publication . Conference object . 2019

OpenArchaeo for Usable Semantic Interoperability

Marlet , Olivier; Francart, Thomas; Markhoff, Béatrice; Rodier, Xavier;
English
  • Published: 03 Jun 2019
  • Publisher: HAL CCSD
  • Country: France
Abstract
International audience; CIDOC CRM is an ontology intended to facilitate the integration, mediation and interchange of heterogeneous cultural heritage information. The Semantic Web with its Linked Open Data cloud enables scholars and cultural institutions to publish their data in RDF, using CIDOC CRM as an interlingua that enables a semantically consistent re-interpretation of their data. Nowadays more and more projects have done the task of mapping legacy datasets to CIDOC CRM, and successful Extract-Transform-Load data-integration processes have been performed in this way. A next step is enabling people and applications to actually dynamically explore autonomou...
Subjects
free text keywords: Semantic Interoperability, Visual Querying, CIDOC CRM, [INFO.INFO-WB]Computer Science [cs]/Web, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], [SHS.ARCHEO]Humanities and Social Sciences/Archaeology and Prehistory
Related Organizations
Funded by
EC| ARIADNEplus
Project
ARIADNEplus
Advanced Research Infrastructure for Archaeological Data Networking in Europe - plus
  • Funder: European Commission (EC)
  • Project Code: 823914
  • Funding stream: H2020 | RIA
Communities
DARIAH EU
Digital Humanities and Cultural HeritageDH-CH Projects: ARIADNEplus

1. Oldman D., Tanase D. Reshaping the Knowledge Graph by Connecting Researchers, Data and Practices in ResearchSpace. In: Vrandečić D. et al. (eds) The Semantic Web - ISWC 2018. LNCS, vol 11137. pp. 325-340. Springer, Cham (2018). [OpenAIRE]

2. Marlet, O., Curet, S., Rodier, X., Markhoff, B. Using CIDOC CRM for dynamically querying ArSol, a relational database, from the semantic web. In: Campana, S., et al. (eds) CAA 2015 Keep the revolution going. pp. 241-250. Archaeopress Archaeology, Oxford (2016).

3. Soylu, A., Giese, M., Jimenez-Ruiz, E. et al. Ontology-based End-user Visual Query Formulation: Why, What, Who, How, and Which?. Univ Access Inf Soc (2017) 16: 435. https://doi.org/10.1007/s10209-016-0465-0

4. Doerr, M., Iorizzo, D. The dream of a global knowledge network - a new approach. J. Comput. Cult. Herit. 1(1), 5:1-5:23 (2008).

5. Felicetti A., Gerth P., Meghini C., Theodoridou M. Integrating heterogeneous coin datasets in the context of archaeological research. In Proc. of the Workshop on Extending, Mapping and Focusing the CRM, co-located with 19th ICTPDL conference, p. 13-27. CEUR-WS.org (2015). [OpenAIRE]

6. Niang, X., Marinica, C., Markhoff, B., Leboucher, E., Laissus, F., Malavergne, O., Bouiller, L., Darrieumerlou, C., Capderou, C. Supporting Semantic Interoperability in Conservation-Restoration domain the PARCOURS project. ACM Journal on Computing and Cultural Heritage (JOCCH) - Special Issue on Digital Infrastructure for Cultural Heritage 10, 16 (2017). [OpenAIRE]

7. Calvanese, D., Liuzzo, P., Mosca, A., Remesal, J., Rezk, M., Rull, G. Ontology Based Data Integration in EPNet: production and distribution of food during the Roman Empire. Eng. Appl. Artif. Intell. 51, 212-229 (2016).

8. Ozsu, M.T.: A survey of RDF data management systems. Front. Comput. Sci. 10(3), p. 418-432 (2016). [OpenAIRE]

9. Saleem M., Potocki A., Soru T., Hartig O., and Ngonga Ngomo A. C. CostFed: Cost-Based Query Optimization for SPARQL Endpoint Federation. SEMANTICS 2018, p. 163-174 (2018).

10. Schwarte, A., Haase, P., Hose, K., Schenkel, R., Schmidt, M.: FedX: optimization techniques for federated query processing on linked data. In: Aroyo et al. (eds.) ISWC 2011. LNCS, vol. 7031, pp. 601-616. Springer, Heidelberg (2011). [OpenAIRE]

Abstract
International audience; CIDOC CRM is an ontology intended to facilitate the integration, mediation and interchange of heterogeneous cultural heritage information. The Semantic Web with its Linked Open Data cloud enables scholars and cultural institutions to publish their data in RDF, using CIDOC CRM as an interlingua that enables a semantically consistent re-interpretation of their data. Nowadays more and more projects have done the task of mapping legacy datasets to CIDOC CRM, and successful Extract-Transform-Load data-integration processes have been performed in this way. A next step is enabling people and applications to actually dynamically explore autonomou...
Subjects
free text keywords: Semantic Interoperability, Visual Querying, CIDOC CRM, [INFO.INFO-WB]Computer Science [cs]/Web, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], [SHS.ARCHEO]Humanities and Social Sciences/Archaeology and Prehistory
Related Organizations
Funded by
EC| ARIADNEplus
Project
ARIADNEplus
Advanced Research Infrastructure for Archaeological Data Networking in Europe - plus
  • Funder: European Commission (EC)
  • Project Code: 823914
  • Funding stream: H2020 | RIA
Communities
DARIAH EU
Digital Humanities and Cultural HeritageDH-CH Projects: ARIADNEplus

1. Oldman D., Tanase D. Reshaping the Knowledge Graph by Connecting Researchers, Data and Practices in ResearchSpace. In: Vrandečić D. et al. (eds) The Semantic Web - ISWC 2018. LNCS, vol 11137. pp. 325-340. Springer, Cham (2018). [OpenAIRE]

2. Marlet, O., Curet, S., Rodier, X., Markhoff, B. Using CIDOC CRM for dynamically querying ArSol, a relational database, from the semantic web. In: Campana, S., et al. (eds) CAA 2015 Keep the revolution going. pp. 241-250. Archaeopress Archaeology, Oxford (2016).

3. Soylu, A., Giese, M., Jimenez-Ruiz, E. et al. Ontology-based End-user Visual Query Formulation: Why, What, Who, How, and Which?. Univ Access Inf Soc (2017) 16: 435. https://doi.org/10.1007/s10209-016-0465-0

4. Doerr, M., Iorizzo, D. The dream of a global knowledge network - a new approach. J. Comput. Cult. Herit. 1(1), 5:1-5:23 (2008).

5. Felicetti A., Gerth P., Meghini C., Theodoridou M. Integrating heterogeneous coin datasets in the context of archaeological research. In Proc. of the Workshop on Extending, Mapping and Focusing the CRM, co-located with 19th ICTPDL conference, p. 13-27. CEUR-WS.org (2015). [OpenAIRE]

6. Niang, X., Marinica, C., Markhoff, B., Leboucher, E., Laissus, F., Malavergne, O., Bouiller, L., Darrieumerlou, C., Capderou, C. Supporting Semantic Interoperability in Conservation-Restoration domain the PARCOURS project. ACM Journal on Computing and Cultural Heritage (JOCCH) - Special Issue on Digital Infrastructure for Cultural Heritage 10, 16 (2017). [OpenAIRE]

7. Calvanese, D., Liuzzo, P., Mosca, A., Remesal, J., Rezk, M., Rull, G. Ontology Based Data Integration in EPNet: production and distribution of food during the Roman Empire. Eng. Appl. Artif. Intell. 51, 212-229 (2016).

8. Ozsu, M.T.: A survey of RDF data management systems. Front. Comput. Sci. 10(3), p. 418-432 (2016). [OpenAIRE]

9. Saleem M., Potocki A., Soru T., Hartig O., and Ngonga Ngomo A. C. CostFed: Cost-Based Query Optimization for SPARQL Endpoint Federation. SEMANTICS 2018, p. 163-174 (2018).

10. Schwarte, A., Haase, P., Hose, K., Schenkel, R., Schmidt, M.: FedX: optimization techniques for federated query processing on linked data. In: Aroyo et al. (eds.) ISWC 2011. LNCS, vol. 7031, pp. 601-616. Springer, Heidelberg (2011). [OpenAIRE]

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