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Data Model Legibility A comparison of 3 graphic styles J.C. Forgotten Dept. of Information Science, University of Bergen, N5020 Bergen, Norway email Joan IFI.USB.no M.E. Crosby Dept. of Information

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What is data model legibility?

Data model legibility refers to the comprehensibility and clarity of the structure and relationships within a data model. It ensures that the data model is easily readable and understandable by users and stakeholders.

Who is required to file data model legibility?

The responsibility to file data model legibility lies with the organization or entity that owns and maintains the data model. This can be the data architect, data steward, or the IT department, depending on the organizational structure.

How to fill out data model legibility?

To fill out data model legibility, you need to document the data model using standard notations such as Entity-Relationship (ER) diagrams or Unified Modeling Language (UML) diagrams. Clearly define entities, attributes, relationships, and constraints within the data model. Use appropriate naming conventions and provide accompanying documentation to explain the purpose and usage of the data model.

What is the purpose of data model legibility?

The purpose of data model legibility is to ensure that the data model is easily understood and interpreted by intended users. It helps in promoting effective communication, collaboration, and decision-making related to the design, development, and usage of the data model. Legible data models facilitate system development, data integration, data analysis, and data governance.

What information must be reported on data model legibility?

The information that should be reported on data model legibility includes the names of entities, attributes, relationships, and constraints within the data model. It should also include the purpose, usage, and scope of the data model, as well as any relevant business rules, data definitions, or data quality requirements.