Big data and semantic web, challenges and opportunities a survey

  • Authors

    • Jeelani Ahmed
    • Dr. Muqeem Ahmed
    2018-09-22
    https://doi.org/10.14419/ijet.v7i4.5.21174
  • Big Data, Semantics Web, Ontologies.

  • Abstract

    In recent years, vast and complex amounts of data are being created and making it difficult for traditional data processing applications to manage them. The coming of the Internet prompted monstrous spike in the volume of information being made and made accessible. World Wide Web consortium W3C and international standardization body of the web spread the Semantic Web. It is an extended form of current web which provide easier way to search, reuse, combine and share information. In the last few years, major businesses corporations have demonstrated interest in incorporating semantic web technology with big data for added value. Indeed this incorporation has some benefits as well; it increases end-users ability to self-manage data from various sources, it on focuses changing business environments and varying user needs and handles concepts and relationships, manages terminology while connecting different data from varied data sources. For Social Network Analysis (SNA) new methods are needed by combining Big Data and Semantic Web technologies as a way to utilize and add capacities to existing frameworks. Moreover, the fast changing business requirements and latest industry culture of Agile Development needs a robust yet flexible solution for Business Intelligence and by using distributed enterprise level ontologies Data Warehousing can be incorporated. This paper is an attempt to focus on effects of incorporating Big Data with Semantic web, how Semantic Web making Big Data smarter, revisit the Big Data and Semantic Web challenges and opportunities, relationship between them and finally we summarizes with future direction of this integration

     

  • References

    1. [1] K. Davis, D. Patterson, Ethics of Big Data: Balancing Risk and Innovation, O’Reilly Media, 2012.

      [2] Li Kang, Li Yi, LIU Dong, “Research on Construction Methods of Big Data Semantic Modelâ€, World Congress on Engineering 2014 Vol I, WCE 2014.

      [3] Qudamah Quboa and Nikolay Mehandjiev, “Creating Intelligent Business Systems by Utilizing Big Data and Semanticsâ€, IEEE 19th Conference on Business Informatics, Volume 2, 39-46, 2017.

      [4] G. Halevi, H. Moed, The evolution of big data as a research and scientific topic: Overview of the literature, Res. Trends (2012) 3–6.

      [5] Boris Mocialov, “Big Data Management Assessed Coursework Two Big Data vs Semantic Webâ€, Heriot-Watt University, Edinburgh, April 5, 2015.

      [6] David Ostrowski, Nestor Rychtyckyj, Perry MacNeille and Mira Kim,“Integration of Big Data Using Semantic Web Technologies†IEEE Tenth International Conference on Semantic Computing, 382-385, 2016.

      [7] Srividya K Bansal (2014), “Towards a Semantic Extract-Transform-Load (ETL) framework for Big Data Integrationâ€, IEEE International Congress on Big Data, 2014.

      [8] Olivier Cur´e, Fadhela Kerdjoudj, Chan Le Duc and Myriam Lamolle, “On the Potential Integration of an Ontology-Based Data Access Approach in NoSQL Storesâ€, Third International Conference on Emerging Intelligent Data and Web Technologies, 166-173, 2012.

      [9] Srividya K Bansal and Sebastian Kagemann, “Integrating Big Data: A Semantic Extract-Transform-Load Framework†IEEE Computer Society,Volume 48, Issue 3, 42-50, 2015.

      [10] Li Ma, Jing Mei, Yue Pan Krishna Kulkarni Achille Fokoue and Anand Ranganathan, “Semantic Web Technologies and Data Managementâ€, IBM China Research Laboratory, 2007.

      [11] Ivan Merelli, Horacio Pérez-Sánchez, Sandra Gesing and Daniele D’Agostino, “Managing, Analysing, and Integrating Big Data in Medical Bioinformatics: Open Problems and Future Perspectivesâ€, BioMed Research International, Volume 2014, Article ID 134023, 13 pages, 2014.

      [12] Maryam Panahiazar, Vahid Taslimitehrani, Ashutosh Jadhav, Jyotishman Pathak, “Empowering Personalized Medicine with Big Data and Semantic Web Technology: Promises, Challenges, and Use Casesâ€, IEEE International Conference on Big Data, [Online] 978-1-4799-5666-1, 2014.

      [13] Bastian Eine, Matthias Jurisch, and Werner Quint (2017), “Ontology-Based Big Data Managementâ€, System, 5, 45, 1-14, 2017

      [14] Jing Xiong, Yuntong Liu and Wei Liu (2014), “Ontology-based Integration and Sharing of Big Data Educational Resourcesâ€, 11th Web Information System and Application Conference, 245-248, 2014.

      [15] Loukia Karanikola, Isambo Karali and Sally McClean (2014), “Uncertainty reasoning for the Big Data Semantic Webâ€, IEEE 15th International Conference on Information Reuse and Integration, 147 – 154, 2014.

      [16] Knoblock, Craig & Szekely, Pedro (2015), Exploiting Semantics for Big Data Integration. AI Magazine. 36. 25-38.

      [17] Gary E. Marshall, Paul A Tibbits (2016), “Data Integration with Semantic Web Technologies (SWT)â€, office of technology strategies (TS), office of information and technology (OI&T), Version 1.0, 2016.

      [18] C.Kacfah Emani, et al., Understandable Big Data: A Survey, Computer Science Review (2015), http://dx.doi.org/10.1016/j.cosrev.2015.05.002.

      [19] Zhang, J., & Huang, M. L. (2013, December). 5Ws model for big data analysis and visualization. In Computational Science and Engineering (CSE), 2013 IEEE 16th International Conference on (pp. 1021-1028). IEEE.

      [20] C.A. Knoblock, and P. Szekely, “Exploiting semantics for Big Data integration,†AI Magazine, vol. 36(1), pp. 25-39, 2015.

      [21] J.F. Sánchez-Rada, M. Torres, C.A. Iglesias, R. Maestre, and E. Peinado, “A Linked Data approach to sentiment and emotion analysis of twitter in the financial domain,†Proceedings of the Second International Workshop on Finance and Economics on the Semantic Web (FEOSW 2014), Anissaras, Crete, Greece. 26th May 2014, pp.51-62, 2014.

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  • How to Cite

    Ahmed, J., & Muqeem Ahmed, D. (2018). Big data and semantic web, challenges and opportunities a survey. International Journal of Engineering & Technology, 7(4.5), 631-633. https://doi.org/10.14419/ijet.v7i4.5.21174

    Received date: 2018-10-07

    Accepted date: 2018-10-07

    Published date: 2018-09-22