What is a concept included in data quality?

Data quality encompasses various attributes that determine the usefulness and reliability of data. One key concept included in data quality is data relevancy. This aspect pertains to how pertinent and applicable the data is to the context in which it is being used. Relevant data ensures that the information being analyzed or interpreted directly relates to the specific questions or challenges at hand. If data is irrelevant, it can lead to poor decisions or analyses that do not address the actual problem or scenario, ultimately affecting the efficacy of geospatial intelligence efforts.

Additionally, while data presentation methods, data categorization, and data volume play important roles in managing and utilizing data, they are not direct indicators of data quality in the same manner as relevancy. Presentation methods refer to how data is visually represented, categorization concerns the organization of data into groups, and volume deals with the amount of data available. None of these aspects fundamentally assess whether the data is appropriate or suitable for the intended analysis, which is why data relevancy is a more critical aspect of data quality.