiency, as files will often be duplicated and versioning issues can arise.
Modern laboratory instruments and
practices make it easier than ever to create huge amounts of data. The challenge is creating ‘good data’ and storing it, so that it can be used in the most efficient way possible. To overcome this, laboratories must adopt some kind of data management strategy based on selecting the right software tools and creating a centralised repository for their experiments and analysis. Many laboratories will have some kind
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of strategy for how to best record and store data effectively, but may not keep pace with the rise in data created by an organisation. Alternatively, they may not take into account how the data might be used in the future. At one time it was perfectly reasonable to save lots of experimental data on spreadsheets, but these practices have become untenable.
Maximising the effectiveness of research data In 2019, Jisc, a UK provider of shared digital infrastructure and advice on digital technology for education and research, published a report highlighting the need for researchers to properly collect and manage data. Report author Caroline Ingram,
product lead at Jisc, said: ‘Effective data management is carried out for the entire lifecycle of the data, from the point of creation through to dissemination, publication and archiving. Aspects of data management will usually continue long after the initial research project has ended.’ This can provide benefits to
collaboration, research efficiency and
“Effective data management is carried out for the entire lifecycle of the data, from the point of creation through to dissemination, publication and archiving”
research integrity through making data more accessible and easier to interpret. ‘Good research data management will enable you to organise your files and data for access and analysis without difficulty. This way you can track progress more easily, and mitigate against the risk of a team member leaving, taking valuable knowledge about the nature and extent of work completed with them. ‘Good data management can result
in improved research integrity, as well as act as validation for research results. Accurate and complete research data are an essential part of the evidence necessary for evaluating and validating research results, and for reconstructing
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