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Issue No.06 - Nov.-Dec. (2013 vol.28)
pp: 6-11
Payam Barnaghi , University of Surrey
Amit Sheth , Wright State University
Cory Henson , Wright State University
Extending the current Internet and providing connection, communication, and internetworking between devices and physical objects, or "things," is a growing trend that's often referred to as the Internet of Things (IoT). Integrating real-world data into the Web, with its large repositories of data, and providing Web-based interactions between humans and IoT resources is what the Web of Things (WoT) stands for. Here, the guest editors describe the Big Data issues in the WoT, discuss the challenges of extracting actionable knowledge and insights from raw sensor data, and introduce the theme articles in this special issue.
Special issues and sections, Internet of Things, Knowledge management, Web and internet services, Big Data,intelligent systems, Internet of Things, Web of Things, IoT, WoT, internetworking, Big Data
Payam Barnaghi, Amit Sheth, Cory Henson, "From Data to Actionable Knowledge: Big Data Challenges in the Web of Things [Guest Editors' Introduction]", IEEE Intelligent Systems, vol.28, no. 6, pp. 6-11, Nov.-Dec. 2013, doi:10.1109/MIS.2013.142
1. A. Sheth, C. Henson, and S. Sahoo, “Semantic Sensor Web,” IEEE Internet Computing, vol. 12, no. 4, 2008, pp. 78-83.
2. A. Sheth, P. Anantharam, and C. Henson, “Physical-Cyber-Social Computing: An Early 21st Century Approach,” IEEE Intelligent Systems, vol. 28, no. 1, 2013, pp. 79-82.
3. K. Thirunarayan and A. Sheth, “Semantics-Empowered Approaches to Big Data Processing for Physical-Cyber-Social Applications,” Proc. AAAI 2013 Fall Symp. Semantics for Big Data, AAAI, 2013; .
4. M. Compton et al, “The SSN Ontology of the W3C Semantic Sensor Network Incubator Group,” J. Web Semantics, vol 17, 2012, pp. 25-32.
5. L. Lefort et al., Semantic Sensor Network XG Final Report, W3C Incubator Group Report, 2011.
6. P. Barnaghi et al., “Semantics for the Internet of Things: Early Progress and Back to the Future,” Int’l J. Semantic Web and Information Systems, vol. 8, no. 1, 2012, pp. 1-21; doi:10.4018jswis.2012010101.
7. A. Bolles, M. Grawunder, and J. Jacobi, “Streaming SPARQL—Extending SPARQL to Process Data Streams,” The Semantic Web: Research and Applications, LNCS 5021, Springer, 2008, pp. 448-462.
8. D. Anicic et al., “EP-SPARQL: A Unified Language for Event Processing and Stream Reasoning,” Proc. World Wide Web Conf., ACM, 2011, pp. 635-644.
9. T. Kraska, “Finding the Needle in the Big Data Systems Haystack,” IEEE Internet Computing, vol. 17, no. 1, 2013, pp. 84-86.
10. C. Henson, K. Thirunarayan, and A. Sheth, “An Efficient Bit Vector Approach to Semantics-Based Machine Perception in Resource-Constrained Devices,” Proc. 11th Int’l Semantic Web Conf., LNCS 7649, Springer, 2012, pp. 479-164.
11. H.G. Miller, P. Mork, “From Data to Decisions: A Value Chain for Big Data,” IT Professional, vol. 15, no. 1, 2013, pp. 57-59.
12. S. Haller, “Linked Data Use and the Internet of Things,” Future Interent Assembly, presentation, 2011; http://goo.glxI4mD.
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