% This data is distributed under the terms of the Open Data Commons Attribution License (ODC-By) v1.0 - See more at: http://opendatacommons.org/licenses/by/1-0/ @Article{OJSW_2015v2i1n03_Blasko, title = {Ontology Evolution Using Ontology Templates}, author = {Miroslav Blasko and Petr Kremen and Zdenek Kouba}, journal = {Open Journal of Semantic Web (OJSW)}, issn = {2199-336X}, year = {2015}, volume = {2}, number = {1}, pages = {16--29}, url = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194898}, urn = {urn:nbn:de:101:1-201705194898}, publisher = {RonPub}, bibsource = {RonPub}, abstract = {Evolving ontologies by domain experts is difficult and typically cannot be performed without the assistance of an ontology engineer. This process takes long time and often recurrent modeling errors have to be resolved. This paper proposes a technique for creating controlled ontology evolution scenarios that ensure consistency of the possible ontology evolution and give guarrantees to the domain expert that his/her updates do not cause inconsistency. We introduce ontology templates that formalize the notion of controlled evolution and define ontology template consistency checking service together with a consistency checking algorithm. We prove correctness and demonstate the practical use of the techniques in two scenarios.} } @Article{OJSW_2016v3i1n03_Smid, title = {OnGIS: Semantic Query Broker for Heterogeneous Geospatial Data Sources}, author = {Marek Smid and Petr Kremen}, journal = {Open Journal of Semantic Web (OJSW)}, issn = {2199-336X}, year = {2016}, volume = {3}, number = {1}, pages = {32--50}, url = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194936}, urn = {urn:nbn:de:101:1-201705194936}, publisher = {RonPub}, bibsource = {RonPub}, abstract = {Querying geospatial data from multiple heterogeneous sources backed by different management technologies poses an interesting problem in the data integration and in the subsequent result interpretation. This paper proposes broker techniques for answering a user's complex spatial query: finding relevant data sources (from a catalogue of data sources) capable of answering the query, eventually splitting the query and finding relevant data sources for the query parts, when no single source suffices. For the purpose, we describe each source with a set of prototypical queries that are algorithmically arranged into a lattice, which makes searching efficient. The proposed algorithms leverage GeoSPARQL query containment enhanced with OWL 2 QL semantics. A prototype is implemented in a system called OnGIS.} } @Article{OJSW_2018v5i1n01_Kostov, title = {Count Distinct Semantic Queries over Multiple Linked Datasets}, author = {Bogdan Kostov and Petr Kremen}, journal = {Open Journal of Semantic Web (OJSW)}, issn = {2199-336X}, year = {2018}, volume = {5}, number = {1}, pages = {1--11}, url = {http://nbn-resolving.de/urn:nbn:de:101:1-201712245426}, urn = {urn:nbn:de:101:1-201712245426}, publisher = {RonPub}, bibsource = {RonPub}, abstract = {In this paper, we revise count distinct queries and their semantics over datasets with incomplete knowledge, which is a typical case for the linked data integration scenario where datasets are viewed as ontologies. We focus on counting individuals present in the signature of the ontology. Specifically, we investigate the Certain Epistemic Count (CEC) and the Possible Epistemic Count (PEC) interval based semantics. In the case of CEC semantics, we propose an algorithm for its evaluation and we prove its correctness under a practical constraint of the queried ontology. We conduct and report experiments with the implementation of the proposed algorithm. We also prove decidability of the PEC semantics.} }