Abstract
With the terrific growth of data volume and data being produced every second on millions of devices across the globe, there is a desperate need to manage the unstructured data available on web pages efficiently. Semantic Web or also known as Web of Trust structures the scattered data on the Internet according to the needs of the user. It is an extension of the World Wide Web (WWW) which focuses on manipulating web data on behalf of Humans. Due to the ability of the Semantic Web to integrate data from disparate sources and hence makes it more user-friendly, it is an emerging trend. Tim Berners-Lee first introduced the term Semantic Web and since then it has come a long way to become a more intelligent and intuitive web. Data Visualization plays an essential role in explaining complex concepts in a universal manner through pictorial representation, and the Semantic Web helps in broadening the potential of Data Visualization and thus making it an appropriate combination. The objective of this chapter is to provide fundamental insights concerning the semantic web technologies and in addition to that it also elucidates the issues as well as the solutions regarding the semantic web. The purpose of this chapter is to highlight the semantic web architecture in detail while also comparing it with the traditional search system. It classifies the semantic web architecture into three major pillars i.e. RDF, Ontology, and XML. Moreover, it describes different semantic web tools used in the framework and technology. It attempts to illustrate different approaches of the semantic web search engines. Besides stating numerous challenges faced by the semantic web it also illustrates the solutions.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Aroma J, Kurian M (2012) A survey on need for semantic web. Int J Sci Res Publ 2(11). Coimbatore, India
Gopalachari MV, Sammulal P (2013) A survey on semantic web and knowledge processing. Int J Innov Res Comput Commun Eng 1(2). Hyderabad, India
Madhu G, Govardhan A, Rajinikanth TV (2011) Intelligent semantic web search engine. Int J Web Semant Technol 2(1). Hyderabad, India
Chitre N (2016) Semantic web search engine. Int J Adv Res Comput Sci Manag Stud 4(7). Pune, India
Bakshi R, Vijhani (2015) A semantic web-an extensive literature review. Int J Mod Trends Eng Res 2(8). Mumbai, India
Pandey G (2012) The semantic web. Int J Eng Res Appl 2(1). Gujarat, India
Bukhari SN, Mir2 JA, Ahmad U (2017) Study and review of recent trends in semantic web. Int J Adv Res Comput Sci Softw Eng 7(6). Jammu and Kashmir, India
Quboa QK, Saraee M (2013) A state of the art survey on semantic web mining. Intell Inf Manag 5(1). Salford, UK
Shabajee P (2006) Informed consent on the semantic web – issues for interaction and interface designer. In: Proceedings of the third international semantic web user interaction workshop, Athens, GA
Ishkey H, Harb HM, Farahat H (2014) A comprehensive semantic web survey. Al-Azhar Univ Eng J 9(1). Cairo, Egypt
Kathirvelu P Semantic web technology, layered architecture, RDF and OWL representation
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Singh, A., Sinha, U., Sharma, D.K. (2020). Semantic Web and Data Visualization. In: Hemanth, J., Bhatia, M., Geman, O. (eds) Data Visualization and Knowledge Engineering. Lecture Notes on Data Engineering and Communications Technologies, vol 32. Springer, Cham. https://doi.org/10.1007/978-3-030-25797-2_6
Download citation
DOI: https://doi.org/10.1007/978-3-030-25797-2_6
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-25796-5
Online ISBN: 978-3-030-25797-2
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)