Representative sampling? Views from a regulator and a measurement scientist.

Area of Science:

• Analytical Chemistry
• Metrology
• Environmental Science

Background:

• The term 'representative sampling' is frequently used but lacks a clear, consistent definition.
• This ambiguity can foster unrealistic expectations regarding sampling quality and data reliability.
• Misinterpretations impact the validity of measurement results and subsequent regulatory actions.

Purpose of the Study:

• To clarify the ambiguity surrounding the term 'representative sampling'.
• To propose a more precise and functionally descriptive alternative term for sampling methodologies.
• To enhance the understanding of sampling's role in ensuring data fit-for-purpose.

Main Methods:

• Conceptual analysis of sampling terminology in scientific literature.
• Evaluation of the impact of sampling definitions on measurement uncertainty.
• Comparison of 'representative sampling' with alternative terminologies.

Main Results:

• 'Representative sampling' is often ill-defined, leading to overconfidence in sampling outcomes.
• The lack of clarity in 'representative sampling' can compromise the reliability of measurement results.
• A proposed alternative term, 'appropriate sampling', better reflects the intended use and uncertainty requirements of measurements.

Conclusions:

• The term 'representative sampling' should be used with caution due to its inherent ambiguity.
• 'Appropriate sampling' is recommended as a more accurate descriptor for sampling strategies that yield fit-for-purpose data.
• Adopting 'appropriate sampling' will improve the clarity and reliability of scientific measurements and regulatory decisions.