## 3 Materials and Methods
Taking these input arguments, the EOI binding triples are generated by performing the steps:  
1. Extracting EOI coded value (_386948008_) from the argument 1.1 using the path from 1.2. 2. Querying the terminology/ontology mapping service using the EOI coded value (_386948008_) and the argument from 3.1 (SNOMEDCT): [[http://data.bioontology.org/ontologies/SNOMEDCT/classes/http%3A%2F9%2](http://data.bioontology.org/ontologies/SNOMEDCT/classes/http%3A%2F9%2) Prunt.bioontology.org%2 Fontology%2F8 NOMEDCT%2F386948008/mappings?apikey=]([http://data.bioontology.org/ontologies/SNOMEDCT/classes/http%3A%2F9%2](http://data.bioontology.org/ontologies/SNOMEDCT/classes/http%3A%2F9%2) Prunt.bioontology.org%2 Fontology%2F8 NOMEDCT%2F386948008/mappings?apikey=)\(\Upsilon\)\(\backslash\)T1\(\backslash\)textless|apikey>[26]. 3. Obtaining the equivalent data item in the target dataset from the response of the terminology/ontology mapping service, filtering by the identifier of the target dataset (from argument 3.2): @id: [[http://www.drugbank.ca/drugs/DB00099](http://www.drugbank.ca/drugs/DB00099)]([http://www.drugbank.ca/drugs/DB00099](http://www.drugbank.ca/drugs/DB00099))[29] The URL _[[http://www.drugbank.ca_](http://www.drugbank.ca_)]([http://www.drugbank.ca_](http://www.drugbank.ca_)) does not provide a LOD representation of the DrugBank dataset. A further step is required (step IV) to convert this data item into a URL belonging to an existing LOD dataset that can be exploited through SPARQL queries. 4. Using the URL prefix provided in the argument 4.1, plus the coded value of the data item in the target terminology (_DB00099_). This results in a URL belonging to an existing LOD dataset that can be used in a query: _[http://bio2 rdf.org/drugbank:DB00099_](http://bio2 rdf.org/drugbank:DB00099_). 5. Building the EOI binding triples using the predicate from argument 2.1 (_skosexactMatch_): <[[http://purl.bioontology.org/ontology/SNOMEDCT/386948008](http://purl.bioontology.org/ontology/SNOMEDCT/386948008)]([http://purl.bioontology.org/ontology/SNOMEDCT/386948008](http://purl.bioontology.org/ontology/SNOMEDCT/386948008))> <[[https://www.w3.org/2009/08/skos-reference/skos.html#exactMatch](https://www.w3.org/2009/08/skos-reference/skos.html#exactMatch)]([https://www.w3.org/2009/08/skos-reference/skos.html#exactMatch](https://www.w3.org/2009/08/skos-reference/skos.html#exactMatch))> <[http://bio2 rdf.org/drugbank:DB00099](http://bio2 rdf.org/drugbank:DB00099)> The _skos:exactMatch_ predicate is used to generate EOI binding triples of the form <_SnomedDrug> skos:exactMatch <DrugBankDrug>_. Values for subjects and objects in these triples are obtained at runtime. Specifically, the <_SnomedDrug>_ is defined by the value of the EOI in the EHR archetype instance, whereas the <_DrugBankDrug>_ is a term from the DrugBank LOD dataset equivalent to <_SnomedDrug>_. (C) Querying Semantic Web datasets. The next step is to build a SPARQL query to retrieve the augmentation content. The query graph is formed by the target dataset plus the EOI binding triples (Figure 3). In this way, the query can be parametrized with the EOI binding triples, allowing the target dataset to be searched for the augmentation content using the EOI coded values as query criteria. At runtime, this approach leads to identification and retrieval of the augmentation content for a given EHR extract (step 5 of Figure 2), by requesting only the data items from the query graph that include the predicates used in the EOI binding triples. The results of the SPARQL query are formatted according to the W3C schema for query results, which is a canonical representation of contents from the Semantic Web. Example: The example illustrates a SPARQL query to obtain the augmentation content, which consists of information about drug-drug interactions for the active medications in the initial EHR extract (an instance of the medication archetype).