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Before a template can be processed, it is important that the input data is represented in a clear and unambiguous way. This is required to ensure that the template is processed in the expected manner, and the intended results are produced. In this section, we explain some of the considerations in representing and preparing the input data for processing.

Input Data Representation

Template input data may be represented in a variety of forms, ranging from flat tabular structures to nested serializations. Irrespective of the format, however, it is important that there is no ambiguity as to how each piece of input data should be used to create the resulting expressions. This can be particularly challenging where repetition of relationship groups or attribute name-value pairs is required.

The UML diagram below illustrates the logical structure of expression template input data. Each set of Expression Template Input Data includes the data intended to be used to create one or more expressions. The data used to populate a single expression is referred to in this model as Expression Data. Each Expression Data (i.e. the data for a single expression), may include at most one Definition Status Slot (with a slot name and a definitionStatus value), zero or more Focus Concept Slots (each with a slotName and zero or more values), zero or more Relationship Group Slots (each with a group name), and zero or more ungrouped Attribute Name-Value Pair Slots (each with a name). Each Relationship Group Slot has zero or more Relationship Group Data instances in the input data. Each of these Relationship Group Data instances has input data for one to many Attribute Name-Value Pair Slots. And for each Attribute Name-Value Pair Slot within a Relationship Group Data instance, there are zero to many Attribute Name-Value Pair Data instances, each with at most one Attribute Name Slot (with name and value), and at most one Attribute Value Slot (with name and either a simple data value, or an Expression Data instance of its own).

Input Data Examples

In this section, we provide some examples of unambiguous expression template input data, and discuss how this input data can be used to populate each expression.

Example 1

The expression template below is used to create expressions that represent a |Disease| with one or more |Finding site| and |Associated morphology|.

When using expression templates, such as this one, in which attribute name-value pairs and relationship groups may be repeated, the input data should be explicit about which attribute name-value pairs should be grouped together and which groups should be included in a single expression. 

    [[+tok ("===", "<<<") @DefStatus)]] [[+scg (<<  64572001 |Disease| ) @Disease]] : 
        [[@Group]] { 
363698007 |Finding site|   =  [[+ (<<  272673000 |Bone structure| ) @Site]],
                     
116676008 |Associated morphology|   =  [[+ (<<  72704001 |Fracture|  ) @Morphology]] }
To populate this template, the input data should be explicit about which data values are used to populate each slot, and how these values are grouped into relationship groups. The table below shows an abstract representation of some input data that may be used to process the expression template above. The relationship to the logical model above has bee noted in brackets under each column name. Please note that the first column is used to group together the data intended to populate each expression, and subsequent columns are named after the associated slot. Relationship group slots are used to group the data that is intended to populate a single relationship group. Attribute name-value slots are not required in this example. They are are only required where both the attribute name and attribute value use a slot.

Using the above input data to populate the given expression template will result in following four expressions.

Example 2

The expression template below is used as a pattern for family history expressions. It contains a nested relationship group (i.e. SSgroup) inside the outer relationship group (i.e. AFgroup). To populate this expression template, the input data must be clear as to where each value should be used, and how these values should be grouped into relationship groups and expressions.

    [[+id (<<   413350009 |Finding with explicit context|  ) @Condition]]:
        [[ 1..2 @AFgroup ]] { [[1..1]]  
246090004 |Associated finding|   = ([[+id (<<   404684003 |Clinical finding|  ) @Finding]]:
            [[0..1 @SSgroup]] { [[0..1]]  
246112005 |Severity|   = [[+id (<   272141005 |Severities|  ) @Severity]],
                                [[0..1]]  
363698007 |Finding site|   = [[+id (<   91723000 |Anatomical structure|  ) @Site]] }),
                        [[1..1]]  
408732007 |Subject relationship context|   = [[+id (<   444148008 |Person in family of subject|  ) @Relationship]],
                        [[1..1]]  
408731000 |Temporal context|    = [[+id (<   410510008 |Temporal context value|  ) @Time]],
                        [[1..1]]  
408729009 |Finding context|    = [[+id (<   410514004 |Finding context value|  ) @Context]] }

To populate the above template, the following example input data has been defined. Once again, the relationship to the logical model above has been noted in brackets under each column name.

The relationship to the logical model above has bee noted in brackets under each column name. Please note that the first column is used to group together the data intended to populate each expression, and subsequent columns are named after the associated slot. Relationship group slots are used to group the data that is intended to populate a single relationship group. Attribute name-value slots are not required in this example. They are are only required where both the attribute name and attribute value use a slot.

Expression
1
2
3

Example 3

The expression template below represents a procedure with a single method and one or more procedure devices. Please note that in the first attribute name-value pair, both the attribute name and the attribute value use a slot. Because this name-value pair is repeatable, the input data needs to include an attribute name-value pair slot to ensure that the corresponding attribute name and attribute value stays connected.

    [[+id (<<  71388002 |Procedure| ) @Procedure]]:
        [[1..1 @Group]]
            { [[1..* @PD_ANVpair]] [[+id (< 
405815000 |Procedure device| ) @DeviceType]] = [[+ (< 260787004 |Physical object| ) @Device]],
              [[1..1]] 
260686004 |Method|  = [[+ (< 129264002 |Action (qualifier value)| ) @Method]] }

The following input data has been created to populate the above template. Because, in the above template, the first attribute name-value pair is repeatable and uses a replacement slot for both the attribute name and attribute value, the input data needs to include the attribute name-value pair slot to ensure that the corresponding attribute name and attribute value stays connected.

Expression Data

Procedure
(Focus Concept Slot)

Group
(Relationship Group Slot)

PD_ANVpair
(Attribute NV Pair)

DeviceType
(Attribute Name Slot)

Device
(Attribute Value Slot)

Method
(Attribute Value Slot)

111
2

1

1
2

Using the above input data to populate the given expression template will result in the following two expressions.

Example 4

The expression template below represents a  |Disease| with one or more values for |Finding site| and  |Associated morphology|, grouped into one or more relationship groups.

     64572001 |Disease|
        [[@Group]] { 
363698007 |Finding site|   =  [[+ (<<  272673000 |Bone structure| ) @Site]],
                     
116676008 |Associated morphology|   =  [[+ (<<  72704001 |Fracture| ) @Morphology]] }
In this example, we will show an alternative format for representing the input data.  A wide variety of formats are possible for representing template input data, including json, xml, tsv, csv etc. The exact format used will depend on the format required by the template processor.

Below is an example of some input data for the above template that uses the same abstract representation as above. This time we have not shown the explicit relationship to the logical model - however this can be inferred from the column names.

As an example of an alternative data input format, this example input data is represented below in JSON.

Example JSON Input Data
{"Expression Data": [
        { "Group": [
                {  "Site":"312763008 |Bone structure of trunk|",
                    "Morphology":"72704001 |Fracture|" },
                {  "Site": "84667006 |Bone structure of cervical vertebra|",
                    "Morphology": "72704001 |Fracture|" } ] },
        { "Group": [
                {  "Site":"71341001 |Bone structure of femur|",
                    "Morphology": "72704001 |Fracture|" } ] },
        { "Group":[  
                {  "Site":"12611008 | Bone structure of tibia|",
                    "Morphology": "72704001 |Fracture|" } ] } ] }

Simplification of Data Representation

While it is important that there is no ambiguity as to how each piece of data should be used to create the resulting expressions, there are often opportunities to make the input data much simpler than is represented in the full logical model above. In particular:

  • When the maximum cardinality of a relationship group is 1, there is no need to include the relationship group slot in the input data to group the attributes it contains;
  • When the maximum cardinality of an attribute name-value pair is 1, there is no need to include the attribute name-value pair slot in the input data to group the corresponding name and value pairs;
  • When there is either an attribute name slot with a fixed attribute value, or a fixed attribute name with an attribute value slot, there is no need to include the attribute name-value pair slot in the input data to group the corresponding name and value pairs.
  • When the maximum cardinality of the focus concept slot is 1, the
  • whenever the maximum cardinality of the focus concept, the relationship groups and attribute

With this in mind, the examples in 8 Expression Template Examples simplify the input data, where appropriate, using these assumptions and an implicit association with the logical model described above. 

 


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