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The user, rather than the database itself, typically initiates data curation and maintains metadata. [8] 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 ...
As an increasing portion of the world’s information output shifts from analog to digital form, preservation metadata is an essential component of most digital preservation strategies, including digital curation, data management, digital collections management and the preservation of digital information over the long-term.
The Data Asset Framework or DAF is a data audit methodology developed by HATII at the University of Glasgow in conjunction with the Digital Curation Centre. Originally the Data Audit Framework, the Data Asset Framework is an interview protocol utilised by educational institutions to better understand their growing research data collections.
The term "digital curation" was first used in the e-science and biological science fields as a means of differentiating the additional suite of activities ordinarily employed by library and museum curators to add value to their collections and enable its reuse [12] [13] [14] from the smaller subtask of simply preserving the data, a significantly more concise archival task. [12]
Data can be described as the elements or units in which knowledge and information is created, [2] and metadata are the summarizing subsets of the elements of data; or the data about the data. [3] The main goal of data preservation is to protect data from being lost or destroyed and to contribute to the reuse and progression of the data.
Code generation is the process of generating executable code (e.g. SQL, Python, R, or other executable instructions) that will transform the data based on the desired and defined data mapping rules. [4] Typically, the data transformation technologies generate this code [5] based on the definitions or metadata defined by the developers.
Algorithmic curation, curation using computer algorithms; Content curation, the collection and sorting of information; Data curation, management activities required to maintain research data; Digital curation, the preservation and maintenance of digital assets; Evidence management, the indexing and cataloguing of evidence related to an event
Data wrangling, sometimes referred to as data munging, is the process of transforming and mapping data from one "raw" data form into another format with the intent of making it more appropriate and valuable for a variety of downstream purposes such as analytics. The goal of data wrangling is to assure quality and useful data.