Data management in biology is a critical process that involves the acquisition, modeling, storage, integration, analysis, and interpretation of various types of data. This includes analog signals, digital images, sequences, spreadsheets, taxonomies, structured records, and unstructured text data. A data management plan (DMP) is the first step towards responsible data management. It outlines the type of data to be collected, how and where it will be stored, and who will have access to it.
Finalizing data sets for analysis is a crucial part of any academic study. Data must be kept for short- and long-term use while also being analyzed quickly to generate new knowledge. Containerization, ontologies, and the ability to assign metadata dynamically are making this process more feasible. For example, the Dutch Research Agency (NWO) requires a DMP for its main funding plan.
In Europe, ELIXIR provides training and Dutch communities of data administrators offer skill development, advice and support. To ensure that data sets are recoverable, accessible, and understandable in the long term, storage, exchange and archiving must be carefully organized and documented. Quality control steps should always be taken to ensure that what is reported to be in a data set is actually there. This can be done by consulting excellent reference databases.
Data managers can support scientists by training them in data management. For example, if a new technique such as microscopy is used to acquire a data set, a data administrator can provide advice on how to archive the resulting data and create the metadata. This makes it accessible during and after the project. Well-maintained and processed data sets can ultimately help researchers better understand biological processes and mechanisms. Data management in biology is an essential part of any research project that should not be overlooked.