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Update faq.md Add Missing Data FAQ #15

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21 changes: 20 additions & 1 deletion docs/documentation/user-documentation/faq.md
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Expand Up @@ -108,10 +108,29 @@ I have a negative control

_There is no specific taxonomy terms for positive and negative controls_

## How do fill in negative controls?
## How do I fill in negative controls?

_TODO_

## How to fill in missing data

Follow the [INSDC Missing Value Reporting](https://www.insdc.org/technical-specifications/missing-value-reporting/) specifications.
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Follow the [INSDC Missing Value Reporting](https://www.insdc.org/technical-specifications/missing-value-reporting/) specifications.
Follow the [INSDC Missing Value Reporting](https://www.insdc.org/technical-specifications/missing-value-reporting/) specifications.

- Missing data is (meta)data that **can not** be reported. This can be due to various constraints, such as:
- the data is truly missing, meaning it is not known and can not be known;
- it can not be shared for privacy reasons;
- it can not be shared due to data agreement restrictions;
- it is not applicable to that particular field (e.g. it is a negative control and the field does not apply)
- Missing data should only be reported for **mandatory** fields, not for **recommended** or **optional** fields. For the latter two, simply leave the field blank if the (meta)data are missing.
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- it is not applicable to that particular field (e.g. it is a negative control and the field does not apply)
- Missing data should only be reported for **mandatory** fields, not for **recommended** or **optional** fields. For the latter two, simply leave the field blank if the (meta)data are missing.
- it is not applicable to that particular field (e.g. it is a negative control and the field does not apply)
- Missing data should only be reported for **mandatory** fields, not for **recommended** or **optional** fields. For the latter two, simply leave the field blank if the (meta)data are missing.
Each of these cases have specific ways of encoding 'missingness' as per the INSDC guidelines.

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I think the mandatory fields sentence should go at the beginning of this section in a preamble paragraph and say more along the lines of:

Fields in MIxS that are mandatory always require something filled into the given metadata entry. If you do not have this information, you must encode this using the specific 'missing information' categories as below.

While optional fields in MIxS can be left blank, if you have a specific reason the information will never be able to be reported (see examples below), then it is good to use these missing data categories there also.

- There are three levels at which you can report missing data, with an increasing amount of specificity for each: _**top level**_, _**lower level**_, and _**reporting level**_. Be as specific/granular as possible when reporting missing values. The _top level_ indicates that the data are missing, while the _lower-_ and _reporting_ levels give a reason (from the [controlled vocabulary](https://www.insdc.org/technical-specifications/missing-value-reporting/)) why the data are missing.
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I would break up the three level descriptions into bullets

- Always report the _top level_ (i.e. "not applicable" or "missing") even when reporting at the more granular levels, in which case separate the _top level_ and _lower/reporting level_ terms with ": ".
- If using terms from the most granular level (_reporting level_), then exclude the _lower level_ term, as each _reporting level_ term is a "child" of the _lower level_, which can then be inferred based on the [table](https://www.insdc.org/technical-specifications/missing-value-reporting/).

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Note that the way that you can use the missing data categories in a particular metadata entry will depend on the implementer of the MIxS-MInAS standard.
For example, in some implementations, numeric-only metadata terms may not allow non-number characters and thus will fail validation when giving e.g. `not applicable: control sample` category.
In these cases, refer to the documentation of the place you are submitting your metadata to.

### Examples
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### Examples
### Examples

- missing
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And let's provide context for each example:

  • How to encode missing info for a negative control (not applicable)
  • How to encode missing info because the infromation was not collected during a historical sampling event, or the collection records burnt down
  • How to encode missing information because native/indigenous groups do not permit sharing of this information

- missing: not collected
- not applicable: control sample
- missing: endangered species

## How to fill in sample age information

_TODO_
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