%0 Conference Paper %1 Alexiev2013-CRM-reasoning %A Alexiev, Vladimir %A Manov, Dimitar %A Parvanova, Jana %A Petrov, Svetoslav %B Workshop Practical Experiences with CIDOC CRM and its Extensions (CRMEX 2013) at TPDL 2013 %C Valetta, Malta %D 2013 %I CEUR WS %K CIDOC_CRM Fundamental_Relations GraphDB ResearchSpace cultural_heritage inference ontology performance semantic_repository semantic_search %T Large-scale Reasoning with a Complex Cultural Heritage Ontology (CIDOC CRM) %U http://ceur-ws.org/Vol-1117/paper8.pdf %V 1117 %X The CIDOC Conceptual Reference Model (CRM) is an important ontology in the Cultural Heritage (CH) domain. CRM is intended mostly as a data integration mechanism, allowing reasoning and discoverability across diverse CH sources represented in CRM. CRM data comprises complex graphs of nodes and properties. An important question is how to search through such complex graphs, since the number of possible combinations is staggering. One answer is the "Fundamental Relations" (FR) approach that maps whole networks of CRM properties to fewer FRs, serving as a "search index" over the CRM semantic web. We present performance results for an FR Search implementation based on OWLIM. This search works over a significant CH dataset: almost 1B statements resulting from 2M objects of the British Museum. This is an exciting demonstration of large-scale reasoning with real-world data over a complex ontology (CIDOC CRM). We present volumetrics, hardware specs, compare the numbers to other repositories hosted by Ontotext, performance results, and compare performance of a SPARQL implementation.

@inproceedings{Alexiev2013-CRM-reasoning, abstract = {The CIDOC Conceptual Reference Model (CRM) is an important ontology in the Cultural Heritage (CH) domain. CRM is intended mostly as a data integration mechanism, allowing reasoning and discoverability across diverse CH sources represented in CRM. CRM data comprises complex graphs of nodes and properties. An important question is how to search through such complex graphs, since the number of possible combinations is staggering. One answer is the "Fundamental Relations" (FR) approach that maps whole networks of CRM properties to fewer FRs, serving as a "search index" over the CRM semantic web. We present performance results for an FR Search implementation based on OWLIM. This search works over a significant CH dataset: almost 1B statements resulting from 2M objects of the British Museum. This is an exciting demonstration of large-scale reasoning with real-world data over a complex ontology (CIDOC CRM). We present volumetrics, hardware specs, compare the numbers to other repositories hosted by Ontotext, performance results, and compare performance of a SPARQL implementation.}, added-at = {2021-08-25T16:07:36.000+0200}, address = {Valetta, Malta}, author = {Alexiev, Vladimir and Manov, Dimitar and Parvanova, Jana and Petrov, Svetoslav}, biburl = {https://www.bibsonomy.org/bibtex/2b997b758886d6ddb8908a8140149399c/valexiev}, booktitle = {Workshop Practical Experiences with CIDOC CRM and its Extensions (CRMEX 2013) at TPDL 2013}, interhash = {59c6f2620f93d716d04e930d444b7e59}, intrahash = {b997b758886d6ddb8908a8140149399c}, keywords = {CIDOC_CRM Fundamental_Relations GraphDB ResearchSpace cultural_heritage inference ontology performance semantic_repository semantic_search}, month = sep, publisher = {CEUR WS}, timestamp = {2021-08-25T16:07:36.000+0200}, title = {{Large-scale Reasoning with a Complex Cultural Heritage Ontology (CIDOC CRM)}}, url = {http://ceur-ws.org/Vol-1117/paper8.pdf}, url_ppt = {http://rawgit2.com/VladimirAlexiev/my/master/pubs/Alexiev2013-CRM-reasoning-slides.ppt}, url_preprint = {http://rawgit2.com/VladimirAlexiev/my/master/pubs/Alexiev2013-CRM-reasoning.pdf}, url_slides = {https://www.slideshare.net/valexiev1/largescale-reasoning-with-a-complex-cultural-heritage-ontology-cidoc-crm-slides}, volume = 1117, year = 2013 }