The principles of the questionniare documentation are:
1. Maintain and do not alter the semantic meaning of the questionnaire.
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Principle 1 is the overall aim of CLOSER's metadata ingest project and therefore the most important. CLOSER's target is to generate a search engine containing every instrument used by 8 individual longitudinal cohort studies. The search engine, often referred to as the CLOSER Discovery, is designed for examining the logical flow and semantic meaning of the instruments. Therefore Principle 1 has to be kept to at all times.
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The three following principles were conceived purposefully to give structure and guidance as to how the first principle should be followed at all times and in all situations.
2. Do not correct the questionnaire.
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There are rare situations where Principle 2 must be violated in order to follow Principle 1 and document meaningful metadata. A real-world example of this is when a code value is accidently printed with the wrong value. There is no easy way to alias code values and CLOSER's documentation would suggest that there are two distinctly different codes, while the dataset would only refer to one of the codes. In this case, documenting the mistake would mislead the user and violate Principle 1.
3. Only record what is contained within the questionnaire.
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An example where the metadata must be added to in order to maintain Principle 1 is when a questionnaire uses an arrow to denote a condition. It is impossible to document an arrow literally and leaving it out of the documentation altogether changes the logical flow of the questionnaire. Therefore, text representing the arrow's meaning has to be added.
4. Do not allow the data recorded (i.e. the variables) to inform the metadata archiving.
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The most common situation where breaking Principle 4 is valid is when Principles 2 or 3 must be broken. For example, in the situation where it is most appropriate to correct the questionnaire, it is obviously vital to check whether the mistake was intentional or not and if the mistake had a distinct effect on the collected data.
