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Appendix A Developer Documentation Learn how to describe what providers and drugs are covered by a particular health plan. JSON All information must be described in the JSON file format. JSON is a

How to fill out machine-readable data dictionary

How to fill out machine-readable data dictionary:

1. Start by gathering all the necessary information about the data you want to include in the dictionary. This may include data names, descriptions, data types, and any additional attributes or metadata.
2. Organize the gathered information into a structured format, such as a spreadsheet or a database. This will make it easier to manage and update the data dictionary in the future.
3. Assign unique identifiers to each data element or field within the dictionary. These identifiers will help in referencing and linking the data to other related information.
4. Provide clear and concise descriptions for each data element. These descriptions should explain the purpose and meaning of the data, making it easier for users to understand and utilize the dictionary.
5. Specify the data type for each data element, such as text, numeric, date, or boolean. This will enable users to correctly interpret and process the data.
6. Include any additional attributes or metadata that are relevant to the data, such as allowable values, range constraints, or units of measurement.
7. Validate the data within the dictionary to ensure accuracy and consistency. This can be done by reviewing the information with domain experts or by performing data quality checks.
8. Regularly update and maintain the data dictionary as new data elements are added or existing ones are modified. It is important to keep the dictionary up to date to reflect any changes in the underlying data.

Who needs a machine-readable data dictionary?

1. Data architects or data modelers: They need the data dictionary to design and maintain data models, ensuring consistency and quality across different systems.
2. Database administrators: They can utilize the data dictionary to manage database structures, optimize query performance, and enforce data integrity rules.
3. Developers and programmers: The data dictionary helps them understand the structure and semantics of the data, making it easier to write code that interacts with databases.
4. Business analysts: They can reference the data dictionary to understand the meaning and context of data, facilitating accurate analysis and reporting.
5. Data stewards or data governance professionals: They use the data dictionary to ensure compliance with data governance policies and standards, as well as to establish data lineage and data lineage.
6. Data consumers: Anyone who uses the data within an organization can benefit from a machine-readable data dictionary, as it provides a comprehensive and reliable source of information about the data.

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What is machine-readable data dictionary?

Machine-readable data dictionary is a structured collection of data with detailed descriptions, enabling automated processing by machines.

Who is required to file machine-readable data dictionary?

Entities mandated by regulations or standards to provide machine-readable data dictionaries are required to file them.

How to fill out machine-readable data dictionary?

Machine-readable data dictionaries are typically filled out by documenting each data element along with its attributes in a structured format.

What is the purpose of machine-readable data dictionary?

The purpose of a machine-readable data dictionary is to provide a clear and detailed reference for data elements, facilitating data management and communication.

What information must be reported on machine-readable data dictionary?

Information such as data element names, descriptions, data types, domain values, and relationships with other data elements must be reported on a machine-readable data dictionary.