[Cryptography] SmartData 4.0: A formalization framework for big data and smart assets

morteza.javan at yahoo.com morteza.javan at yahoo.com
Fri Jan 25 03:47:55 EST 2019


 World Wide Web is one of the main sources of big data. Billions of people, devices, and applications are connected to the Internet and have read–write access to the web. The use of the web as a platform for delivering data has been driven by many technologies; promoting Web 2.0, more and more web applications provide a means of accessing data. It contains silos of data, which needs big computing and processing resources to build services like search engines or social networks. Emerging Web 3.0 and Semantic Web converts traditional web to a smarter web. Linked Data is main driver for the Semantic Web which tries to link (raw) data together. It is growing rapidly since 2006 and is altering research, governments, and industry by this realization that data is a key research enabler that inspires novel theoretical and foundational research questions

SmartData 4.0 has contributed to this area by providing: (1) A formal language for big data problems and solutions and (2) A framework to mathematically integrating data behaviors and data models into the Web of Data. It is possible to develop Intelligent Agents which have perfect sense of the world, dynamically understand the facts and fully interact with the things, which form the next generation of smart applications and smart services.

SmartData 4.0 has described by Smart Data Description Framework (SDF). It is a data object; it can be read, write, publish, reuse, and collect similar to Linked Data. Also it provides some techniques for measuring big data. For example, information theory is incorporated in the framework to measure the scale. The data needs to be well conform to the schema in order to be able to validate against the models. Also it is possible to use model metrics to improve productivity and quality during the model development life cycle. Metrics can be applied to the model design, model development, and model implementation process. The ability to measure the model provides a quantitative basis for its development and validation. A major difference between a “well-developed science” such as physics and some of the less “well-developed” sciences such as psychology or sociology is the degree to which things are measured.

SmartData 4.0 supports description of many simple relations and also complex formulations. In addition to basic Transformations and Fusion, still there are more operations which can be applied using SDF. For example, aligning the model and reality; bind them to processes; verify the behaviors; share the behaviors; discovery; version control; and staging are just some of elaborated ideas. For the future work, we intend to extend the research in some case studies of Anomaly Detection in Big Data. Also we are working on an agent-based design pattern for automatically deploying and scaling the Smart Data applications in the Cloud.

You can reed the full paper online or download it from the Journal of Supercomputing at Springer:
Regards,
Morteza.S.Javan


  
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