Data Modeling and Knowledge Engineering for the Internet of Things
Document Type
Tutorial
Publication Date
10-8-2012
Abstract
This tutorial will focus on data modeling and knowledge engineering for the Internet of Things (IoT). It will discuss issues and challenges related to IoT data modeling and knowledge representation (e.g. modeling for constrained environments, complexity issues and time/location dependency of data) and will describe recent developments on creating annotation models and semantic description frameworks for IoT data (e.g. such as W3C Semantic Sensor Network ontology). The tutorial will review enabling technologies and common scenarios for IoT applications from the data and knowledge engineering point of view and will discuss information processing, reasoning and knowledge extraction as well as existing solutions related to these topics. The tutorial will also present state- of-the-art research and developments on IoT related ontology development, linked data, domain knowledge integration and management, querying large-scale IoT data, and AI applications for automated knowledge extraction from IoT data.
Repository Citation
Barnaghi, P.,
Henson, C. A.,
& Wang, W.
(2012). Data Modeling and Knowledge Engineering for the Internet of Things. The 18th International Conference on Knowledge Engineering and Knowledge Management (EKAW 2012).
https://corescholar.libraries.wright.edu/knoesis/223
Comments
Tutorial presented at the 18th International Conference on Knowledge Engineering and Knowledge Management (EKAW 2012), Galway City, Ireland, October 8-12, 2012.