What is the role of ontology alignment in data integration and interoperability?4 answersOntology alignment plays a crucial role in data integration and interoperability by facilitating the matching of ontologies to establish semantic correspondences between entities from different datasets. This process enables the creation of linked open datasets and ensures interoperability among diverse IT systems. By utilizing knowledge graph embeddings and techniques like absolute orientation, ontology alignment can effectively handle alignment noise and structural differences in ontologies, enhancing the accuracy of data integration. Furthermore, ontology alignment systems, when applied with background knowledge, prove beneficial in addressing the heterogeneity problem in logistics, allowing for better mappings between different standards and promoting interoperability in real-world scenarios.
What is interoperability?4 answersInteroperability refers to the ability of different systems or devices to exchange information and work together effectively. It allows for integration and coordination among disparate systems, enabling them to operate coherently and achieve common objectives. Interoperability is crucial in various domains, including information operations, smart cities, urban flood management, and data transfer between software programs. It helps overcome challenges such as doctrinal differences, lack of standardization, and complexity of physical infrastructure and socio-economic interactions. By actively managing connections between systems and emphasizing their integration, interoperability facilitates the efficient completion of applications, the provision of adaptive services, and the sharing of data across diverse programs.
What the most researched IoT ontology for sensors?4 answersThe most researched IoT ontology for sensors is the one that focuses on adding semantic annotations to sensor data. This ontology enables more expressive data representation and supports knowledge discovery in IoT environments. Several ontologies have been proposed to handle different aspects of sensor data collection in IoT systems, ranging from sensor discovery to applying reasoning on collected sensor data for drawing inferences. These ontologies categorize the fundamental ontological concepts required for annotating different aspects of data collection and data access in an IoT application, such as sensors, context, location, and more. The use of semantic metadata and ontologies in IoT systems allows for the integration of diverse IoT systems and applications, solving challenges related to interoperability and heterogeneity.
What is the role of ontologies in AI and IoT smart buildings?5 answersOntologies play a critical role in data exchange, information integration, and knowledge sharing across diverse smart building applications. They facilitate data readability and reasoning by machines, which is important for smart and ongoing commissioning (SOCx) of buildings. Ontologies can improve IoT interoperability and facilitate the development of software applications for managing and monitoring different IoT installations in a generic and homogeneous way. In the context of IoT-enabled smart buildings, ontologies can ensure human safety during emergencies by collecting, processing, and communicating real-time data from IoT sensors embedded in the building. Ontologies also support ontology matching, alignment, and harmonization, which are important for integrating Linked Building Data (LBD). Overall, ontologies are essential for achieving data interoperability, improving operational performance, and reducing human life loss or injury in smart buildings.
What are the different IoT ontologies?4 answersThere are several IoT ontologies that have been proposed in the literature. One approach is to use a lightweight dynamic ontology that includes only the most important concepts and uses clustering techniques to provide dynamic semantics. Another approach is to implement three layers of interoperability: technical, syntactic, and semantic, with a focus on the semantic layer. The INTER-IoT project aims to address semantic interoperability by analyzing and selecting popular ontologies such as SSN, SAREF, oneM2M Base Ontology, IoT-Lite, and OpenIoT. Standardized ontologies for the Web of Things (WoT) have also been developed, covering different layers of the WoT architecture. Additionally, a set of ontologies has been proposed for information processing in IoT, including goal ontology, role ontology, constraint ontology, message ontology, status ontology, space-time ontology, and activity ontology.
What does interoperability mean?5 answersInteroperability refers to the ability of IoT systems and components to communicate and share information among them. It is the ability of heterogeneous systems to interact and exchange information efficiently and effectively through a planned process. Interoperability is generally understood as the ability of two or more systems to exchange information and make use of it. It is the ability of systems to work together either to collaboratively solve a common problem or to enable the work of one or the other system. While there are several definitions of interoperability, there are no formal theories of interoperability that capture what interoperability is as opposed to how it works and how to tell whether two or more systems can interoperate.