Granularity

• Granularity refers to the level of detail or resolution at which data is collected, stored, processed, or presented
• It is a measure of how fine or coarse-grained the data is, and it impacts the level of precision and information that can be extracted from the data

In the context of data, granularity can be applied to various aspects:

• Time Granularity: Time granularity refers to the level of detail in the time intervals used to collect or represent data. For example, data collected at a daily, hourly, or minute-by-minute level has different time granularities
  • See Cadence

• Spatial Granularity: Spatial granularity relates to the level of detail in the geographic areas or regions represented in the data. For instance, data collected at the country, city, or street level has different spatial granularities.

• Data Granularity: Data granularity can refer to the level of detail in the individual data points or records. Data can be collected at a high granularity, where each data point represents a small and specific value, or at a low granularity, where data points represent larger and more aggregated values.

• Process Granularity: Process granularity relates to the level of detail in the steps or stages of a process. It can refer to the degree of breakdown or decomposition of the process into smaller subprocesses or tasks.

Dave Snowden

• Granularity matters and this is a Goldilocks solution
  • Too finely grained, and things get random
  • Too coarsely grained, and novel interactions that would give rise to new emergent properties are suppressed
  • At the right level of granularity, things can combine and be recombined in different ways
    
• The best way to date (and there will be more) to achieve this is the .10 Estuarine Mapping instruction - keep breaking things down until you agree
  
• In terms of Assemblage Theory, changing the granularity is a deterritorialization method that can change the affordances for distributed action within a system.