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Data curation is the organization and integration of data collected from various sources. It involves annotation, publication and presentation of the data such that the value of the data is maintained over time, and the data remains available for reuse and preservation. Data curation includes "all the processes needed for principled and controlled data creation, maintenance, and management, together with the capacity to add value to data". In science, data curation may indicate the process of extraction of important information from scientific texts, such as research articles by experts, to be converted into an electronic format, such as an entry of a biological database. In the modern era of big data, the curation of data has become more prominent, particularly for software processing high volume and complex data systems. The term is also used in historical occasions and the humanities, where increasing cultural and scholarly data from digital humanities projects requires the expertise and analytical practices of data curation. In broad terms, curation means a range of activities and processes done to create, manage, maintain, and validate a component. Specifically, data curation is the attempt to determine what information is worth saving and for how long. The user, rather than the database itself, typically initiates data curation and maintains metadata. According to the University of Illinois' Graduate School of Library and Information Science, "Data curation is the active and on-going management of data through its lifecycle of interest and usefulness to scholarship, science, and education; curation activities enable data discovery and retrieval, maintain quality, add value, and provide for re-use over time." The data curation workflow is distinct from data quality management, data protection, lifecycle management, and data movement. Census data has been available in tabulated punch card form since the early 20th century and has been electronic since the 1960s.

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