# Linked Data for Life Sciences
## Preliminaries
### Semantic Web Technologies
```This first triple states that the resource 'Netherlands' has the capital 'Amsterdam', which is also a resource. The second triple states that the resource 'Amsterdam' is of type 'City', which is a class in the DBpedia ontology (discussed further in this section). This way, we can link individual facts together, either in the same data set or even across data sets (when the object value resource can be from a different data set), thus calling it Linked Data. Triple store and SPARQL: RDF data is stored in triple stores, which are software programs that are equipped to store and index RDF data efficiently, in order to enable querying this data easily and effectively. A triple store for RDF data is like DBMS for relational databases. Virtuoso [8], Sesame [9], and BigOWLIM [10] are typical examples of triple stores for desktop and server computers. To access the triples (data) stored in triple stores, there is a query language called SPARQL. \"The SPARQL Protocol and RDF Query Language (SPARQL) is the W3C standard query language and protocol for RDF (w3.org/TR/rdf-sparql-query/)\" [11]. SPARQL facilitates the user to write queries that consist of triple patterns along with conjunctions (logical \"and\"), disjunctions (logical \"or\") and/or a set of optional patterns [12]. The SPARQL query specifies the pattern(s) that the resulting data should satisfy. The results of SPARQL queries can be result sets or RDF graphs. Ontology: In order to semantically represent data, W3C introduces the concept of an ontology, which is defined as \"the terms used to describe and represent an area of knowledge\" [13]. An ontology is specific to one domain area of knowledge. The ontology contains concepts/terms, also called classes, and relationships among those terms. The relationships between these classes can be expressed by using a hierarchy, i.e., superclasses represent higher-level concepts and subclasses represent finer, more specific, concepts. The finer classes inherit all the features and attributes that the higher classes have. Additionally, properties express another level of relationship. In other words, an ontology defines a set of classes (e.g., \"Writer\", \"Book\", \"Person\"), and their hierarchy, i.e., which class is a subclass of another one (e.g., \"Writer\" is a subclass of \"Person\"). The ontology also defines how these classes interact with each other, i.e., how different classes are connected to each other via properties (e.g., a \"Book\" has an author of type \"Writer\"). FAIR principles: Another important concept that has been recently introduced is making all this well-structured data as well as metadata on the Web FAIR [14]--that is, making it Findable, Accessible, Interoperable, and Reusable. The FAIR Principles focus on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. smartAPI: Lastly, it is important to provide Application Programming Interfaces (APIs) to retrieve the data. APIs are a set of functions and procedures that allow the creation of applications, which access the features or data of an operating system, application, or other service. Our previous work introduced smartAPI [15] (smart-api.info), with the aim to make APIs FAIR: Findable with the API metadata and the registry; Accessible with the detailed API operations metadata; Interoperable with the responseDataType metadata (profiler); and Reusable with the access to existing APIs stored in an open repository. smartAPI leverages the use of semantic technologies such as ontologies and Linked Data for the annotation, discovery, and reuse of APIs.