# Embracing the Future Internet of Things +
## 3 IoT Platform Capabilities
### Information Transparency  
The capability of having transparent exchange is fundamental for the future hyper-connected IoT systems. This capability consists of semantic interoperability and semantic mediation. Interoperability is the ability of multiple systems to exchange data. _Semantic interoperability_ ensures consistency of data across interacting systems regardless of their individual data formats as these systems attribute the same meaning to the exchanged data. The semantics of data can be defined in a way that different data formats use a shared vocabulary and the vocabulary is specified in an ontology. The concept of semantic interoperability is applicable to all elements of the future IoT framework from data sources to cloud and applications. _Semantic mediation_ is the capability of transforming data coming from one system to make it useful to another system. To achieve interoperability cloud needs to have certain standards so that it can provide contextualized access to the applications. Conversion of data that has certain standards such as oneM2M [13] to other standards such as FIWARE OMA NGSI (Open Mobile Alliance Next Generation Service Interface) [9] can be done on both edge and cloud [14]. Considering that there are many existing standards and communication protocols, semantic mediation is necessary for the realization of communications interoperability between different IoT elements and devices with heterogeneous communication protocols (e.g., Wi-Fi, Zigbee, Bluetooth, 3 GPP). An example of a semantic approach to IoT interoperability is the combination of open standards such as OMA NGSI with the semantic concept of ontology (see Figure 4) such as the one developed within the FIESTA-IoT EU project [15; 16] which is a synthesis of known ontologies and taxonomies (such as Semantic Sensor Network-SSN [17], M3-lite [18], IoT-lite [19]) with the aim of covering the contexts generated by multiple heterogeneous IoT deployments. The ontology is conceived to deal with resources description and observations. In an ontology, rich and complex knowledge is represented as a graphs of nodes, expressing things, and links between nodes that express the relationship between two things. Things are categorized in classes and every thing is an instance of a class. A class may have sub-classes, and an instance of a class is also an instance of all the super-classes of such class. Classes and relationships are specified into taxonomies and an ontology can use classes and relationships from one or more taxonomies. Each class and property used into an ontology is uniquely identified by a namespace prefix and the class or property specific name. For example, _ssnt:Sensor_ is a class defined in the SSN ontology. For sake of readability, in this paragraph, we are omitting the namespace prefix, but they are all represented in Figure 4. In the FIESTA-IoT ontology, the _Observation_ is the core element that bridges the physical phenomena sensed in the M3-lite taxonomy [20] via the _QuantityKind_ (e.g., _Temperature, CountPeopleMoving_). This taxonomy is fundamental to cover the many different sensors of various IoT deployments. Each _Observation_ has a timestamped (_Instant_), a location (_Point_), a unit _Unit_, observed by a sensor (_Sensor_) that is the superclass for all kind of sensors as defined in the M3-lite taxonomy (e.g., _Thermoneter_, _PeopleFlowCountSensor_). In the NGSI standard, each piece of NGSI context data refers to an identifier of the entity, namely _Entitiyld_ and reports several _ContextAttributes_. EntityLds might have one or more _DomainMetadata_ which specify metadata in common to all the attributes (e.g., the location of the sensed attributes). In addition, each _ContextAttributes_ might have multiple _AttributeMetadata_ that are specific to such attribute.