Semantic Web: Modeling and Ontologies

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Related lectures (32)

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Knowledge Inference

Explores knowledge inference, embedding techniques, and schema matching in data integration.

Information Extraction & Knowledge Inference

Explores information extraction, knowledge inference, taxonomy induction, and entity disambiguation.

Semantic Modelling: Tabular Data and RDF

Introduces semantic modelling through tabular data and RDF, covering relational databases, schema migration, future-proof schemata, SPARQL querying, and metaknowledge limitations.

Connecting the Dots in Circular Lifecycle Management

Explores Circular Lifecycle Management, Zero Defect Manufacturing, Big Data Analytics, and Predictive Maintenance in industrial processes.

Data, big data, clouds and IoT

Explores data representation, databases, cloud computing, and challenges in the cloud environment.

Data Wrangling with Hive: Managing Big Data Efficiently

Covers data wrangling techniques using Apache Hive for efficient big data management.

Closed-Loop Lifecycle Management

Explores Closed-Loop Lifecycle Management, Circular Economy, and Zero Defect Manufacturing strategies for sustainable development.

Metadata Ontologies and Brain Atlases

Explores metadata standards, the Gene Ontology, and brain atlases in neuroscience.

Understanding Big Data in Neuroscience

Delves into Big Data in neuroscience, analyzing large datasets and addressing challenges in data organization, standardization, integration, and visualization.

Semantic Web Resources

Explores popular ontologies and knowledge bases like WordNet, WikiData, Google Knowledge Graph, and Schema.org, as well as Linked Open Data sets.