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Motivated by the ongoing success of Linked Data and the growing amount of semantic data sources available on the Web, new challenges to query processing are emerging. Especially in distributed settings that require joining data provided by multiple sources, sophisticated optimization techniques are necessary for efficient query processing. We propose novel(More)
In this paper we present FedBench, a comprehensive benchmark suite for testing and analyzing the performance of federated query processing strategies on semantic data. The major challenge lies in the heterogeneity of semantic data use cases, where applications may face different settings at both the data and query level, such as varying data access(More)
This paper describes the design and implementation of Bibster, a Peer-to-Peer system for exchanging bibliographic data among researchers. Bibster exploits ontologies in data-storage, query formulation, query-routing and answer presentation: When bibliographic entries are made available for use in Bibster, they are structured and classified according to two(More)
Representing knowledge about researchers and research communities is a prime use case for distributed, locally maintained, interlinked and highly structured information in the spirit of the Semantic Web. In this paper we describe the publicly available ‘Semantic Web for Research Communities’ (SWRC) ontology, in which research communities and relevant(More)
We present a user-centered model for porting natural language interfaces (NLIs) between domains efficiently. The model assumes that domain experts without any background knowledge about computational linguistics will perform the customization of the NLI to a specific domain. In fact, it merely requires familiarity with the underlying knowledge base as well(More)
In this paper we present a comprehensive framework for measuring similarity within and between ontologies as a basis for the interoperability across various application fields. In order to define such a framework, we base our work on an abstract ontology model that allows adhering to various existing and evolving ontology standards. The main characteristic(More)
In this paper we argue why it is necessary to associate linguistic information with ontologies and why more expressive models, beyond RDFS, OWL and SKOS, are needed to capture the relation between natural language constructs on the one hand and ontological entities on the other. We argue that in the light of tasks such as ontology-based information(More)
Support for ontology evolution is extremely important in ontology engineering and application of ontologies in dynamic environments. A core aspect in the evolution process is the to guarantee consistency of the ontology when changes occur. In this paper we discuss the consistent evolution of OWL ontologies. We present a model for the semantics of change for(More)
The customization of a natural language interface to a certain application, domain or knowledge base still represents a major effort for end users given the current state-of-the-art. In this article, we present our natural language interface ORAKEL, describe its architecture, design choices and implementation. In particular, we present ORAKEL’s adaptation(More)
Ontology Learning from text aims at generating domain ontologies from textual resources by applying natural language processing and machine learning techniques. It is inherent in the ontology learning process that the acquired ontologies represent uncertain and possibly contradicting knowledge. From a logical perspective, the learned ontologies are(More)