Data-Reference-Model
The Data-Reference-Model (DRM) is a part of the Federal Enterprise Architecture (FEA) framework, specifically designed to facilitate the identification, organization, and sharing of data across federal agencies. Here's a detailed look into its aspects:
Overview
The DRM provides a standard means by which data can be described, categorized, and shared among different government entities. It is structured to enhance the effectiveness of data management within and across federal agencies by promoting:
- Standardized data definitions
- Improved data sharing
- Enhanced data interoperability
- Better data governance
Components of DRM
The DRM is composed of several key components:
- Data Description: This component outlines how data elements are defined, including their semantics, structure, and relationships.
- Data Context: Focuses on the context in which data is used, detailing business contexts and processes.
- Data Sharing: Describes mechanisms for data exchange, including standards for interoperability.
- Data Standards: Provides guidelines and standards for data architecture, including metadata standards, data exchange standards, and data quality standards.
History and Development
The DRM was developed as part of the broader initiative to modernize federal IT under the E-Government Act of 2002, which mandated the development of an enterprise architecture for the federal government. Here are key points in its development:
- 2005: The initial version of the DRM was published by the Office of Management and Budget (OMB).
- 2012: The DRM was revised to align with new federal IT policies and to address emerging technologies and data management practices.
- The DRM has evolved to incorporate modern data management concepts like cloud computing, big data analytics, and data governance frameworks.
Application and Impact
The DRM aids in:
- Reducing redundancy in data collection and storage.
- Enabling cross-agency data sharing, thus improving inter-agency collaboration.
- Improving data quality through standardized definitions and governance.
- Supporting compliance with federal data policies and laws.
Challenges and Criticisms
Despite its benefits, the implementation of the DRM has faced challenges:
- Resistance to change from existing data management practices.
- Complexity in aligning various agency-specific systems with DRM standards.
- Ensuring data privacy and security while promoting data sharing.
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