Semantic Web Technologies

Part of the Studies in Computational Intelligence book series (SCI, volume 941)


The overarching aim of the Semantic Web is to allow computers to perform more valuable research and to construct structures that can facilitate reliable connections around the Network. Semantic Web applications help people to establish data stores on the Internet, build vocabulary, and compose data handling guidelines. Using the details of metadata, the semantic web recovers efficiently the web page user is searching for. Authors have introduced Semantic web, its development and technologies in brief, in this work. Provenance is the most crucial feature in for trustworthiness of semantic web. This feature is focused with the help of provenance data model. Authors discussed semantic web implementations such as semantic web desktop, geospatial semantic web etc. and their applications in different fields such as agriculture, healthcare, and IoT.


Linked open data Ontologies Resource description framework(RDF) Web ontology language (OWL) Provenance 


  1. 1.
  2. 2.
    Abelló, A., Romero, O., Pedersen, T.B., Berlanga, R., Nebot, V., Aramburu, M.J., Simitsis, A.: Using semantic web technologies for exploratory OLAP: a survey. IEEE Trans. Knowl. Data Eng. 27(2), 571–588 (2014)CrossRefGoogle Scholar
  3. 3.
    Feigenbaum, L., Herman, I., Hongsermeier, T., Neumann, E., Stephens, S.: The semantic web in action. Sci. Am. 297(6), 90–97 (2007)CrossRefGoogle Scholar
  4. 4.
    Breitman, K., Casanova, M. A., Truszkowski, W.: Semantic Web: Concepts, Technologies and Applications. Springer Science & Business Media (2007)Google Scholar
  5. 5.
  6. 6.
    Antoniou, G., van Harmelen, F.: A Semantic Web Primer, MIT Press. Cambridge, MA (2004)Google Scholar
  7. 7.
    Wang, X., Gorlitsky, R., Almeida, J.S.: From XML to RDF: how semantic web technologies will change the design of ‘omic’ standards. Nat. Biotechnol. 23(9), 1099 (2005)CrossRefGoogle Scholar
  8. 8.
    Berners-Lee, T.: Linked data-design issues. (2006)
  9. 9.
  10. 10.
    Pandey, M., Pandey, R.: Provenance linking using bundles in OWL ontology. Int. J. Comput. Appl. 975, 8887 (2017)Google Scholar
  11. 11.
    Pandey, M., Pandey, R., Darbari, M.: Provenance descriptions using the OWL functional syntax in Protégé. Int. J. Innov. Technol. Exploring Eng. (IJITEE), 8(8), 2421–2428 (2019)Google Scholar
  12. 12.
    Pandey, M., Pandey, R., Darbari, M.: Provenance use and its application in education domain using owl/XML syntax in Protégé. Int. J. Innov. Technol. Exploring Eng. (IJITEE) 8(9), 1037–1045 (2019)CrossRefGoogle Scholar
  13. 13.
    Shafiq, M.O., Ding, Y., Fensel, D.: Bridging multi agent systems and web services: towards interoperability between software agents and semantic web services. In: 2006 10th IEEE International Enterprise Distributed Object Computing Conference (EDOC’06), pp. 85–96. IEEE (2006, October)Google Scholar
  14. 14.
    Melesko, J., Kurilovas, E.: Personalised intelligent multi-agent learning system for engineering courses. In: 2016 IEEE 4th Workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE), pp. 1–6. IEEE (2016, November)Google Scholar
  15. 15.
    Stancheva, N.S., Popchev, I., Stoyanova-Doycheva, A., Stoyanov, S.: Automatic generation of test questions by software agents using ontologies. In: 2016 IEEE 8th International Conference on Intelligent Systems (IS), pp. 741–746. IEEE (2016, September)Google Scholar
  16. 16.
    Jilek, C., Schröder, M., Schwarz, S., Maus, H., Dengel, A.: Context spaces as the cornerstone of a near-transparent and self-reorganizing semantic desktop. In: European Semantic Web Conference, pp. 89–94. Springer, Cham (2018, June)Google Scholar
  17. 17.
    Janowicz, K., Hitzler, P.: Geospatial Semantic Web. Int. Encycl. Geogr. People Earth Environ. Technol. People Earth Environ. Technol. 1–6 (2016)Google Scholar
  18. 18.
    Nishanbaev, I., Champion, E., McMeekin, D.A.: A survey of geospatial semantic web for cultural heritage. Heritage 2(2), 1471–1498 (2019)CrossRefGoogle Scholar
  19. 19.
    Drury, B., Fernandes, R., Moura, M.F., de Andrade Lopes, A.: A survey of semantic web technology for agriculture. Inf. Process. Agric. 6(4), 487–501 (2019)Google Scholar
  20. 20.
    Mokgetse, T.L.: Need of ontology-based systems in healthcare system. Ontology-Based Inf. Retrieval Healthc. Syst. 257 (2020)Google Scholar
  21. 21.
    Shah, P., Thakkar, A.: Comparative analysis of semantic frameworks in healthcare. In Healthcare Data Analytics and Management, pp. 133–154. Academic Press (2019)Google Scholar
  22. 22.
    Al-Osta, M., Ahmed, B., Abdelouahed, G.: A lightweight semantic web-based approach for data annotation on IoT gateways. Procedia Comput. Sci. 113, 186–193 (2017)CrossRefGoogle Scholar
  23. 23.
    Soldatos, J., Kefalakis, N., Hauswirth, M., Serrano, M., Calbimonte, J. P., Riahi, M., Aberer, K., Jayaraman, P.P., Zaslavsky, A., Žarko, I.P., Skorin-Kapov, L.: Openiot: Open source internet-of-things in the cloud. In: Interoperability and Open-Source Solutions for the Internet of Things, pp. 13–25. Springer, Cham (2015)Google Scholar
  24. 24.
    Gyrard, A., Serrano, M.: Fiesta-iot: federated interoperable semantic internet of things (iot) testbeds and applications. In ICT (2015)Google Scholar
  25. 25.
    Honti, G.M., Abonyi, J.: A review of semantic sensor technologies in internet of things architectures. Complexity 2019 (2019)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2021

Authors and Affiliations

  1. 1.Sinhgad College of EngineeringPuneIndia
  2. 2.Vishwakarma Institute of Information TechnologyPuneIndia
  3. 3.Amity School of Engineering and Technology, Amity University RajasthanJaipurIndia

Personalised recommendations