Electronic data files that adhere to a predefined format and structure, facilitating standardized and consistent data analysis across various applications or systems.

Data Interoperability:

The ability of standard analytical files to seamlessly exchange and integrate data across different platforms, ensuring compatibility and ease of use in diverse analytical environments.

Structured Data:

Information organized in a standardized format within standard analytical files, allowing for systematic storage, retrieval, and analysis.

Data Harmonization:

The process of aligning and standardizing data from various sources within standard analytical files to ensure consistency and coherence for meaningful analysis.

Data Dictionary:

A reference guide or documentation within standard analytical files that defines the variables, codes, and meanings used in the dataset, promoting clarity and understanding.

Cross-Platform Compatibility:

The capability of standard analytical files to function seamlessly across different software applications and systems, enhancing accessibility and usability.

Normalization:

The process of organizing and structuring data within standard analytical files to eliminate redundancies and inconsistencies, ensuring accurate and reliable analyses.

Data Validation:

The verification of data integrity and accuracy within standard analytical files, employing checks and validations to identify and rectify errors.

Query Language:

A specialized language or set of commands used to retrieve specific data from standard analytical files, enabling users to extract relevant information for analysis.

Open Data Standards:

Specifications and formats for standard analytical files that are openly accessible and widely adopted, promoting transparency, collaboration, and interoperability.