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The EPA metadata registry furnishes an example of data stewardship. Note that each data element therein has a "POC" (point of contact). In 2023, ETH Zurich launched the Data Stewardship Network (DSN) to facilitate collaboration among employees engaged in data management, analysis, and code development across research groups. The DSN serves as a ...
In data governance groups, responsibilities for data management are increasingly divided between the business process owners and information technology (IT) departments. Two functional titles commonly used for these roles are data steward and data custodian .
A data steward is a role that ensures that data governance processes are followed and that guidelines are enforced, and recommends improvements to data governance processes. Data governance involves the coordination of people, processes, and information technology necessary to ensure consistent and proper management of an organization's data ...
Master data management (MDM) is a discipline in which business and information technology collaborate to ensure the uniformity, accuracy, stewardship, semantic consistency, and accountability of the enterprise's official shared master data assets.
Enterprise data management (EDM) is the ability of an organization to precisely define, easily integrate and effectively retrieve data for both internal applications and external communication. EDM focuses on the creation of accurate, consistent, and transparent content.
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 data usually need to be integrated with other data. In addition, the data need to interoperate with applications or workflows for analysis, storage, and processing. I1. (Meta)data use a formal, accessible, shared, and broadly applicable language for knowledge representation. I2. (Meta)data use vocabularies that follow FAIR principles I3.
Data warehouses are designed to manage and store the data. Data warehouses differ from business intelligence (BI) systems because BI systems are designed to use data to create reports and analyze the information, to provide strategic guidance to management. [90] Metadata is an important tool in how data is stored in data warehouses.