Superclass
| Annotation | Refers a broad, high-level category or classification that groups related datasets or entities under a shared theme or characteristic. It functions as a parent category within a hierarchical structure, helping to organize and simplify data discovery by connecting more specific subcategories or classes, which inherit attributes from the superclass. |
| Type | TEXT |
Subclass
| Annotation | Refers to a lower level category or classification that groups related datasets or entities under a shared theme or characteristic. It functions as a subcategory within a hierarchical structure, helping to organize and simplify data discovery by connecting data elements into subcategories or classes, which inherit attributes from the subclass |
| Type | TEXT |
Parameter
| Annotation | Refers to the device parameters used to collect the values of the data element. |
| Type | TEXT |
Parameter Short Description
| Annotation | Provides short descriptive infromation on the data element. |
| Type | TEXT |
Parameter Description
| Annotation | Provides detailed information on the captured data. |
| Type | TEXT |
Parameter Answer Text
| Annotation | Answer text options for the specific parameter that can be selected, only found in Questionnaires |
| Type | TEXT/INTEGER/TIME |
Rank
| Annotation | Indicates the numerical order or position of the different answers as provided in the data extract. |
| Type | INTEGER |
Measurement Unit
| Annotation | Specifies the unit of measurement for the captured data element value. |
| Type | TEXT |
Value_Type
| Annotation | The Value Type of a data element describes the type of variable corresponding to it. 1. Integer - whole numbers; 2. Categorical (single) - a single answer selected from a coded list or tree of mutually exclusive options, for example a yes/no choice; 3. Categorical (multiple) - sets of answers selected from a coded list or tree of options, i.e. concurrent medications; 4. Decimal/Continuous - floating-point numbers, i.e. the height of a participant; 5. Text - data composed of alphanumeric characters, for example the first line of an address; 6. Date - a calendar date; 7. Time - a time; 8. Compound - a set of values required as a whole to describe some compound property, for example an ECG trace; 9. Binary object - a complex dataset (blob), for example an image; 10. Records - a summary showing the volume of records data available via the secure portal. |
| Type | TEXT |
Instrument
| Annotation | Refers to the device used to collect the values of the data element. |
| Type | TEXT |
Protocol
| Annotation | Details the data capture method used for collecting the data field, along with the relevant protocol, if applicable. |
| Type | TEXT |
Sexed
| Annotation | Indicates for which sexes the data is relevant. There are 3 possible values: 1. Both sexes - for example height; 2. Males only - for example prostate cancer history; 3. Females only - for example age at menopause. |
| Type | TEXT |
Stability
| Annotation | The Stability of a data element describes how 'fixed' the values are. There are four categories: 1. Complete - all data has been collected and will never change, an example would be the date at which a participant joined Qatar Biobank; 2. Updateable - all data has been collected, but the values may change over time, an example would be the volume of the initial blood samples collected by QBB which will decrease as new analyses are performed using them; 3. Accruing - data is still being gathered; 4. Ongoing - data is still being gathered and the values already held may change over time. Data-Fields which are Accruing or Ongoing may be classified as Preview-Only until such time as the data becomes less changeable. |
| Type | TEXT |
Strata
| Annotation | The Strata of a data element is a description of the nature of the data it describes. There are four categories: 1. Primary - the key clinically/scientifically relevant data-fields; 2. Derived - data which has been constructed by combining/processing values from one or more other data-fields; 3. Supporting - data which is clinical/scientific in nature, but largely superceded by a Primary data-field; 4. Auxiliary - data which describes the systems or processes used to acquire the data. |
| Type | TEXT |
Array
| Annotation | The Array property of a data element describes whether there are multiple data items for a given participant instance. There are two categories: 1. Single - only one data item is present for each participant 2. Multiple - more than one data item may be present for each participant. With a Multiple data-field, the maximum number of items present for any participant will be indicated in the Array Number of the data element. Where tests were performed multiple times during the same examination/visit (e.g. repeated blood pressure readings at the Qatar Biobank Clinic) then the results for each 'round' of measurement are presented as an array. |
| Type | TEXT |
Array_Number
| Annotation | For multiple data fields, the array number indicates the maximum number of items recorded for any participant. This applies when tests are conducted multiple times during the same examination or visit. |
| Type | TEXT |
Item_Type
| Annotation | The Item Type of a data element describes the type of item which is held. There are 4 categories: 1. Data - data values, of elementary types or with simple structures; 2. Samples - inventory information corresponding to biological samples held by Qatar Biobank; 3. Bulk - large complex objects, typically binary files (blobs) which cannot be decomposed into smaller chunks. 4. Records - inventory information describing the number of (records) held. |
| Type | TEXT |
Instances
| Annotation | The Instance property of a data element indicates how many occasions participants have measurements performed. There are three categories: 1. Singular - only one instance can be present, for example sex or year-of-birth; 2. Defined - more than one instance may be present, and each instance represents a fixed identifiable set of results across all participants; 3. Variable - more than one instance may be present, however there is no correspondence between (say) the 3rd instance for one participant and the 3rd instance for another; To illustrate: If everyone were weighed on each birthday (and only on those occasions) then the data-field for weight would be a Defined Instance. If everyone was weighed on an ad-hoc basis, then it would be a Variable Instance. If all participants attended a clinic 3 times and had their height measured twice during each visit, then the data-field would have 3 instances, each of which being an array of 2 values. |
| Type | TEXT |
Number of instances
| Annotation | Indicates how many times measurements have been taken for a data element across participants. |
| Type | INTEGER |
Sensitivity_Level
| Annotation | Indicates the sensitivity level of the data element, categorized into three tiers: sensitive, highly sensitive, and Personally Identifiable Information (PII) |
| Type | TEXT |