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A Data Naming Practitioner s Guide

Version Date: 8-31-95 Version #: 095-046 IRM Guideline 10, Version 1

DOCUMENT OVERVIEW Purpose and Scope of This Document This document: 1) provides assistance to technical data practitioners who need to establish data naming policies, standards and methods, or create standard data names, 2) establishes best practices for data naming, and 3) provides starter kit standards and examples of standard data names.

Data names that are in the scope of this document include names for computerized data and data model objects. Computerized data is actual data that has been (or will be) collected, stored, or accessed by an organization or its customers in the course of doing business. Computerized data are destined for storage within a computer, and thus are given standard data names to provide unique identification. Data model objects describe business objects - persons, places, things or concepts -that are represented in a data model or business object model. Data model objects may, or may not, have counterparts in computerized data.

Physical data names are also created to represent computerized data within a system implementation. Physical data names meet syntax requirements of programming languages or data base managers. When implemented within a system, a single data item may end up with multiple physical data names. Since data names are used to identify and locate data, redundant data names can present a major challenge for accessing or sharing data. The problems of redundant data names can be addressed through the use of standard data names that represent an organization's data. A standard name provides a common point to which multiple physical names (also known as aliases) can be linked. The links identify common data and show usage of the data across systems - an important first step toward being able to access the data. This document addresses the need for standard data names to be linked to physical data, but does not address standards for physical data names.

Data names must also be created for other kinds of data, such as system data and implementation data. System data is data about system objects, such as files or records. Implementation data is data used internally by systems, such as internal program counters. System data names and implementation data names are outside the scope of this document.

Audiences for This Document The intended audience for this document is technical data practitioners, such as data administrators, data modelers, systems analysts, data warehouse or repository implementers, data base administrators and those establishing vendor contract performance requirements. NOTE: Non-technical audiences may prefer to read the companion document: Data Administration: A Data Naming Primer instead of, or in addition to, this document.

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