A Review - From Data to Actionable Knowledge

Authors

  • Pinkal Shah  IT Department, Sigma Institute of engineering, Vadodara, Gujarat, India
  • Trilok Suthar  IT Department, Sigma Institute of engineering, Vadodara, Gujarat, India
  • Digvijaysinh Mahida  IT Department, Sigma Institute of engineering, Vadodara, Gujarat, India
  • Shivam Upadhyay  IT Department, Sigma Institute of engineering, Vadodara, Gujarat, India

Keywords:

Internet of Things, Data Analysis, Web of Things, Big Data

Abstract

Over the years, Speed of data generation has become very frequent and advanced technologies have provided more facilities to generate and gather data. These data are continuous and associated with many other things like decision making and data stream mining. Among multiple technologies Internet of Things (IoT) plays significant role in generating different types of data and make computational of data more challenging. In this paper, Extending the current technology providing connection and internetworking between devices and physical objects or "things," is a growing trend that's often referred to as the Internet of Things (IoT). Sharing real-world data into the Web, with its large sources of data, and providing Web-based interactions between humans and IoT object is what the Web of Things (WoT) stands for. Here, the Big Data issues in the WoT, discuss the challenges of extracting actionable data and insights from raw object data.

References

  1. A. Sheth, C. Henson, and S. Sahoo, “Semantic Sensor Web,” IEEE Internet Computing, vol. 12, no. 4, 2008, pp. 78–83.
  2. . 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; http://knoesis.org/library/download/ aaaiSemanticsAndBigData-TKP-ASPCS.pdf.
  3. 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.
  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:10.4018/ jswis.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. 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.

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Published

2018-04-10

Issue

Section

Research Articles

How to Cite

[1]
Pinkal Shah, Trilok Suthar, Digvijaysinh Mahida, Shivam Upadhyay, " A Review - From Data to Actionable Knowledge, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 5, pp.300-303, March-April-2018.