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Reseach Article

Using the Generalized World Entities (GWEs) Paradigm in a Semantic Web of Things (SWoT) Context

by Gian Piero Zarri
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 186 - Number 4
Year of Publication: 2024
Authors: Gian Piero Zarri
10.5120/ijca2024923392

Gian Piero Zarri . Using the Generalized World Entities (GWEs) Paradigm in a Semantic Web of Things (SWoT) Context. International Journal of Computer Applications. 186, 4 ( Jan 2024), 32-40. DOI=10.5120/ijca2024923392

@article{ 10.5120/ijca2024923392,
author = { Gian Piero Zarri },
title = { Using the Generalized World Entities (GWEs) Paradigm in a Semantic Web of Things (SWoT) Context },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2024 },
volume = { 186 },
number = { 4 },
month = { Jan },
year = { 2024 },
issn = { 0975-8887 },
pages = { 32-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume186/number4/33063-2024923392/ },
doi = { 10.5120/ijca2024923392 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:29:45.496018+05:30
%A Gian Piero Zarri
%T Using the Generalized World Entities (GWEs) Paradigm in a Semantic Web of Things (SWoT) Context
%J International Journal of Computer Applications
%@ 0975-8887
%V 186
%N 4
%P 32-40
%D 2024
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The Generalized World Entities (GWEs) paradigm is a proposal for introducing a semantic/conceptual dimension into the standard IoT procedures and supporting then the creation of a real Semantic Web of Things (SWoT). It is based on a substantial extension of the kind of entities to be considered within a sensor-monitored environment, by modelling in a unified way both physical entities like objects, humans, robots, etc. and higher levels of abstraction structures like situations, events, and behaviors. The unifying element is provided by an extended conceptual representation of the world, ontology based, that is used for modelling the GWEs of both types. NKRL (Narrative Knowledge Representation Language), a high-level tool grounded on two separated but integrated ontologies, an ontology of concepts and an ontology of elementary events, is utilized in this context.

References
  1. Comai, S., Finocchi, J., Fugini, M.G., Mastos, T., and Papadopoulos, A. 2022. Sharing Semantic Knowledge for Autonomous Robots: Cooperation for Social Robotic Systems. In Proc. of iiWAS 2022. Cham, Springer Nature LNCS 13635, pp. 1-15.
  2. Zarri, G.P. 2013. Generalized World Entities as a Unifying IoT Framework: A Case for the GENIUS Project. In Internet of Things and Inter-Cooperative Computational Technologies for Collective Intelligence. Berlin, Springer, pp. 345-367.
  3. Amarilli, F., Amigoni, F., Fugini, M.G., and Zarri, G.P. 2017. A Semantic-Rich Approach to IoT Using the Generalized World Entities Paradigm. In Managing the Web of Things, Linking the Real World to the Web. Cambridge (MA), Morgan Kaufmann Elsevier, pp. 105-147.
  4. Delin, K.A., and Jackson, S.P. 2001. The Sensor Web: A New Instrument Concept. SPIE’s Symposium on Integrated Optics, http://www.sensorwaresystems.com/historical/resources/sensorweb-concept.pdf (accessed December 10, 2023).
  5. Gibbons, P.B., Karp, B., Ke, Y., Nath, S., and Seshan, S. 2003, “IrisNet: An Architecture for a World-Wide Sensor Web”, IEEE Pervasive Computing 2(4), 22-33.
  6. Bröring, A., Echterhoff, J., Jirka, S., Simonis, I., Everding, T., Stasch, C., Liang, S., and Lemmens, R. 2011, “New Generation Sensor Web Enablement”, Sensors 11: 2652-2699.
  7. Sheth, A., Henson, C., and Sahoo, S. 2008, “Semantic Sensor Web”, IEEE Internet Computing 12(4), 78-83.
  8. Koubarakis, M., and Kyzirakos, K. 2010. Modeling and Querying Metadata in the Semantic Sensor Web: The Model stRDF and the Query Language stSPARQL. In Proc. of the 7th Extended Semantic Web Conference, ESWC-2010 (Part 1). Berlin, Springer LNCS 6088, pp. 425-439.
  9. Compton, M., Barnaghi, P., Bermudez, L., García-Castro, R., Corcho, O., and 17 additional Authors. 2012, “The SSN Ontology of the W3C Semantic Sensor Network Incubator Group”, Web Semantics 17, 25-32.
  10. Haller, A., Janowicz, K., Cox, S., Le Phuoc, D., Taylor, K., Lefrançois, M., and contributors. 2017. Semantic Sensor Network Ontology (W3C Recommendation 19 October 2017), https://www.w3.org/TR/vocab-ssn/ (accessed December 10, 2023).
  11. Russomanno, D.J., Kothari, C.R., and Thomas, O.A. 2005. Building a Sensor Ontology: A Practical Approach Leveraging ISO and OGC Models. In Proc. of the 2005 Int. Conference on Artificial Intelligence (ICAI). Athens (GA), CSRA Press, pp. 637-643.
  12. Compton, M., Neuhaus, H., Taylor, K., and Khoi-Nguyen Tran, K.-N. 2009. Reasoning about Sensors and Compositions. In Proc. of the 2nd Int. Workshop on Semantic Sensor Networks (SSN09), co-located with the 8th Int. SW Conference (ISWC-2009). Aachen, CEUR Workshop Proceedings (vol. 522), pp. 33-48.
  13. Janowicz, K., and Compton, M. 2010. The Stimulus-Sensor-Observation Ontology Design Pattern and its Integration into the Semantic Sensor Network Ontology. In Proc. of the 3rd Int. Workshop on Semantic Sensor Networks. Aachen, CEUR Workshop Proceedings (vol. 668), pp. 64-78.
  14. Bermudez-Edo, M., Elsaleh, T., Barnaghi, P., and Taylor, K. 2015. IoT-Lite Ontology (W3C Member Submission 26 November 2015), https://www.w3.org/Submission/iot-lite/ (accessed December 10, 2023).
  15. Gyrard, A., Datta, S.K., Bonnet, C., and Boudaoud, K. 2015. Cross-Domain Internet of Things Application Development: M3 Framework and Evaluation. In Proc. of the 3rd Int. Conference on Future Internet of Things and Cloud. New York, IEEEXplore, pp. 9-16.
  16. Haller, A., Janowicz, K., Cox, S., Le Phuoc, D., Taylor, K., Lefrançois, M., and contributors. 2017. Semantic Sensor Network Ontology (W3C Recommendation 19 October 2017), https://www.w3.org/TR/vocab-ssn/ (accessed December 10, 2023).
  17. Janowicz, K., Haller, A., Cox, S.J.D., Le Phuoc, D., and Lefrançois, M. 2018, “SOSA: A Lightweight Ontology for Sensors, Observations, Samples, and Actuators”, Journal of Web Semantics 56 (May 2019), 1-10.
  18. Elsaleh, T., Bermudez-Edo, M., Enshaeifar, S., Acton, S.T., Rezvani, R., and Barnaghi, P. 2019. IoT-Stream: A Lightweight Ontology for Internet of Things Data Streams. In Proc. of the 2019 Global IoT Summit (GIoTS). New York, IEEEXplore, pp. 135-140.
  19. Daniele, L., den Hartog, F., and Roes, J. 2015. Assets for Smart Appliances Interoperability (D-S4: Final Report). The Hague, Netherlands Organization for Applied Scientific Research (TNO).
  20. Daniele, L. 2020. SAREF4ENER: An Extension of SAREF for the Energy Domain, Created in Collaboration with Energy@Home and EEBus Associations. Valbonne, European Telecommunications Standards Institute (ETSI), https://saref.etsi.org/saref4ener/v1.1.2/ (accessed December 10, 2023).
  21. Bassi, A., Bauer, M., Fiedler, M., Kramp, T., van Kranenburg, R., Lange, S., and Meissner, S., eds. 2013. Enabling Things to Talk – Designing IoT Solutions with the IoT Architectural Reference Model. Berlin, Springer.
  22. Bauer, M., Bui, N., De Loof, J., Magerkurth, C., Nettsträter, A., Stefa, J., and Walewski, J.W. 2013. IoT Reference Model. In Enabling Things to Talk – Designing IoT Solutions with the IoT Architectural Reference Model. Berlin, Springer, pp. 113-162.
  23. De, S., Barnaghi, P., Bauer, M., and Meissner, S. 2011. Service Modelling for the Internet of Things. In Proc. of the 2011 Federated Conference on Computer Science and Information Systems – 3rd Workshop on Semantic-Based Software Services. Los Alamitos (CA), IEEE Computer Society Press, pp. 949-956.
  24. Serrano, M., Gyrard, A., Boniface, M., Grace, P., et al. 2017. Cross-Domain Interoperability Using Federated Interoperable Semantic IoT/Cloud Testbeds and Applications: The FIESTA-IoT Approach. In Serrano, M., et al., eds., Building the Future Internet through FIRE. Aalborg, River Publishers, pp. 287-321.
  25. Desai, P., Sheth, A., and Anantharam, P. (2015). Semantic Gateway as a Service Architecture for IoT Interoperability. In Proc. of the 2015 IEEE Int. Conference on Mobile Services. New York: IEEEXplore, pp. 313-319.
  26. Patni, H.K., Henson, C.A., and Sheth, A.P. 2010. Linked Sensor Data. In Proc. of the 2010 Int. Symposium on Collaborative Technologies and Systems. New York, IEEEXplore, pp. 362-370.
  27. Barnaghi, P., Wang, W., Henson, C. A., and Taylor, K. 2012, “Semantics for the Internet of Things: Early Progress and Back to the Future”, Int. Journal on Semantic Web and Information Systems 8(1), 1-21.
  28. Barnaghi, P., Presser, M., and Moessner, K. 2010. Publishing Linked Sensor Data. In Proc. of the 3rd Int. Workshop on Semantic Sensor Networks (SSN10), co-located with ISWC 2010. Aachen, CEUR Workshop Proceedings (vol. 468), pp. 4-19.
  29. Jain, P., Hitzler, P., Yeh, P.Z., Verma, K., and Sheth, A.P. 2010. Linked Data Is Merely More Data. In Proc. of the 2010 AAAI Spring Symposium – Workshop No. 7: Linked Data Meets Artificial Intelligence. Palo Alto (CA), AAAI.
  30. Bernstein, A., Hendler, J., and Noy, N. 2016, “A New Look at the Semantic Web”, Communications of the ACM 59(9), 35-37.
  31. Trame, J., Kessler, C., and Kuhn, W. 2013. Linked Data and Time – Modeling Researcher Life Lines by Events. In Proc. of the 11th Int. Conference on Spatial Information Theory (COSIT 2013.) Berlin, Springer LNCS 8116, pp. 205-223.
  32. Zarri, G.P. 2009. Representation and Management of Narrative Information, Theoretical Principles and Implementation. London, Springer.
  33. Zarri, G.P. 2019, “Functional and Semantic Roles in a High-Level Knowledge Representation Language”, Artificial Intelligence Review 51(4), 537-575.
Index Terms

Computer Science
Information Sciences

Keywords

Semantic Web of Things (SWoT) Generalized World Entities (GWEs) Narrative Knowledge Representation Language (NKRL) ontology of standard concepts ontology of dynamic events inference procedures examples of actual GWEs.