Papers by Dominique Ritze
International Conference on Dublin Core and Metadata Applications, Sep 2, 2013
Traditionally, research data and publications are held in separate systems. This results in a dis... more Traditionally, research data and publications are held in separate systems. This results in a disadvantageous situation for researchers as they need to use a variety of different systems to find relevant information about a topic. We therefore face the challenge to overcome the boundaries between bibliographic records and research data by providing an integrated search environment for publications and research data. Because of the inherently different system structure and the diverse metadata for publications and datasets respectively, one type of data cannot easily be integrated into an information system designed for another data type. We present the challenges that arise when adapting a bibliographic library system to include the additional data and give recommendations for an efficient implementation. By presenting our enhanced prototype, we show the applicability and practicability of our proposed solutions. Since our library catalogue prototype features links between publications and underlying research datasets, we provide direct access to metadata of research data stored in remote research data repositories and thus connect both types of information systems.
Proceedings of the 5th International Conference on Web Intelligence, Mining and Semantics - WIMS '15, 2015
Lecture Notes in Computer Science, 2015
Proceedings of the 23rd International Conference on World Wide Web - WWW '14 Companion, 2014
Ontology matching 1 is a key interoperability enabler for the Semantic Web, as well as a useful t... more Ontology matching 1 is a key interoperability enabler for the Semantic Web, as well as a useful tactic in some classical data integration tasks. It takes the ontologies as input and determines as output an alignment, that is, a set of correspondences between the semantically related entities of those ontologies. These correspondences can be used for various tasks, such as ontology merging and data translation. Thus, matching ontologies enables the knowledge and data expressed in the matched ontologies to interoperate.
With the growth of the Linked Data Web, time-efficient Link Discovery frameworks have become indi... more With the growth of the Linked Data Web, time-efficient Link Discovery frameworks have become indispensable for implementing the fourth Linked Data principle, i.e., the provision of links between data sources. Due to the sheer size of the Data Web, detecting links even when using trivial specifications based on a single property can be very timedemanding. Moreover, non-trivial Link Discovery tasks require complex link specifications and are consequently even more challenging to optimize with respect to runtime. In this paper, we present a novel hybrid approach to link discovery that combines two very fast algorithms. Both algorithms are combined by using original insights on the translation of complex link specifications to combinations of atomic specifications via a series of operations on sets and filters. We show in three experiments that our approach outperforms SILK by more than six orders of magnitude while abiding to the restriction of not losing any link.
Lecture Notes in Computer Science, 2015
The ICE-Map Visualization was developed to graphically an- alyze the distribution of indexing res... more The ICE-Map Visualization was developed to graphically an- alyze the distribution of indexing results within a given Knowledge Organization System (KOS) hierarchy and allows the user to explore the document sets and the KOSs at the same time. In this paper, we demonstrate the use of the ICE-Map Visualization in combination with a simple automatic indexer to visualize the semantic overlap between a KOS and a set of documents.
Current ontology matching techniques focus on detecting correspondences between atomic concepts a... more Current ontology matching techniques focus on detecting correspondences between atomic concepts and properties. Nevertheless, it is necessary and possible to detect correspondences between complex concept or property descriptions. In this paper, we demonstrate how complex matching can benefit from natural language processing techniques, and propose an enriched set of correspondence patterns leveraging linguistic matching conditions. After elaborating on the integration of methods for the linguistic analysis of textual labels with an existing framework for detecting complex correspondences, we present the results of an experimental evaluation on an OAEI dataset. The results of our experiments indicate a large increase of precision as compared to the original approach, which was based on similarity measures and thresholds.
State of the art ontology matching techniques are limited to detect simple correspondences betwee... more State of the art ontology matching techniques are limited to detect simple correspondences between atomic concepts and properties. Nevertheless, for many concepts and properties atomic counterparts will not exist, while it is possible to construct equivalent complex concept and property descriptions. We define a correspondence where at least one of the linked entities is non-atomic as complex correspondence. Further, we introduce several patterns describing com- plex correspondences. In particular, we focus on methods for automatically de- tecting complex correspondences. These methods are based on a combination of basic matching techniques. We conduct experiments with different datasets and discuss the results.
Web Semantics: Science, Services and Agents on the World Wide Web, 2015
Lecture Notes in Computer Science, 2015
ABSTRACT This paper reports on the first usage of the MultiFarm dataset for evaluating ontology m... more ABSTRACT This paper reports on the first usage of the MultiFarm dataset for evaluating ontology matching systems. This dataset has been de-signed as a comprehensive benchmark for multilingual ontology match-ing. In this first set of experiments, we analyze how state-of-the-art matching systems – not particularly designed for the task of multilingual ontology matching – perform on this dataset. Our experiments show the hardness of MultiFarm and result in baselines for any algorithm specif-ically designed for multilingual ontology matching. Moreover, this first reporting allows us to draw relevant conclusions for both multilingual ontology matching and ontology matching evaluation in general.
Lecture Notes in Computer Science, 2015
Web resources, such as publications, datasets, pictures and others can be directly linked to thei... more Web resources, such as publications, datasets, pictures and others can be directly linked to their provenance data, as described in the specification about Provenance Access and Query (PROV-AQ) by the W3C. On its own, this approach places all responsibility with the publisher of the resource, who hopefully maintains and publishes provenance information. In reality, however, most publishers lack incentives to publish the provenance of resources, even if the owner would like such information to be published. Currently, it is very intricate to link existing resources to new provenance information, either provided by the owner or a third party. In this paper, we present a solution for this problem by implementing a lightweight, read/write provenance query service, integrated with a pingback mechanism, following the PROV-AQ recommendation.
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Papers by Dominique Ritze