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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 ...
The DCC Curation Lifecycle Model is especially relevant to three key participants in the digital curation process: data creators, data archivists, and data reusers. The model highlights the importance of data creation, such as metadata, in successful, sustainable curation practices. This is relevant to data creators.
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 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.
However, data has staged a comeback with the popularisation of the term big data, which refers to the collection and analyses of massive sets of data. While big data is a recent phenomenon, the requirement for data to aid decision-making traces back to the early 1970s with the emergence of decision support systems (DSS).
Digital thread, also known as digital chain, [1] is defined as “the use of digital tools and representations for design, evaluation, and life cycle management.”. [2] It is a data-driven architecture that links data gathered during a Product lifecycle from all involved and distributed manufacturing systems. [3]
Data can be put in a location/area of a storage mechanism. The fundamental feature of a storage location is that its content is both readable and updatable. Before a storage location can be read or updated it needs to be created; that is allocated and initialized with content.
In software engineering, a software development process or software development life cycle (SDLC) is a process of planning and managing software development. It typically involves dividing software development work into smaller, parallel, or sequential steps or sub-processes to improve design and/or product management .