## 5 Use Case
\begin{table}
\begin{tabular}{c c c} \hline \hline  & **Variable** & **Value** \\ \hline \multirow{6}{*}{Inputs} & Initial EHR Extract & An instance of the summary EHR archetype provided at runtime \\  & _/content[archetype\_id=“at0043”]_ & _/members[archetype\_id=“at0024”]_ \\  & Path to the EOI in the initial EHR archetype & _/members[archetype\_id=“at0053”]_ \\  & Path to the EOI in the initial EHR archetype & _/members[archetype\_id=“at0054”]_ \\  & _/items[archetype\_id=“at0172”]_ & _/parts[archetype\_id=“at0181”]_/value_ \\  & The predicate URL & _[[http://www.w3.org/2004/02/skos/core](http://www.w3.org/2004/02/skos/core)]([http://www.w3.org/2004/02/skos/core](http://www.w3.org/2004/02/skos/core))\&exactMatch_ \\  & The name of the source terminology employed by & \\  & the EOI coded values & \\  & The identifier URL of the target & \\  & terminology/ontology returned by the & _[[http://www.drugbank.ca/drugs_](http://www.drugbank.ca/drugs_)]([http://www.drugbank.ca/drugs_](http://www.drugbank.ca/drugs_)) \\  & The URL prefix of data items in the target dataset & _[http://bio2 rdf.org/drugbank:_](http://bio2 rdf.org/drugbank:_) \\ Output & The EOI binding triples & RDF triples that relates EOIs from the initial EHR extract with data items in the target dataset \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Inputs and output of the automatic procedure to build the EOI binding triples for the drug–drug interactions’ EHR augmentation. Figure 10: On the left, a LinkEHR visualization of the initial EHR archetype _CEN-EN13606-COMPOSITION_. _HistoriaClinicaResumida.v1_. On the right, two views of the initial EHR extract presented in HTML. The EOIs’ active episode of patients’ diseases (_EOI\({}_{1}\)_) and patients’ active medication (_EOI\({}_{2}\)_) and their coded values are highlighted on both the initial EHR archetype and the initial EHR extract. The resulting EOI binding triples for the drug-drug interactions' EHR augmentation are generated using inputs from Table 1 and the initial EHR extract introduced in Figure 10, whose EOI (patient's active medication) coded value is Filgrastim-[SNOMED-CT:386948008]. The EOI binding triples for the disease-related treatments EHR augmentation are built using inputs from Table 2 and the initial EHR extract introduced in Figure 10, whose EOI (active episodes of the patient's diseases) coded value is Alzheimer-[SNOMED-CT:26929004]. Table 3 summarizes information related to the EOI binding triples obtained for this use case. The EOI binding triples are injected at runtime in a SPARQL query as part of the query graph to collect the augmentation content. Figure 11 shows the SPARQL queries for the EHR augmentations' drug-drug interactions and disease-related treatments. The augmentation archetypes to normalize the augmentation content are modeled at design time. Figure 12 shows the drug-drug interactions' augmentation archetype (_CEN-EN13606-CLUSTER.DrugDrugInteraction.v1_) and the disease-related treatments' augmentation archetype (_CEN-EN13606-CLUSTER.DiseaseTreatment.v1_). These augmentation archetypes were modeled using LinkEHR. In both augmentation archetypes, the root element is a cluster containing at least one element for each variable in the SPARQL query to hold the augmentation content.