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Data integration refers to the process of combining, sharing, or synchronizing data from multiple sources to provide users with a unified view. [1] There are a wide range of possible applications for data integration, from commercial (such as when a business merges multiple databases) to scientific (combining research data from different bioinformatics repositories).
Data sharing may also be restricted to protect institutions and scientists from use of data for political purposes. Data and methods may be requested from an author years after publication. In order to encourage data sharing [3] and prevent the loss or corruption of data, a number of funding agencies and journals established policies on data ...
In some domains, a few dozen different source and target schema (proprietary data formats) may exist. An "exchange" or "interchange format" is often developed for a single domain, and then necessary routines (mappings) are written to (indirectly) transform/translate each and every source schema to each and every target schema by using the interchange format as an intermediate step.
Knowledge sharing (fostering a culture that encourages the sharing of information, based on the concept that knowledge is not irrevocable and should be shared and updated to remain relevant) Make knowledge-sharing a key role in employees' job description; Inter-project knowledge transfer; Intra-organisational knowledge sharing
Traditional information sharing referred to one-to-one exchanges of data between a sender and receiver. Online information sharing gives useful data to businesses for future strategies based on online sharing. [4] These information exchanges are implemented via dozens of open and proprietary protocols, message, and file
March 2017: The Association for Information and Image Management (AIIM) proposed replacing "enterprise content management" with "intelligent information management". IIM is defined as "the strategies, methods, and tools used to create, capture, automate, deliver, secure, and analyze content and documents related to organizational processes.
Formally, a "database" refers to a set of related data accessed through the use of a "database management system" (DBMS), which is an integrated set of computer software that allows users to interact with one or more databases and provides access to all of the data contained in the database (although restrictions may exist that limit access to particular data).
Data modeling during systems analysis: In systems analysis logical data models are created as part of the development of new databases. Data modeling is also used as a technique for detailing business requirements for specific databases. It is sometimes called database modeling because a data model is eventually implemented in a database. [4]