Abstract. While the increasing popularity of folksonomies has lead to a vast quantity of tagged data, resource retrieval in folksonomies is limited by being agnostic to the meaning (i.e., semantics) of tags. Our goal is to automatically enrich folksonomy tags (and implicitly the related resources) with formal semantics by associating them to relevant concepts defined in online ontologies. We introduce FLOR, a method that performs automatic folksonomy enrichment by combining knowledge from WordNet and online available ontologies. Experimentally testing FLOR, we found that it correctly enriched 72 % of 250 Flickr photos. 1

With the prevalence of graph data in a variety of domains, there is an increasing need for a language to query and manipulate graphs with heterogeneous attributes and structures. We propose a query language for graph databases that supports arbitrary attributes on nodes, edges, and graphs. In this language, graphs are the basic unit of information and each query manipulates one or more collections of graphs. To allow for flexible compositions of graph structures, we extend the notion of formal languages from strings to the graph domain. We present a graph algebra extended from the relational algebra in which the selection operator is generalized to graph pattern matching and a composition operator is introduced for rewriting matched graphs. Then, we investigate access methods of the selection operator. Pattern matching over large graphs is challenging due to the NP-completeness of subgraph isomorphism. We address this by a combination of techniques: use of neighborhood subgraphs and profiles, joint reduction of the search space, and optimization of the search order. Experimental results on real and synthetic large graphs demonstrate that our graph specific optimizations outperform an SQL-based implementation by orders of magnitude.

Abstract. SwetoDblp is a large populated ontology with a shallow schema yet a large number of real-world instance data. We describe how such ontology is built from an XML source and how it can be maintained. Instead of a one-to-one mapping from XML to RDF, the creation of the ontology emphasizes the addition of relationships and the value of URIs. SwetoDblp is publicly available online. We also summarize research efforts that have used or are using this freely available community resource. Keywords. Ontology, Semantic Analytics, RDF, XML, Ontology Population. 1

Personalization of web-based information systems based on specialized user models has become more important in order to preserve the effectiveness of their use as the amount of available content increases. We describe a user modeling approach based on automated acquisition of user behaviour and its successive rule-based evaluation and transformation into an ontological user model. We stress reusability and flexibility by introducing a novel approach to logging, which preserves the semantics of logged events. The successive analysis is driven by specialized rules, which map usage patterns to knowledge about users, stored in an ontology-based user model. We evaluate our approach via a case study using an enhanced faceted browser, which provides personalized navigation support and recommendation.

Knowledge artifacts that have been labeled as ontologies have many different qualities and intended outcomes. This is particularly true of bio-ontologies where high demand has led to a rapid growth in the number of these artifacts. Good communication between the human agents involved in the life cycle of ontologies is essential for the ontologist to encode the right knowledge in the ontology. Not only this, but it should be encoded such that subsequent retrieval of the knowledge from the ontology by any agent can be clear and precise. The ontologist can encode ontological statements, for interpretation by a computer agent, or meta-ontological statements, for interpretation by human agents. We consider how the current communication between agents and ontologies produces drawbacks that add to the considerable overheads associated with ontology development. We describe the processes of communication between human agents and ontologies as Ontology Comprehension. We then suggest how these processes could be augmented, particularly with the use of Web 2.0 ideas. By exposing and enhancing the social interactions involved in ontology comprehension, development overheads are potentially reduced and the prospect of ontology sharing and reuse is improved.

New challenges for advanced web search interfaces and visualization tools arise as user needs shift from traditional lookup tasks towards more open ended search activities collectively described as exploratory search. Exploratory search opens new possibilities for employing social aspects for effective information retrieval. We facilitate exploratory search by providing users with an integrated search and navigation interface combining three search paradigms – full text search, view-based (faceted) search and content-based (queryby-example) search. Full text search is used for both domain data and metadata lookup, view-based search allows users to further refine/filter the respective result set, while content-based search orders or biases the results based on their similarity to a given set of sample results.

Abstract. The current work has arisen with respect to the growing importance of ontology modelling in Information Systems development. Due to emerging technologies of Semantic Web, it is desirable to use for this purpose the Web Ontology Language OWL. From the other side, the relational database technology has ensured the best facilities for storing, updating and manipulating the information of problem domain. The algorithms for transformation of domain ontology, described in OWL, to relational database are proposed. The methodology is illustrated with an example.

The fast growth and spread of Web 2.0 environments have demonstrated the great willingness of general Web users to contribute and share various type of content and information. Many very successful web sites currently exist which thrive on the wisdom of the crowd, where web users in general are the sole data providers and curators. The Semantic Web calls for knowledge to be semantically represented using ontologies to allow for better access and sharing of data. However, constructing ontologies collaboratively is not well supported by most existing ontology and knowledge-base editing tools. This has resulted in the recent emergence of a new range of collaborative ontology construction tools with the aim of integrating some Web 2.0 features into the process of structured knowledge construction. This paper provides a survey of the start of the art of these tools, and highlights their significant features and capabilities. 1.

Abstract. The semantics of OWL-DL and its subclasses are based on the classical semantics of first-order logic, in which the interpretation domain may be an infinite set. This constitutes a serious expressive limitation for such ontology languages, since, in many real application scenarios for the Semantic Web, the domain of interest is actually finite, although the exact cardinality of the domain is unknown. Hence, in these cases the formal semantics of the OWL-DL ontology does not coincide with its intended semantics. In this paper we start filling this gap, by considering the subclasses of OWL-DL which correspond to the logics of the DL-Lite family, and studying reasoning over finite models in such logics. In particular, we mainly consider two reasoning problems: deciding satisfiability of an ontology, and answering unions of conjunctive queries (UCQs) over an ontology. We first consider the description logic DL-LiteR and show that, for the two above mentioned problems, finite model reasoning coincides with classical reasoning, i.e., reasoning over arbitrary, unrestricted models. Then, we analyze the description logics DL-LiteF and DL-LiteA. Differently from DL-LiteR, in such logics finite model reasoning does not coincide with classical reasoning. To solve satisfiability and query answering over finite models in these logics, we define techniques which reduce polynomially both the above reasoning problems over finite models to the corresponding problem over arbitrary models. Thus, for all the DL-Lite languages considered, the good computational properties of satisfiability and query answering under the classical semantics also hold under the finite model semantics. Moreover, we have effectively and easily implemented the above techniques, extending the DL-Lite reasoner QuOnto with support for finite model reasoning. 1

Abstract. Motivated by recent developments in the dataspaces, web, and personal information management communities, we outline research directions on query processing for SPARQL, the W3C recommendation language for querying RDF triple stores. The core of each SPARQL query is a basic graph pattern (BGP). BGP is a little logic for extracting subsets of related nodes in an RDF graph. In this paper we undertake a formal study of BGP with an eye towards efficient SPARQL query evaluation. Our main contributions are (1) an algebraization of BGP, and (2) first steps towards a framework for the design of structural indexes to accelerate processing of queries in this algebra. 1