| layout | default |
|---|---|
| title | DSM-2-C2 |
| parent_level | level2 |
| nav_exclude | true |
| Identifier | DSM-2-C2 |
|---|---|
| Name | Where applicable, the Dataset Model organises data values within a dataset according to the Tidy Data Principles |
| Maturity Level | 2 |
| Category | Content and Context |
| Granularity Level | Dataset Fields |
| Description | This is a data-related requirement that is a pre-requisite for the 'accuracy' of metadata that FAIR principle (R1) refers to. This requirement is borrowed from one of the key Tidy Data Principles, which states that each column/field should be a single variable. This prevents the often seen scenario in structured data whereby a single column header might carry values for more than one variable. For example, 'temperature_screening', 'temperature_followup', each column implicitly carries the value for a visit variable and a value for an observation temperature in this case. This indicator therefore requires the data manager to split these variables into two fields: One per variable that is a field for temperature and a field for visit. This is a pre-requisite to DSM-2-C5 and DSM-2-C6 since each Dataset Field is expected to control its terms and create a local dictionary. Unless individual concepts are reported per Dataset Field it will not be possible to find suitable terms that can later be standardised for level 3. |
| Related DSM Indicator | DSM-2-C5, DSM-2-C6 |
| Related FAIR Principle | R1. Meta(data) are richly described with a plurality of accurate and relevant attributes |
| Cross-reference FAIR indicators |