From the Development to the Evaluation of the MOTunAr Ontology

Authors

  • Haifa Degachi MIRACL, University of Sfax, Tunisia
  • Yengui Ameni MIRACL, University of Sfax, Tunisia
  • Neji Mahmoud MIRACL, University of Sfax, Tunisia

Keywords:

Archaeology, Axioms, Concept, Ontology, Relations

Abstract

The focus of reasoning and interpreting in the knowledge engineering field is moving from ‘data processing’ to ‘concept processing’, it means that we focus more on the semantic aspects which are considered a significant challenge in the modern information system. Ontology is commonly considered as the solution which serves as a representative of the semantics of any domain. In the archaeological field, the gathered data dispersed a significant set of incoherent and heterogeneous sources (e.g., excavation reports, archives, etc.) and appear in various formats and may be uniquely accessed over broken mode since given than the joining between recording data is insufficient. In the area of the Tunisian archaeological field, heterogeneity is a dominant characteristic so that ontologies present an efficient solution to the semantic heterogeneity issue.  Our ongoing research is oriented to develop a multimedia ontology of the Tunisian archaeological field. This ontology aims to describe the whole Tunisian archaeological sites. We profited from the different available sources that describe this domain. The development of the MOTunAr ontology will be realized in 6 steps. The principal ones will be detailed in this paper. MOWL will be used as a knowledge representation language that permits us to represent the multimedia knowledge used in our experiments.

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References

D. Haifa, Y. Ameni, and N. Mahmoud, “Accomplishment of multimedia ontology for the tunisian archaeology field,” in Advances in Intelligent Systems and Computing, vol. 1184, Springer Science and Business Media Deutschland GmbH, 2021, pp. 64–72.

D. Haifa, Y. Ameni, and N. Mahmoud, “Multimedia Ontology of the Tunisian Archaeology Field,” in Advances in Intelligent Systems and Computing, Jul. 2020, vol. 1105 AISC, pp. 321–330, doi: 10.1007/978-3-030-36674-2_33.

T. R. Gruber, “Toward principles for the design of ontologies used for knowledge sharing,” Int. J. Hum. - Comput. Stud., vol. 43, no. 5–6, pp. 907–928, Nov. 1995, doi: 10.1006/ijhc.1995.1081.

C. Niang et al., “Supporting semantic interoperability in conservation-restoration domain: The PARCOURS project,” J. Comput. Cult. Herit., vol. 10, no. 3, pp. 1–20, Jul. 2017, doi: 10.1145/3097571.

T. Messaoudi, sous la direction de L. De Luca, P. Véron, and G. Halin, “Vers une ontologie de domaine pour l’analyse de l’état de conservation du bâti patrimonialTowards an ontology for the analysis of the conservation status of a heritage building,” Situ, no. 39, Jul. 2019, doi: 10.4000/insitu.22470.

O. P. Zalamea Patino, J. Van Orshoven, and T. Steenberghen, “Merging and expanding existing ontologies to cover the Built Cultural Heritage domain,” J. Cult. Herit. Manag. Sustain. Dev., vol. 8, no. 2, pp. 162–178, Jun. 2018, doi: 10.1108/JCHMSD-05-2017-0028.

C. S. Gray and S. J. Watson, “Physics of failure approach to wind turbine condition based maintenance,” Wind Energy, vol. 13, no. 5, pp. 395–405, Jul. 2010, doi: 10.1002/WE.360.

M. Doerr, “The CIDOC CRM, an Ontological Approach to Schema Heterogeneity,” undefined, 2005.

M. Gergatsoulis, L. Bountouri, P. Gaitanou, and C. Papatheodorou, “Mapping cultural metadata schemas to CIDOC conceptual reference model,” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2010, vol. 6040 LNAI, pp. 321–326, doi: 10.1007/978-3-642-12842-4_37.

C. Niang, C. Marinica, É. Leboucher, L. Bouiller, and C. Capderou, “An ontological model for conservation-restoration of cultural objects,” in 2015 Digital Heritage International Congress, Digital Heritage 2015, 2015, pp. 157–160, doi: 10.1109/DigitalHeritage.2015.7419476.

P. Chevalier, L. Granjon, É. Leclercq, A. Millereux, M. Savonnet, and C. Sapin, “Database Wiki annotated the corpus digital CARE,” Hortus Artium Mediaev., vol. 18, no. 1, pp. 27–35, Nov. 2012, doi: 10.1484/J.HAM.1.102782.

A. Mallik and S. Chaudhury, “Using concept recognition to annotate a video collection,” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Dec. 2009, vol. 5909 LNCS, pp. 507–512, doi: 10.1007/978-3-642-11164-8_82.

C. Chrisment, O. Haemmerlé, N. Hernandez, and J. Mothe, “Méthodologie de transformation d’un thesaurus en une ontologie de domaine,” Rev. d’Intelligence Artif., vol. 22, no. 1, pp. 7–37, 2008, doi: 10.3166/ria.22.7-37.

A. L. Rector, “Modularisation of domain ontologies implemented in description logics and related formalisms including OWL,” in Proceedings of the 2nd International Conference on Knowledge Capture, K-CAP 2003, Oct. 2003, pp. 121–128, doi: 10.1145/945645.945664.

A. Mallik and S. Chaudhury, “Acquisition of multimedia ontology: an application in preservation of cultural heritage,” Int. J. Multimed. Inf. Retr., vol. 1, no. 4, pp. 249–262, Dec. 2012, doi: 10.1007/s13735-012-0021-5.

A. Mallik, H. Ghosh, S. Chaudhury, and G. Harit, “MOWL: An ontology representation language for web-based multimedia applications,” ACM Trans. Multimed. Comput. Commun. Appl., vol. 10, no. 1, pp. 1–21, Dec. 2013, doi: 10.1145/2542205.2542210.

B. Villazón-Terrazas, M. C. Suárez-Figueroa, and A. Gómez-Pérez, “A pattern-based method for re-engineering non-ontological resources into ontologies,” Int. J. Semant. Web Inf. Syst., vol. 6, no. 4, pp. 27–63, Oct. 2010, doi: 10.4018/jswis.2010100102.

D. Soergel, B. Lauser, A. Liang, F. Fisseha, J. Keizer, and S. Katz, “Reengineering Thesauri for New Applications: the AGROVOC Example.”

D. Haifa, Y. Ameni, and N. Mahmoud, “Towards a Multimedia Ontology for Tunisian Archaeology Field,” Dec. 2019, doi: 10.1109/ICTA49490.2019.9144900.

J. J. f. Deetz, “Households: A Structural Key to Archaeological Explanation,” Am. Behav. Sci., vol. 25, no. 6, pp. 717–724, 1982, doi: 10.1177/000276482025006009.

M. S. Hobson, “EAMENA training in the use of satellite remote sensing and digital technologies in heritage management: Libya and Tunisia workshops 2017-2019,” Libyan Studies, vol. 50. Cambridge University Press, pp. 63–71, Nov. 01, 2019, doi: 10.1017/lis.2019.22.

M. P. Sullivan and A. Venter, “The Hero Within: Inclusion of Heroes into the Self,” Self Identity, vol. 4, no. 2, pp. 101–111, Apr. 2005, doi: 10.1080/13576500444000191.

F. Z. Smaili, X. Gao, and R. Hoehndorf, “OPA2Vec: combining formal and informal content of biomedical ontologies to improve similarity-based prediction,” 2018, doi: 10.1093/bioinformatics/xxxxxx.

A. Mathews, S. Chen, M. T. Bigham, and K. Mansel, “Oops: rapid Deterioration of the Transport Patient Admitted to the General Care Floor,” Pediatrics, vol. 141, no. 1 MeetingAbstract, pp. 728–728, Jan. 2018, doi: 10.1542/PEDS.141.1_MEETINGABSTRACT.728.

J.-P. Goulette, “Sémantique formelle de l’espace. Application au raisonnement spatial qualitatif en architecture,” Intellectica. Rev. l’Association pour la Rech. Cogn., vol. 29, no. 2, pp. 9–34, 1999, doi: 10.3406/intel.1999.1584.

S. Ferré, “Concepts de plus proches voisins dans des graphes de To cite this version : HAL Id : hal-01570277 Concepts de plus proches voisins dans des graphes de connaissances,” 2017.

S. Baghernezhad-Tabasi et al., “IOPE: Interactive Ontology Population and Enrichment,” 2021, Accessed: Mar. 16, 2022. [Online]. Available: https://protege.stanford.edu.

G. Petasis, V. Karkaletsis, G. Paliouras, A. Krithara, and E. Zavitsanos, “Ontology population and enrichment: State of the art,” Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics), vol. 6050, pp. 134–166, 2011, doi: 10.1007/978-3-642-20795-2_6.

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Published

2022-04-01

How to Cite

Degachi, H., Ameni, Y. ., & Mahmoud, N. . (2022). From the Development to the Evaluation of the MOTunAr Ontology. International Journal of Computer Engineering and Data Science (IJCEDS), 2(1), 1–16. Retrieved from https://ijceds.com/ijceds/article/view/31