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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 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 ...
There are limitations in the ability of Designer to parse HTML and display it in a form; Designer cannot handle a number of fundamental tags, including ordered list, unordered list and tables. [3] The program has had a reported consistent issue with users being able to set the tabbing order correctly.
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]
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] This data can come from any ...
The data capture products allow users to create and deploy XML-based form templates as PDFs (Forms Standard and Forms Pro), manage live data (Data Services), and customizes editing functionalities on a per-document basis (Reader Extensions). It also has multiple features to ensure document security.
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).
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