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Matches in ScholarlyData for { ?s <https://w3id.org/scholarlydata/ontology/conference-ontology.owl#abstract> ?o. }

• 147 abstract "Ultrawrap is an automatic wrapping system that synthesizes an OWL ontology from the database’s SQL schema and provides SPARQL query services for legacy relational databases. The system intentionally defines triples by using SQL view statements. The benefits of this organization include, the virtualization of the triple table assures real-time consistency between relational and semantic accesses to the database and the existing SQL optimizer implements the most challenging aspects of rewriting SPARQL to equivalent queries on the relational representation of the data. Initial experiments are auspicious.".
• 148 abstract "This demo shows the integration of spatial and semantic reasoning for the recognition of ship behavior. We recognize abstract behavior such as "ferry trip" and derive that the ship showing this behavior is a "ferry". We accomplish this by abstracting over low-level ship trajectory data and applying Prolog rules that express properties of ship behavior. These rules make use of the GeoNames ontology and a spatial indexing package for SWI-Prolog, which is available as open source software.".
• 149 abstract "Semantic Web reasoning systems are confronted with the task to process growing amounts of distributed, dynamic resources. We propose a novel way of approaching the challenge by RDF graph traversal, exploiting the advantages of Swarm Intelligence. Our nature-inspired methodology is realised by self-organising swarms of autonomous, light-weight entities that traverse RDF graphs by following paths, aiming to instantiate pattern-based inference rules.".
• 150 abstract "In this paper we present TagMe!, a tagging and exploration front-end for Flickr images, which enables users to add categories to tag assignments and to attach tag assignments to a specific area within an image. We analyze the differences between tags and categories and show how both facets can be applied to learn semantic relations between concepts referenced by tags and categories. Further, we discuss how the multi-faceted tagging helps to improve the retrieval of folksonomy entities. The TagMe! system is currently available at http://tagme.groupme.org".
• 151 abstract "Ranking and optimization of web service compositions are some of the most interesting challenges at present. Since web services can be enhanced with formal semantic descriptions, forming the "semantic web services", it becomes conceivable to exploit the quality of semantic links between services (of any composition) as one of the optimization criteria. For this we propose to use the semantic similarities between output and input parameters of web services. Coupling this with other criteria such as quality of service (QoS) allow us to rank and optimize compositions achieving the same goal. We present the Composition Optimizer tool, using an innovative and extensible optimization model designed to balance semantic fit (or functional quality) with non-functional QoS metrics, in order to optimize service composition. To allow the use of this model in the context of a large number of services as foreseen by the EC-funded project SOA4All we propose and test the use of Genetic Algorithms.".
• 152 abstract "This paper presents SWEET, the first tool developed for supporting users in creating semantic RESTful services by structuring service descriptions and associating semantic annotations with the aim to support a higher level of automation when performing common tasks with RESTful services, such as their discovery and composition.".
• 153 abstract "The Ontology Engineering field lacks tools that guide ontology developers to plan and schedule their ontology development projects. gOntt helps ontology developers in two ways: (a) to schedule ontology projects; and (b) to execute such projects based on the schedule and using the NeOn Methodology.".
• 154 abstract "The need to monitor a person's web presence has risen in recent years due to identity theft and lateral surveillance becoming prevalent web actions. In this paper we present a machine learning-inspired bootstrapping approach to monitor identity web references that only requires as input an initial small seed set of data modelled as an RDF graph. We vary the combination of different RDF graph matching paradigms with different machine learning classifiers and observe the effects on the classification of identity web references. We present preliminary results of an evaluation in order to show the variation in accuracy of these different permutations.".
• 158 abstract "Large scale semantic web applications require efficient and robust description logic (DL) reasoning services. In this paper, we present a soundness preserving tractable approximative reasoning approach for TBox reasoning in R, a fragment of OWL2-DL supporting ALC GCIs and role chains with 2ExpTime-hard complexity. We first rewrite the ontologies into EL+ with an additional complement table maintaining the complementary relations between named concepts, and then classify the approximation. Preliminary evaluation shows that our approach can classify existing benchmarks in large scale efficiently with a high recall.".
• 162 abstract "The Semantic Web was designed to unambiguously define and use ontologies to encode data and knowledge on the Web. Many people find it difficult, however, to write complex RDF statements and queries because it requires familiarity with the appropriate ontologies and the terms they define. We describe a framework that eases the experiences in authoring and querying RDF data, in which we focus on automatically finding a set of appropriate Semantic Web ontology terms from a set of words used as the labels of nodes and edges in an incoming semantic graph.".
• 163 abstract "A vision of the Semantic Web is to facilitate global software interoperability. Many approaches and specifications are available that work towards realization of this vision: Service-oriented architectures (SOA) provide a good level of abstraction for interoperability; Web Services provide programmatic interfaces for application to application communication in SOA; there are ontologies that can be used for machine-readable description of service semantics. What is still missing is a standard for constructing semantically formulated service requests that solely rely on shared domain ontologies without depending on programatic or even semantically described interfaces. emph{Semantic RPC} would then include the whole process from issuing such a request, matchmaking with semantic profiles of available and accessible services, deriving input parameters for the matched service(s), calling the service(s), getting the results, and mapping back the results onto an appropriate response to the original request. The standard must avoid realization-specific assumptions so that frameworks supporting semantic RPC can be built for bridging the gap between the semantically formulated service requests and matched programmatic interfaces. This poster introduces a candidate solution to this problem by outlining a query language for semantic service utilization based on an extension of the OWL-S ontology for service description.".
• 164 abstract "The Open Ontology Repository is an open source effort to develop infrastructure for ontologies that is federated, robust and secure. This article describes the purpose, requirements and goals of this initiative.".
• 168 abstract "As more and more of the world's databases are opened to the Semantic Web as linked data, there is a growing awareness of the need for upper-level ontologies and RDF vocabularies to support the dissemination of this data. For more than 150 years libraries have been developing standards for describing resources contained in the world's libraries. This year, for the first time in its long history, the library community is making that experience and knowledge freely available as a coordinated set of controlled vocabularies and upper-level ontologies. Resource Description and Access (RDA) is the international library community's new standard for resource description. A component of this standard -- the RDA Vocabularies -- will finally allow libraries to make the vast silos of library and museum metadata publicly available as semantically rich linked data, and provide the semantic web and linked data communities access to more than a century of library experience in describing resources. The Open Metadata Registry is hosting these vocabularies. The Registry is an Open Source, non-commercial project specifically designed to provide individuals, communities, and organizations an easy-to-use platform supporting the development and dissemination of multi-lingual controlled vocabularies and upper-level and domain-specific ontologies. This demo, poster and related handouts will introduce Resource Description and Access (RDA) and the Open Metadata Registry vocabulary development platform to the Semantic Web Community.".
• 169 abstract "We present SaHaRa, a system that helps to discover and analyze the relationship between entities and topics in large collections of news articles. We augment entity related search by including semantically related linked open data.".
• 170 abstract "The Tetherless World Mobile Wine Agent integrates semantics, geolocation, and social networking on a low-power, mobile platform to provide a unique food and wine recommender system. It provides a robust user interface that allows users to describe a wealth of information about foods and wines as OWL classes and instances and it allows users to share these descriptions with their friends via custom URIs. This demonstration will examine how the user interface simplifies generating RDF data, how location services such as GPS can simplify reasoning (reducing the ABox due to context-sensitive information), and how users of the Mobile Wine Agent can utilize social networking tools such as Facebook and Twitter to share content with others over the World Wide Web.".
• 171 abstract "The National Center for Biomedical Ontology Annotator is an ontology-based web service for annotation of textual biomedical data with biomedical ontology concepts. The biomedical community can use the Annotator service to tag datasets automatically with concepts from more than 200 ontologies coming from the two most important set of biomedical ontology & terminology repositories: the UMLS Metathesaurus and NCBO BioPortal. Through annotation (or tagging) of datasets with ontology concepts, unstructured free-text data becomes structured and standardized. Such annotations contribute to create a biomedical semantic web that facilitates translational scientific discoveries by integrating annotated data.".
• 174 abstract "The Lexical Grid (LexGrid) project is an on-going community-driven initiative coordinated by the Mayo Clinic Division of Biomedical Statistics and Informatics. It provides a common terminology model to represent multiple vocabulary and ontology sources as well as a scalable and robust API for accessing such information. While successfully used and adopted in the biomedical and clinical community, LexGrid model now needs to be aligned with emerging Semantic Web standards and specifications. This paper introduces the LexRDF model, which maps the LexGrid model elements to corresponding constructs in W3C speci¯cations such as RDF, OWL, and SKOS. With LexRDF, the terminological information represent in LexGrid can be translated to RDF triples, and therefore allowing LexGrid to leverage standard tools and technologies such as SPARQL and RDF triple stores.".
• 175 abstract "SILK is a new knowledge representation (KR) language and system that integrates and extends recent theoretical and implementation advances in semantic rules and ontologies. It addresses fundamental requirements for scaling the Se- mantic Web to large knowledge bases in science and busi- ness that answer questions, proactively supply info, and rea- son powerfully. SILK radically extends the KR power of W3C OWL RL, SPARQL, and RIF-BLD, as well as of SQL and production rules. It includes defaults (cf. Courteous LP), higher-order features (cf. HiLog), frame syntax (cf. F-Logic), external actions (cf. production rules), and sound interchange with the main existing forms of knowledge/data in the Semantic Web and deep Web. These features cope with knowledge quality and context, provide flexible meta- reasoning, and activate knowledge.".
• 177 abstract "In this demo, we demonstrate a plaform which makes sensor data available following the linked open data principle and enables the seamless integration of such data into mashups. SensorMasher publishes sensor data as Web data sources which can then easily be integrated with other (linked) data sources and sensor data. Raw sensor readings and sensors can be semantically described and annotated by the user. These descriptions can then be exploited in mashups and in linked open data scenarios and enable the discovery and integration of sensors and sensor data at large scale. The user-generated mashups of sensor data and linked open data can in turn be published as linked open data sources and be used by others".
• 182 abstract "In this demo and poster, we show a conceptual approach and an on-line tool that allows the use of RDFa for embedding non-trivial RDF models in the form of invisible div/span elements into existing Web content. This simplifies the publication of sophisticated RDF data, i.e. such that goes beyond simple property-value pairs, by broad audiences. Also, it empowers users with access limited to inserting XHTML snippets within Web-based authoring systems to add fully-fledged RDF and even OWL. Such is a frequent limitation for users of CMS systems or Wikis.".
• 184 abstract "Semantic graphs can be seen as a way of representing and visualizing textual information in more structured, RDF-like graphs. The reader thus obtains an overview of the content, without having to read through the text. In building a compact semantic graph, an important step is grouping similar concepts under the same label and connecting them to external repositories. This is achieved through disambiguating word senses, in our case by assigning the sense to a concept given its context. The paper presents an unsupervised, knowledge based word sense disambiguating algorithm for linking semantic graph nodes to the WordNet vocabulary. The algorithm is integrated in the semantic graph generation pipeline, improving the semantic graph readability and conciseness. Experimental evaluation of the proposed disambiguation algorithm shows that it gives good results.".
• 186 abstract "In this demo we will present XLWrap-Server, which is a wrapper for collections of spreadsheets providing a SPARQL and Linked Data interface similar to D2R-Server. It is based on XLWrap, a novel approach for generating RDF graphs of arbitrary complexity from spreadsheets with different layouts. To our best knowledge, XLWrap is the first spreadsheet wrapper, supporting cross tables and tables where data is not aligned in rows. It features a full expression algebra based on the syntax of OpenOffice Calc which can be easily extended by users and it supports Microsoft Excel, Open Document, and large CSV spreadsheets. XLWrap-Server can be used to integrate information from a collection of spreadsheets. We will show several use-cases and mapping design patterns in our demonstration.".
• 187 abstract "Service oriented access in a multi-application, multi-access network environment is faced with the problem of cross-layer interoperability among technologies. In this demo, we present a knowledge base (KB) which contains local (user terminal specific) knowledge that enables pro-active network selection by translating technology specific parameters to higher-level, more abstract parameters. We implemented a prototype which makes use of semantic technology (namely ResearchCyc) for creating the elements of the KB and uses reasoning to determine the best access network. The system implements technology-specific parameter mapping according to the IEEE 802.21 draft standard recommendation.".
• 188 abstract "The Data-gov Wiki is the delivery site for a project where we investigate the role of linked data in producing, processing and utilizing the government datasets found on data.gov. The project has generated over 2 billion triples from government data and a few interesting applications covering data access, visualization, integration, linking and analysis.".
• 190 abstract "This paper discusses semantic technologies for multi-perspective issues of ontologies based on ontological viewpoint management. We developed two technologies and implement them in environmental and medical domain. The first one is conceptual map generation tool which allows the users to explore an ontology according to their own perspectives and visualizes them in a user-friendly form, i.e. conceptual map. The other is on-demand reorganization of is-a hierarchy from an ontology. They contribute to integrated understanding of ontologies and a solution of multi-perspective issues of ontologies.".
• 191 abstract "GNOWSYS-mode is an Emacs extension package for knowledge networking and ontology management using GNOWSYS (Gnowledge Networking and Organizing SYStem) as a server. The demonstration shows how to collaboratively build ontologies and semantic network in an intuitive plain text without any of the RDF notations, though importing and exporting in RDF is possible.".
• 192 abstract "The adoption of ontologies for the Web of Data can be increased by tools that help populating respective knowledge bases from legacy content, e.g. existing databases, business applications, or proprietary data formats. In this demo and poster, we show the results from our efforts of developing a suite of open-source tools for creating e-commerce descriptions for the Web of Data based on the GoodRelations ontology. Also, we demonstrate how RDF/XML data can be (1) submitted to Yahoo SearchMonkey via the RDF2DataRSS conversion tool, (2) inspected using the SearchMonkey Meta-Data Inspector, and (3) how common data inconsistencies can be spotted with the GoodRelations Validator.".
• 194 abstract "In many data-centric applications, it is desirable to use OWL as an expressive schema language with which one expresses constraints that must be satisfied by instance data. However, specific aspects of OWL's standard semantics---i.e., the Open World Assumption (OWA) and the absence of Unique Name Assumption (UNA)---make it difficult to use OWL in this way. In this paper, we present an Integrity Constraint (IC) semantics for OWL axioms, show that IC validation can be reduced to query answering, and present our preliminary results with a prototype implementation using Pellet.".
• 195 abstract "Hierarchical classifications are available for many domains of interest. They often provide a large amount of category definitions and some sort of hierarchies. Thanks to their size and popularity, they are a promising ground for publishing and organizing data on the Semantic Web. Unfortunately, classifications can mostly not be directly used as ontologies in OWL, because they are not (or at least: very bad) ontologies. In particular, the labels in categories often lack a context-neutral notion of what it means to be an instance of that category, and the meaning of the hierarchical relations is often not a strict subClassOf. SKOS2OWL is an online tool that allows deriving consistent RDF-S or OWL ontologies from most hierarchical classifications available in the W3C SKOS exchange format. SKOS2OWL helps the user narrow down the intended meaning of the available categories to classes and guides the user through several modeling choices. In particular, SKOS2OWL can draw a representative random sample of relevant conceptual elements in the SKOS file and asks the user to make statements about their meaning. This can be used to make reliable modeling decisions without looking at every single element, which would be unfeasible for large classifications.".
• 106 abstract "One of the core services provided by OWL reasoners is classification: the discovery of all subclass relationships between class names occurring in an ontology. Discovering these relations can be computationally expensive, particularly if individual subsumption tests are costly or if the number of class names is large. We present a classification algorithm which exploits partial information about subclass relationships to reduce both the number of individual tests and the cost of working with large ontologies. We also describe techniques for extracting such partial information from existing reasoners. Empirical results from a prototypical implementation demonstrate substantial performance improvements compared to existing algorithms and implementations.".
• 125 abstract "RDF Schema (RDFS) as a lightweight ontology language is gaining popularity and, consequently, tools for scalable RDFS inference and querying are needed. SPARQL has become recently a W3C standard for querying RDF data, but it mostly provides means for querying simple RDF graphs only, whereas querying with respect to RDFS or other entailment regimes is left outside the current specification. In this paper, we show that SPARQL faces certain unwanted ramifications when querying ontologies in conjunction with RDF datasets that comprise multiple named graphs, and we provide an extension for SPARQL that remedies these effects. Moreover, since RDFS inference has a close relationship with logic rules, we generalize our approach to select a custom ruleset for specifying inferences to be taken into account in a SPARQL query. We show that our extensions are technically feasible by providing benchmark results for RDFS querying in our prototype system GiaBATA, which uses Datalog coupled with a persistent Relational Database as a back-end for implementing SPARQL with dynamic rule-based inference. By employing different optimization techniques like magic set rewriting our system remains competitive with state-of-the-art RDFS querying systems.".
• 136 abstract "The QL profile of OWL 2 has been designed so that it is possible to use database technology for query answering via query rewriting. We present a comparison of our resolution based rewriting algorithm with the standard algorithm proposed by Calvanese et al., implementing both and conducting an empirical evaluation using ontologies and queries derived from realistic applications. The results indicate that our algorithm produces significantly smaller rewritings in most cases, which could be important for practicality in realistic applications.".
• 152 abstract "This paper presents a decidable fragment for combining ontologies andrules in order-sorted logic programming. We describe order-sortedlogic programming with sort, predicate, and meta-predicate hierarchiesfor deriving predicate and meta-predicate assertions. Meta-levelpredicates (predicates of predicates) are useful for representingrelationships between predicate formulas, and further, theyconceptually yield a hierarchy similar to the hierarchies of sorts andpredicates. By extending the order-sorted Horn-clause calculus, wedevelop a query-answering system that can answer queries such as atomsand meta-atoms generalized by containing predicate variables. We showthat the expressive query-answering system computes every generalizedquery in single exponential time, i.e., the complexity of our querysystem is equal to that of DATALOG.".
• 160 abstract "Social Network Analysis (SNA) provides graph algorithms to characterize the structure of social networks, strategic positions in these networks, specific sub-networks and decompositions of people and activities. Online social platforms like Facebook form huge social networks, enabling people to connect, interact and share their online activities across several social applications. We extended SNA operators using semantic web frameworks to include the semantics of these graph-based representations when analyzing such social networks and to deal with the diversity of their relations and interactions. We present here the results of this approach when it was used to analyze a real social network with 60,000 users connecting, interacting and sharing content.".
• 161 abstract "An increasing number of scientific communities rely on Semantic Web ontologies to share and interpret data within and across research domains. These common knowledge representation resources are usually developed and maintained manually and essentially co-evolve along with experimental evidence produced by scientists worldwide. Detecting automatically the differences between (two) versions of the same ontology in order to store or visualize their deltas is a challenging task for e-science. In this paper, we focus on languages allowing the formulation of concise and intuitive deltas, which are expressive enough to describe unambiguously any possible change and that can be effectively and efficiently detected. We propose a specific language that provably exhibits those characteristics and provide a change detection algorithm which is sound and complete with respect to the proposed language. Finally, we provide a promising experimental evaluation of our framework using real ontologies from the cultural and bioinformatics domains.".
• 165 abstract "Recently, the W3C Linking Open Data effort has boosted the publication and inter-linkage of large amounts of RDF datasets on the Semantic Web. Various ontologies and knowledge bases with millions of RDF triples from Wikipedia and other sources, mostly in e-science, have been created and are publicly available. Recording provenance information of RDF triples aggregated from different heterogeneous sources is crucial in order to effectively support trust mechanisms, digital rights and privacy policies. Managing provenance becomes even more important when we consider not only explicitly stated but also implicit triples (through RDFS inference rules) in conjunction with declarative languages for querying and updating RDF graphs. In this paper we rely on colored RDF triples represented as quadruples to capture and manipulate explicit provenance information.".
• 174 abstract "This paper explores the application of restricted relationship graphs (RDF) and statistical NLP techniques to improve named entity annotation in challenging Informal English domains. We validate our approach using on-line forums discussing popular music. Named entity annotation is particularly difficult in this domain because it is characterized by a large number of ambiguous entities, such as the Madonna album “Music” or Lilly Allen’s pop hit “Smile”. We evaluate improvements in annotation accuracy that can be obtained by restricting the set of possible entities using real-world constraints. We find that constrained domain entity extraction raises the annotation accuracy significantly, making an infeasible task practical. We then show that we can further improve annotation accuracy by over 50% by applying SVM based NLP systems trained on word-usages in this domain.".
• 203 abstract "In this paper a novel approach is presented for generating RDF graphs of arbitrary complexity from various spreadsheet layouts. Currently, none of the available spreadsheet-to-RDF wrappers supports cross tables and tables where data is not aligned in rows. Similar to RDF123, XLWrap is based on template graphs where fragments of triples can be mapped to specific cells of a spreadsheet. Additionally, it features a full expression algebra based on the syntax of OpenOffice Calc and various shift operations, which can be used to repeat similar mappings in order to wrap cross tables including multiple sheets and spreadsheet files. The set of available expression functions includes most of the native functions of OpenOffice Calc and can be easily extended by users of XLWrap. Additionally, XLWrap is able to execute SPARQL queries, and since it is possible to define multiple virtual class extents in a mapping specification, it can be used to integrate information from multiple spreadsheets. XLWrap supports a special identity concept which allows to link anonymous resources (blank nodes) - which may originate from different spreadsheets - in the target graph.".
• 206 abstract "Ontology matching plays a key role for semantic interoperability. Many methods have been proposed for automatically finding the alignment between heterogeneous ontologies. However, in many real-world applications, finding the alignment in a completely automatic way is highly infeasible. Ideally, an ontology matching system would have an interactive interface to allow users to provide feedbacks to guide the automatic algorithm. Fundamentally, we need answer the following questions: how can a system perform an efficiently interactive process with the user? How many interactions are sufficient for finding a more accurate matching? To address these questions, we propose an active learning framework for ontology matching, which tries to find the most informative candidate matches to query the user. The user’s feedbacks are used to: 1) correct the mistake matching and 2) propagate the supervise information to help the entire matching process. Three measures are proposed to estimate the confidence of each matching candidate. A correct propagation algorithm is further proposed to maximize the spread of the user’s “guidance”. Experimental results on several public data sets show that the proposed approach can significantly improve the matching accuracy (+8.0% better than the baseline methods).".
• 217 abstract "Ontologies are tools for describing and structuring knowledge, with many applications in searching and analyzing complex knowledge bases. Since building them manually is a costly process, there are various approaches for bootstrapping ontologies automatically through the analysis of appropriate documents. Such an analysis needs to find the concepts and the relationships that should form the ontology. However, since relationship extraction methods are imprecise and cannot homogeneously cover all concepts, the initial set of relationships is usually inconsistent and rather imbalanced - a problem which, to the best of our knowledge, was mostly ignored so far. In this paper, we define the problem of extracting a consistent as well as properly structured ontology from a set of inconsistent and heterogeneous relationships. Moreover, we propose and compare three graph-based methods for solving the ontology extraction problem. We extract relationships from a large-scale data set of more than 325K documents and evaluate our methods against a gold standard ontology comprising more than 12K relationships. Our study shows that an algorithm based on a modified formulation of the dominating set problem outperforms greedy methods.".
• 219 abstract "The work on integrating sources and services in the Semantic Web assumes that the data is either already represented in RDF or OWL or is available through a Semantic Web Service. In practice, there is a tremendous amount of data on the Web that is not available through the Semantic Web. In this paper we present an approach to automatically discover and create new Semantic Web Services. The idea behind this approach is to start with a set of known sources and the corresponding semantic descriptions and then discover similar sources, extract the source data, build semantic descriptions of the sources, and then turn them into Semantic Web Services. We implemented an end-to-end solution to this problem in a system called Deimos and evaluated the system across five different domains. The results demonstrate that the system can automatically discover, learn semantic descriptions, and build Semantic Web Services with only example sources and their descriptions as input.".
• 240 abstract "Conjunctive query answering for EL++ ontologies has recently drawn much attention, as the Description Logic EL++ captures the expressivity of many large ontologies in the biomedical domain and is the foundation for the OWL 2 EL profile. In this paper, we propose a practical approach for conjunctive query answering in a fragment of EL++, namely acyclic EL+, that supports role inclusions. This approach can be implemented with low cost by leveraging any existing relational database management system to do the ABox data completion and query answering. We conducted a preliminary experiment to evaluate our approach using a large clinical data set and show our approach is practical.".
• 241 abstract "In this paper, we consider the problem of materializing the complete finite RDFS closure in a scalable manner; this includes those parts of the RDFS closure that are often ignored such as literal generalization and container membership properties. We point out characteristics of RDFS that allow us to derive an embarrassingly parallel algorithm for producing said closure, and we evaluate our C/MPI implementation of the algorithm on a cluster with 128 cores using different-size subsets of the LUBM 10,000-university data set. We show that the time to produce inferences scales linearly with the number of processes, evaluating this behavior on up to hundreds of millions of triples. We also show the number of inferences produced for different subsets of LUBM10k. To the best of our knowledge, our work is the first to provide RDFS inferencing on such large data sets in such low times. Finally, we discuss future work in terms of promising applications of this approach including OWL2RL rules, MapReduce implementations, and massive scaling on supercomputers.".
• 251 abstract "Module extraction methods have proved to be effective in improving the performance of some ontology reasoning tasks, including finding justifications to explain why an entailment holds in an OWL DL ontology. However, the existing module extraction methods that compute a syntactic locality-based module for the sub-concept in a subsumption entailment, though ensuring the resulting module to preserve all justifications of the entailment, may be insufficient in improving the performance of finding all justifications. This is because a syntactic locality-based module is independent of the super-concept in a subsumption entailment and always contains all concept/role assertions. In order to extract smaller modules to further optimize finding all justifications in an OWL DL ontology, we propose a goal-directed method for extracting a module that preserves all justifications of a given entailment. Experimental results on large ontologies show that a module extracted by our method is smaller than the corresponding syntactic locality-based module, making the subsequent computation of all justifications more scalable and more efficient.".
• 253 abstract "Scalable query answering over Description Logic (DL) based ontologies plays an important role for the success of the Semantic Web. Towards tackling the scalability problem, we propose a decomposition-based approach to optimizing existing OWL DL reasoners in evaluating conjunctive queries in OWL DL ontologies. The main idea is to decompose a given OWL DL ontology into a set of target ontologies without duplicated ABox axioms so that the evaluation of a given conjunctive query can be separately performed in every target ontology by applying existing OWL DL reasoners. This approach guarantees sound and complete results for the category of conjunctive queries that the applied OWL DL reasoner correctly evaluates. Experimental results on large benchmark ontologies and benchmark queries show that the proposed approach can significantly improve scalability and efficiency in evaluating general conjunctive queries.".
• 278 abstract "Enriching business process models with semantic annotations taken from an ontology has become a crucial necessity both in service provisioning, integration and composition, and in business processes management. In our work we represent semantically annotated business processes as part of an OWL knowledge base that formalises the business process structure, the business domain, and a set of criteria describing correct semantic annotations. In this paper we show how Semantic Web representation and reasoning techniques can be effectively applied to formalise, and automatically verify, sets of constraints on Business Process Diagrams that involve both knowledge about the domain and the process structure. We also present a tool for the automated transformation of an annotated Business Process Diagram into an OWL ontology. The use of the semantic web techniques and tool presented in the paper results in a novel support for the management of business processes in the phase of process modeling, whose feasibility and usefulness will be illustrated by means of a concrete example.".
• 279 abstract "The Semantic Web fosters novel applications targeting a more efficient and satisfying exploitation of the data available on the web, e.g. faceted browsing of linked open data. Large amounts and high diversity of knowledge in the Semantic Web pose the challenging question of appropriate relevance ranking for producing fine-grained and rich descriptions of the available data, e.g. to guide the user along most promising knowledge aspects. Existing methods for graph-based authority ranking lack support for fine-grained latent coherence between resources and predicates (i.e. support for link semantics in the linked data model). In this paper, we present TripleRank, a novel approach for faceted authority ranking in the context of RDF knowledge bases. TripleRank captures the additional latent semantics of Semantic Web data by means of statistical methods in order to produce richer descriptions of the available data. We model the Semantic Web by a 3-dimensional tensor that enables the seamless representation of arbitrary semantic links. For the analysis of that model, we apply the PARAFAC decomposition, which can be seen as a multi-modal counterpart to Web authority ranking with HITS. The result are groupings of resources and predicates that characterize their authority and navigational (hub) properties with respect to identified topics. We have applied TripleRank to multiple data sets from the linked open data community and gathered encouraging feedback in a user evaluation where TripleRank results have been exploited in a faceted browsing scenario.".
• 286 abstract "The framework developed in this paper can deal with scenarios where selected sub-ontologies of a large ontology are offered as views to users, based on criteria like the user's access right, the trust level required by the application, or the level of detail requested by the user. Instead of materializing a large number of different sub-ontologies, we propose to keep just one ontology, but equip each axiom with a label from an appropriate labeling lattice. The access right, required trust level, etc. is then also represented by a label (called user label) from this lattice, and the corresponding sub-ontology is determined by comparing this label with the axiom labels. For large-scale ontologies, certain consequence (like the concept hierarchy) are often precomputed. Instead of precomputing these consequences for every possible sub-ontology, our approach computes just one label for each consequence such that a comparison of the user label with the consequence label determines whether the consequence follows from the corresponding sub-ontology or not. In this paper we determine under which restrictions on the user and axiom labels such consequence labels (called boundaries) always exist, describe different black-box approaches for computing boundaries, and present first experimental results that compare the efficiency of these approaches on large real-world ontologies. Black-box means that, rather than requiring modifications of existing reasoning procedures, these approaches can use such procedures directly as sub-procedures, which allows us to employ existing highly-optimized reasoners.".
• 290 abstract "RDF is an increasingly important paradigm for the representation of information on the Web. As RDF databases increase in size to approach tens of millions of triples, and as sophisticated graph matching queries expressible in languages like SPARQL become increasingly important, scalability becomes an issue. To date, there is no graph-based indexing method for RDF data where the index was designed in a way that makes it disk-resident. There is therefore a growing need for indexes that can operate efficiently when the index itself resides on disk. In this paper, we first propose the DOGMA index for fast subgraph matching on disk and then develop a basic algorithm to answer queries over this index. This algorithm is then significantly sped up via an optimized algorithm that uses efficient (but correct) pruning strategies when combined with two different extensions of the index. We have implemented a preliminary system and tested it against four existing RDF database systems developed by others. Our experiments show that our algorithm performs very well compared to these systems, with orders of magnitude improvements for complex graph queries.".
• 301 abstract "The Web of Linked Data forms a single, globally distributed dataspace. Due to the openness of this dataspace, it is not possible to know in advance all data sources that might be relevant for query answering. This openness poses a new challenge that is not addressed by traditional research on federated query processing. In this paper we present an approach to execute SPARQL queries over the Web of Linked Data. The main idea of our approach is to discover data that might be relevant for answering a query during the query execution itself. This discovery is driven by following RDF links between data sources based on URIs in the query and in partial results. The URIs are resolved over the HTTP protocol into RDF data which is continuously added to the queried dataset. This paper describes concepts and algorithms to implement our approach using an iterator-based pipeline. We introduce a formalization of the pipelining approach and show that classical iterators may cause blocking due to the latency of HTTP requests. To avoid blocking, we propose an extension of the iterator paradigm. The evaluation of our approach shows its strengths as well as the still existing challenges.".
• 305 abstract "Ranking and optimization of web service compositions are some of the most interesting challenges at present. Since web services can be enhanced with formal semantic descriptions, forming the ”semantic web services”, it becomes conceivable to exploit the quality of semantic links between services (of any composition) as one of the optimization criteria. For this we propose to use the semantic similarities between output and input parameters of web services. Coupling this with other criteria such as quality of service (QoS) allow us to rank and optimize compositions achieving the same goal. Here we suggest an innovative and extensible optimization model designed to balance semantic fit (or functional quality) with non-functional QoS metrics. To allow the use of this model in the context of a large number of services as foreseen by the strategic EC-funded project SOA4All we propose and test the use of Genetic Algorithms.".
• 306 abstract "The Web of Data is built upon two simple ideas: Employ the RDF data model to publish structured data on the Web and to create explicit data links between entities within different data sources. This paper presents the Silk - Linking Framework, a toolkit for discovering and maintaining data links between Web data sources. Silk consists of three components: 1. A link discovery engine, which computes links between data sources based on a declarative specification of the conditions that entities must fulfill in order to be interlinked; 2. A tool for evaluating the generated data links in order to fine-tune the linking specification; 3. A protocol for maintaining data links between continuously changing data sources. The protocol allows data sources to exchange both linksets as well as detailed change information and enables continuous link recomputation. The interplay of all the components is demonstrated within a life science use case.".
• 311 abstract "Ontology matching is one of the key research topics in the field of the Semantic Web. There are many matching systems that generate mappings between different ontologies either automatically or semi-automatically. However, the mappings generated by these systems may be inconsistent with the ontologies. Several approaches have been proposed to deal with the inconsistencies between mappings and ontologies. This problem is often called a mapping revision problem, as the ontologies are assumed to be correct, whereas the mappings are repaired when resolving the inconsistencies. In this paper, we first propose a conflict-based mapping revision operator and show that it can be characterized by two logical postulates adapted from some existing postulates for belief base revision. We then provide an algorithm for iterative mapping revision by using an ontology revision operator and show that this algorithm defines a conflict-based mapping revision operator. Three concrete ontology revision operators are given to instantiate the iterative algorithm, which result in three different mapping revision algorithms. We implement these algorithms and provide some preliminary but interesting evaluation results.".
• 323 abstract "Process modeling is a core task in software engineering in general and in web service modeling in particular. The explicit management of process models for purposes such as process selection and/or process reuse requires flexible and intelligent retrieval of process structures based on process entities and relationships, i.e. process activities, hierarchical relationship between activities and their parts, temporal relationships between activities, conditions on process flows as well as the modeling of domain knowledge. In this paper, we analyze requirements for modeling and querying of process models and present a pattern-oriented approach exploiting OWL-DL representation and reasoning capabilities for expressive process modeling and retrieval.".
• 335 abstract "Semantic formalisms represent content in a uniform way according to ontologies. This enables manipulation and reasoning via automated means (e.g. Semantic Web services), but limits the user’s ability to explore the semantic data from a point of view that originates from knowledge representation motivations. We show how, for user consumption, a visualization of semantic data according to some easily graspable dimensions (e.g. space and time) provides effective sense-making of data. In this paper, we look holistically at the interaction between users and semantic data, and propose multiple visualization strategies and dynamic filters to support the exploration of semantic-rich data. We discuss a user evaluation and how interaction challenges could be overcome to create an effective user-centred framework for the visualization and manipulation of semantic data. The approach has been implemented and evaluated on a real company archive.".
• 347 abstract "RDF data are usually accessed using one of two methods: either, graphs are rendered in forms perceivable by human users (e.g., in tabular or in graphical form), which are difficult to handle for large data sets. Alternatively, query languages like SPARQL provide means to express information needs in structured form; hence they are targeted towards developers and experts. Inspired by the concept of spreadsheet tools, where users can perform relatively complex calculations by splitting formulas and values across multiple cells, we have investigated mechanisms that allow us to access RDF graphs in a more intuitive and manageable, yet formally grounded manner. In this paper, we make three contributions towards this direction. First, we present RDFunctions, an algebra that consists of mappings between sets of RDF language elements (URIs, blank nodes, and literals) under consideration of the triples contained in a background graph. Second, we define a syntax for expressing RDFunctions, which can be edited, parsed and evaluated. Third, we discuss Tripcel, an implementation of RDFunctions using a spreadsheet metaphor. Using this tool, users can easily edit and execute function expressions and perform analysis tasks on the data stored in an RDF graph.".
• 360 abstract "In this paper we investigate different technologies to attack the automatic solution of orchestration problems based on synthesis from declarative specifications, a semantically enriched description of the services, and a collection of services available on a testbed. In addition to our previously presented tableaux-based synthesis technology, we consider two structurally rather different approaches here: using jMosel, our tool for Monadic Second-Order Logic on Strings and the high-level programming language Golog, that internally makes use of planning techniques. As a common case study we consider the Mediation Scenario of the Semantic Web Service Challenge, which is a benchmark for process orchestration. All three synthesis solutions have been embedded in the jABC/jETI modeling framework, and used to synthesize the abstract mediator processes as well as their concrete, running (Web) service counterpart. Using the jABC as a common frame helps highlighting the essential differences and similarities. It turns out, at least at the level of complication of the considered case study, all approaches behave quite similarly, both considering the performance as well as the modeling. We believe that turning the jABC framework into experimentation platform along the lines presented here, will help understanding the application profiles of the individual synthesis solutions and technologies, answering questing like when the overhead to achieve compositionality pays of and where (heuristic) search is the technology of choice.".
• 361 abstract "We present a lightweight framework for processing uncertain emergent knowledge that comes from multiple resources with varying relevance. The framework is essentially RDF-compatible, but allows also for direct representation of contextual features (e.g., provenance). We support soft integration and robust querying of the represented content based on well-founded notions of aggregation, similarity and ranking. A proof-of-concept implementation is presented and evaluated within large scale knowledge-based search in life science articles.".
• 370 abstract "Due to significant improvements in the capabilities of small devices such as PDAs and smart phones, these devices can not only consume but also provide Web Services. The dynamic nature of mobile environment means that users need accurate and fast approaches for service discovery. In order achieve high accuracy semantic languages can be used in conjunction with logic reasoners. Since powerful broker nodes are not always available (due to lack of long range connectivity), create a bottleneck (since mobile devices are all trying to access the same server) and single point of failure (in the case that a central server fails), on-board mobile reasoning must be supported. However, reasoners are notoriously resource intensive and do not scale to small devices. Therefore, in this paper we provide an efficient mobile reasoner which relaxes the current strict and complete matching approaches to support anytime reasoning. Our approach matches the most important request conditions (deemed by the user) first and provides a degree of match and confidence result to the user. We provide a prototype implementation and performance evaluation of our work.".
• 374 abstract "We address the problem of scalable distributed reasoning, proposing a technique for materialising the closure of an RDF graph based on MapReduce. We have implemented our approach on top of Hadoop and deployed it on a compute cluster of up to 64 commodity machines. We show that a naive implementation on top of MapReduce is straightforward but performs badly and we present several non-trivial optimisations. Our algorithm is scalable and allows us to compute the RDFS closure of 865M triples from the Web (producing 30B triples) in less than two hours, faster than any other published approach.".
• 375 abstract "The Web allows users to share their work very effectively leading to the rapid re-use and remixing of content on the Web including text, images, and videos. Scientific research data, social networks, blogs, photo sharing sites and other such applications known collectively as the Social Web have lots of increasingly complex information. Such information from several Web pages can be very easily aggregated, mashed up and presented in other Web pages. Content generation of this nature inevitably leads to many copyright and license violations, motivating research into effective methods to detect and prevent such violations. This is supported by an experiment on Creative Commons (CC) attribution license violations from samples of Web sites that had at least one embedded Flickr image, which revealed that the attribution license violation rate of Flickr images on the Web is around 70-90%. Our primary objective is to enable users to do the right thing and comply with CC licenses associated with Web media, instead of preventing them from doing the wrong thing or detecting violations of these licenses. As a solution, we have implemented two applications: (1) Attribution License Violations Validator, which can be used to validate users' derived work against attribution licenses of reused media and, (2) Semantic Clipboard, which provides license awareness of Web media and enables users to copy them along with the appropriate license metadata.".
• 380 abstract "The field of biomedicine has embraced the Semantic Web probably more than any other field. As a result, there is a large number of biomedical ontologies covering overlapping areas of the field. We have developed BioPortal — an open community-based repository of biomedical ontologies. We analyzed ontologies and terminologies in BioPortal and the Unified Medical Language System (UMLS), creating more than 4 million mappings between concepts in these ontologies and terminologies based on the lexical similarity of concept names and synonyms. We then analyzed the mappings and what they tell us about the ontologies themselves, the structure of the ontology repository, and the ways in which the mappings can help in the process of ontology design and evaluation. For example, we can use the mappings to guide users who are new to a field to the most pertinent ontologies in that field, to identify areas of the domain that are not covered sufficiently by the ontologies in the repository, and to identify which ontologies will serve well as background knowledge in domain-specific tools. While we used a specific (but large) ontology repository for the study, we believe that the lessons we learned about the value of a large-scale set of mappings to ontology users and developers are general and apply in many other domains.".
• 387 abstract "To direct automated Web service composition, it is compelling to provide a template, workflow or scaffolding that dictates the ways in which services can be composed. In this paper we present an approach to Web service composition that builds on work using AI planning, and more specifically Hierarchical Task Networks (HTNs), for Web service composition. A significant advantage of our approach is that it provides much of the how-to knowledge of a choreography while enabling customization and optimization of integrated Web service selection and composition based upon the needs of the specific problem, the preferences of the customer, and the available services. Many customers must also be concerned with enforcement of regulations, perhaps in the form of corporate policies and/or government regulations. Regulations are traditionally enforced at design time by verifying that a workflow or composition adheres to regulations. Our approach supports customization, optimization and regulation enforcement all at composition construction time. To maximize efficiency, we have developed novel search heuristics together with a branch and bound search algorithm that enable the generation of high quality compositions with the performance of state-of-the-art planning systems.".
• 391 abstract "Significant efforts have focused in the past years on bringing large amounts of metadata online and the success of these efforts can be seen by the impressive number of web sites exposing data in RDFa or RDF/XML. However, little is known about the extent to which this data fits the needs of ordinary web users with everyday information needs. In this paper we study what we perceive as the semantic gap between the supply of data on the Semantic Web and the needs of web users as expressed in the queries submitted to a major Web search engine. We perform our analysis on both the level of instances and ontologies. First, we first look at how much data is actually relevant to Web queries and what kind of data is it. Second, we provide a generic method to extract the attributes that Web users are searching for regarding particular classes of entities. This method allows to contrast class definitions found in Semantic Web vocabularies with the attributes of objects that users are interested in. Our findings are crucial to measuring the potential of semantic search, but also speak to the state of the Semantic Web in general.".
• 403 abstract "The focus of web search is moving away from returning relevant documents towards returning structured data as results to user queries. A vital part in the architecture of search engines are link-based ranking algorithms, which however are targeted towards hypertext documents. Existing ranking algorithms for structured data, on the other hand, require manual input of a domain expert and are thus not applicable in cases where data integrated from a large number of sources exhibits enormous variance in vocabularies used. In such environments, the authority of data sources is an important signal that the ranking algorithm has to take into account. This paper presents algorithms for prioritising data returned by queries over web datasets expressed in RDF. We introduce the notion of naming authority which provides a correspondence between identifiers and the sources which can speak authoritatively for these identifiers. Our algorithm uses the original PageRank method to assign authority values to data sources based on a naming authority graph, and then propagates the authority values to identifiers referenced in the sources. We conduct performance and quality evaluations of the method on a large web dataset. Our method is schema-independent, requires no manual input, and has applications in search, query processing, reasoning, and user interfaces over integrated datasets.".
• 405 abstract "OntoCase is a framework for semi-automatic pattern-based ontology construction. In this paper we focus on the retain and reuse phases, where an initial ontology is enriched based on content ontology design patterns (Content ODPs), and especially the implementation and evaluation of these phases. Applying Content ODPs within semiautomatic ontology construction, i.e. ontology learning (OL), is a novel approach. The main contributions of this paper are the methods for pattern ranking, selection, and integration, and the subsequent evaluation showing the characteristics of ontologies constructed automatically based on ODPs. We show that it is possible to improve the results of existing OL methods by selecting and reusing Content ODPs. OntoCase is able to introduce a general top structure into the ontologies, and by exploiting background knowledge the ontology is given a richer overall structure.".
• 423 abstract "Forgetting is an important tool for reducing ontologies by eliminating some concepts and roles while preserving sound and complete reasoning. Attempts have previously been made to address the problem of forgetting in relatively simple description logics (DLs) such as DL-Lite and extended EL. The ontologies used in these attempts were mostly restricted to TBoxes rather than general knowledge bases (KBs). However, the issue of forgetting for general KBs in more expressive description logics, such as ALC and OWL DL, is largely unexplored. In particular, the problem of characterizing and computing forgetting for such logics is still open. In this paper, we first define semantic forgetting about concepts and roles in ALC ontologies and state several important properties of forgetting in this setting. We then define the result of forgetting for concept descriptions in ALC, state the properties of forgetting for concept descriptions, and present algorithms for computing the result of forgetting for concept descriptions. Unlike the case of DL-Lite, the result of forgetting for an ALC ontology does not exist in general, even for the special case of concept forgetting. This makes the problem of how to compute forgetting in ALC more challenging. We address this problem by defining a series of approximations to the result of forgetting for ALC ontologies and studying their properties and their application to reasoning tasks. We use the algorithms for computing forgetting for concept descriptions to compute these approximations. Our algorithms for computing approximations can be embedded into an ontology editor to enhance its ability to manage and reason in (large) ontologies.".
• 424 abstract "An important issue for the Semantic Web is how to combine open-world ontology languages with closed-world (non-monotonic) rule paradigms. Several proposals for hybrid languages allow concepts to be simultaneously defined by an ontology and rules, where rules may refer to concepts in the ontology and the ontology may also refer to predicates defined by the rules. Hybrid MKNF knowledge bases are one such proposal, for which both a stable and a well-founded semantics have been defined. The definition of Hybrid MKNF knowledge bases is parametric on the ontology language, in the sense that non-monotonic rules can extend any decidable ontology language. In this paper we define a query-driven procedure for Hybrid MKNF knowledge bases that is sound with respect to the original stable model-based semantics, and is correct with respect to the well-founded semantics. This procedure is able to answer conjunctive queries, and is parametric on an inference engine for reasoning in the ontology language. Our procedure is based on an extension of a tabled rule evaluation to capture reasoning within an ontology by modeling it as an interaction with an external oracle and, with some assumptions on the complexity of the oracle compared to the complexity of the ontology language, maintains the data complexity of the well-founded semantics for hybrid MKNF knowledge bases.".
• 484 abstract "Ontology Modularization techniques identify coherent and often reusable regions within an ontology. The ability to identify such modules, thus potentially reducing the size or complexity of an ontology for a given task or set of concepts is increasingly important in the Semantic Web as domain ontologies increase in terms of size, complexity and expressivity. To date, many techniques have been developed, but evaluation of the results of these techniques is sketchy and somewhat ad hoc. Theoretical properties of modularization algorithms have only been studied in a small number of cases. This paper presents an empirical analysis of a number of modularization techniques, and the modules they identify over a number of diverse ontologies, by utilizing objective, task-oriented measures to evaluate the fitness of the modules for a number of statistical classification problems.".
• 501 abstract "An important application of semantic web technology is recognizing human-defined concepts in text. Query transformation is a strategy often used in search engines to derive queries that are able to return more useful search results than the original query and most popular search engines provide facilities that let users complete, specify, or reformulate their queries. We study the problem of semantic query suggestion, a special type of query transformation based on identifying semantic concepts contained in user queries. We use a feature-based approach in conjunction with supervised machine learning, augmenting term-based features with search history-based and concept-specific features. We apply our method to the task of linking queries from real-world query logs (the transaction logs of the Netherlands Institute for Sound and Vision) to the DBpedia knowledge base. We evaluate the utility of different machine learning algorithms, features, and feature types in identifying semantic concepts using a manually developed test bed and show significant improvements over an already high baseline. The resources developed for this paper, i.e., queries, human assessments, and extracted features, are available for download.".
• 524 abstract "State-of-the-art discovery of Semantic Web services is based on hybrid algorithms that combine semantic and syntactic matchmaking. These approaches are purely based on similarity measures between parameters of a service request and available service descriptions, which, however, fail to completely capture the actual functionality of the service or the quality of the results returned by it. On the other hand, with the advent of Web 2.0, active user participation and collaboration has become an increasingly popular trend. Users often rate or group relevant items, thus providing valuable information that can be taken into account to further improve the accuracy of search results. In this paper, we tackle this issue, by proposing a method that combines multiple matching criteria with user feedback to further improve the results of the matchmaker. We extend a previously proposed dominance-based approach for service discovery, and describe how user feedback is incorporated in the matchmaking process. We evaluate the performance of our approach using a publicly available collection of OWL-S services.".
• 105 abstract "Measuring similarity between ontologies can be very useful for different purposes, e.g., finding an ontology to replace another, or finding an ontology in which queries can be translated. Classical measures compute similarities or distances in an ontology space by directly comparing the content of ontologies. We introduce a new family of ontology measures computed in an alignment space: they evaluate the similarity between two ontologies with regard to the available alignments between them.We define two sets of such measures relying on the existence of a path between ontologies or on the ontology entities that are preserved by the alignments. The former accounts for known relations between ontologies, while the latter reflects the possibility to perform actions such as instance import or query translation. All these measures have been implemented in the OntoSim library, that has been used in experiments which showed that entity preserving measures are comparable to the best ontology space measures. Moreover, they showed a robust behaviour with respect to the alteration of the alignment space. ".
• 110 abstract "The availability of streaming data sources is progressively increasing thanks to the development of ubiquitous data capturing technologies such as sensor networks. The heterogeneity of these sources introduces the requirement of providing data access in a unified and coherent manner, whilst allowing the user to express their needs at an ontological level. In this paper we describe an ontology-based streaming data access service. Sources link their data content to ontologies through s2o mappings. Users can query the ontology using sparqlStream, an extension of sparql for streaming data. A preliminary implementation of the approach is also presented. With this proposal we expect to set the basis for future efforts in ontology-based streaming data integration.".
• 114 abstract "The proliferation of linked data on the Web paves the way to a new generation of applications that exploit heterogeneous data from different sources. However, because this Web of data is large and continuously evolving, it is non-trivial to identify the relevant link data sources and to express some given information needs as structured queries against these sources. In this work, we allow users to express needs in terms of simple keywords. Given the keywords, we define the problem of finding the relevant sources as the one of keyword query routing. As a solution, we present a family of summary models, which compactly represents the Web of linked data and allows to quickly find relevant sources. The proposed models capture information at different levels, representing summaries of varying granularity. They represent different trade-offs between effectiveness and efficiency. We provide a theoretical analysis of these trade-offs and also, verify them in experiments carried out in a real-world setting using more than 150 publicly available datasets.".
• 119 abstract "A key problem in ontology alignment is that different ontological features (e.g., lexical, structural or semantic) vary widely in their importance for different ontology comparisons. In this paper, we present a set of principled techniques that exploit user feedback to customize the alignment process for a given pair of ontologies. Specifically, we propose an iterative supervised-learning approach to (i) determine the weights assigned to each alignment strategy and use these weights to combine them for matching ontology entities; and (ii) determine the degree to which the information from such matches should be propagated to their neighbors along different relationships for collective matching. We demonstrate the utility of these techniques with standard benchmark datasets and large, real-world ontologies, showing improvements in F-scores of up to 70% from the weighting mechanism and up to 40% from collective matching, compared to an unweighted linear combination of matching strategies without information propagation. ".
• 123 abstract "Justifications - that is, minimal entailing subsets of an ontology - are currently the dominant form of explanation provided by ontology engineering environments, especially those focused on the Web Ontology Language (OWL). Despite this, there are naturally occurring justifications that can be very difficult to understand. In essence, justifications are merely the premises of a proof and, as such, do not articulate the (often non-obvious) reasoning which connect those premises with the conclusion. This paper presents justification oriented proofs as a potential solution to this problem.".
• 125 abstract "OWL 2 RL was standardized as a less expressive but scalable subset of OWL 2 that allows a forward-chaining implementation. However, building an enterprise-scale forward-chaining based inference engine that can 1) take advantage of modern multi-core computer architectures, and 2) efficiently update inference for additions remains a challenge. In this paper, we present an OWL 2 RL inference engine implemented inside the Oracle database system, using novel techniques for parallel processing that can readily scale on multi-core machines and clusters. Additionally, we have added support for efficient incremental maintenance of the inferred graph after triple additions. Finally, to handle the increasing number of owl:sameAs relationships present in Semantic Web datasets, we have provided a hybrid in-memory/disk based approach to efficiently compute compact equivalence closures. We have done extensive testing to evaluate these new techniques; the test results demonstrate that our inference engine is capable of performing efficient inference over ontologies with billions of triples using a modest hardware configuration.".
• 126 abstract "On the Semantic Web, decision makers (humans or software agents alike) are faced with the challenge of examining large volumes of information originating from heterogeneous sources with the goal of ascertaining trust in various pieces of information. While previous work has focused on simple models for review and rating systems, we introduce a new trust model for rich, complex and uncertain information.We present the challenges raised by the new model, and the results of an evaluation of the first prototype implementation under a variety of scenarios.".
• 127 abstract "Ontologies underpin the semantic web; they define the concepts and their relationships contained in a data source. An increasing number of ontologies are available on-line, but an ontology that combines information from many different sources can grow extremely large. As an ontology grows larger, more resources are required to use it, and its response time becomes slower. Thus, we present and evaluate an on-line approach that forgets fragments from an OWL ontology that are infrequently or no longer used, or are cheap to relearn, in terms of time and resources. In order to evaluate our approach, we situate it in a controlled simulation environment, RoboCup OWLRescue, which is an extension of the widely used RoboCup Rescue platform, which enables agents to build ontologies automatically based on the tasks they are required to perform. We benchmark our approach against other comparable techniques and show that agents using our approach spend less time forgetting concepts from their ontology, allowing them to spend more time deliberating their actions, to achieve a higher average score in the simulation environment.".
• 131 abstract "The Social Semantic Web has begun to provide connections between users within social networks and the content they produce across the whole of the Social Web. Thus, the Social Semantic Web provides a basis to analyze both the communication behavior of users together with the content of their communication. However, there is little research combining the tools to study communication behaviour and communication content, namely, social network analysis and content analysis. Furthermore, there is even less work addressing the longitudinal characteristics of such a combination. This paper presents a general framework for measuring the dynamic bi-directional influence between communication content and social networks. We apply this framework in two use-cases: online forum discussions and conference publications. The results provide a new perspective over the dynamics involving both social networks and communication content.".
• 135 abstract "Given the large number of Semantic Web Services that can be created from online sources by using existing annotation tools, expressive formalisms and efficient and scalable approaches to solve the service selection problem are required to make these services widely available to the users. In this paper, we propose a framework that is grounded on logic and the Local-As-View approach for representing instances of the service selection problem. In our approach,Web services are semantically described using LAV mappings in terms of generic concepts from an ontology, user requests correspond to conjunctive queries on the generic concepts and, in addition, the user may specify a set of preferences that are used to rank the possible solutions to the given request. The LAV formulation allows us to cast the service selection problem as a query rewriting problem that must consider the relationships among the concepts in the ontology and the ranks induced by the preferences. Then, building on related work, we devise an encoding of the resulting query rewriting problem as a logical theory whose models are in correspondence with the solutions of the user request, and in presence of preferences, whose best models are in correspondence with the best-ranked solutions. Thus, by exploiting known properties of modern SAT solvers, we provide an efficient and scalable solution to the service selection problem. The approach provides the basis to represent a large number of real-world situations and interesting user requests.".
• 144 abstract "We study the problem of SPARQL query optimization on top of distributed hash tables. Existing works on SPARQL query processing in such environments have never been implemented in a real system, or do not utilize any optimization techniques and thus exhibit poor performance. Our goal in this paper is to propose efficient and scalable algorithms for optimizing SPARQL basic graph pattern queries. We augment a known distributed query processing algorithm with query optimization strategies that improve performance in terms of query response time and bandwidth usage. We implement our techniques in the system Atlas and study their performance experimentally in a local cluster.".
• 146 abstract "As knowledge bases move into the landscape of larger ontologies and have terabytes of related data, we must work on optimizing the performance of our tools. We are easily tempted to buy bigger machines or to fill rooms with armies of little ones to address the scalability problem. Yet, careful analysis and evaluation of the characteristics of our data-using metrics-often leads to dramatic improvements in performance. Firstly, are current scalable systems scalable enough? We found that for large or deep ontologies (some as large as 500,000 classes) it is hard to say because benchmarks obscure the load-time costs for materialization. Therefore, to expose those costs, we have synthesized a set of more representative ontologies. Secondly, in designing for scalability, how do we manage knowledge over time? By optimizing for data distribution and ontology evolution, we have reduced the population time, including materialization, for the NCBO Resource Index, a knowledge base of 16.4 billion annotations linking 2.4 million terms from 200 ontologies to 3.5 million data elements, from one week to less than one hour for one of the large datasets on the same machine.".
• 152 abstract "Recently, processing of queries on linked data has gained attention. We identify and systematically discuss three main strategies: a bottom-up strategy that discovers new sources during query processing by following links between sources, a top-down strategy that relies on complete knowledge about the sources to select and process relevant sources, and a mixed strategy that assumes some incomplete knowledge and discovers new sources at run-time. To exploit knowledge discovered at run-time, we propose an additional step, explicitly scheduled during query processing, called correct source ranking. Additionally, we propose the adoption of stream-based query processing to deal with the unpredictable nature of data access in the distributed Linked Data environment. In experiments, we show that our implementation of the mixed strategy leads to early reporting of results and thus, more responsive query processing, while not requiring complete knowledge.".
• 153 abstract "Many applications make use of named entity classification. Machine learning is the preferred technique adopted for many named entity classification methods where the choice of features is critical to final performance. Existing approaches explore only the features derived from the characteristic of the named entity itself or its linguistic context. With the development of the SemanticWeb, a large number of data sources are published and connected across the Web as Linked Open Data (LOD). LOD provides rich a priori knowledge about entity type information, knowledge that can be a valuable asset when used in connection with named entity classification. In this paper, we explore the use of LOD to enhance named entity classification. Our method extracts information from LOD and builds a type knowledge base which is used to score a (named entity string, type) pair. This score is then injected as one or more features into the existing classifier in order to improve its performance. We conducted a thorough experimental study and report the results, which confirm the effectiveness of our proposed method.".
• 158 abstract "Debugging is an important prerequisite for the wide-spread application of ontologies, especially in areas that rely upon everyday users to create and maintain knowledge bases, such as the Semantic Web. Most recent approaches use diagnosis methods to identify sources of inconsistency. However, in most debugging cases these methods return many alternative diagnoses, thus placing the burden of fault localization on the user. This paper demonstrates how the target diagnosis can be identified by performing a sequence of observations, that is, by querying an oracle about entailments of the target ontology. We exploit probabilities of typical user errors to formulate information theoretic concepts for query selection. Our evaluation showed that the suggested method reduces the number of required observations compared to myopic strategies.".
• 167 abstract "Companies, governmental agencies and scientists produce a large amount of quantitative (research) data, consisting of measurements ranging from e.g. the surface temperatures of an ocean to the viscosity of a sample of mayonnaise. Such measurements are stored in tables in e.g. spreadsheet files and research reports. To integrate and reuse such data, it is necessary to have a semantic description of the data. However, the notation used is often ambiguous, making automatic interpretation and conversion to rdf or other suitable format difficult. For example, the table header cell ``f (Hz)'' refers to frequency measured in Hertz, but the symbol ``f'' can also refer to the unit farad or the quantities force or luminous flux. Current annotation tools for this task either work on less ambiguous data or perform a more limited task. We introduce new disambiguation strategies based on an ont, which allows to improve performance on ``sloppy'' datasets not yet targeted by existing systems.".
• 169 abstract "In its core, the Semantic Web is about the creation, collection and interlinking of metadata on which agents can perform tasks for human users. While many tools and approaches support either the creation or usage of semantic metadata, there is neither a proper notion of metadata need, nor a related theory of guidance which metadata should be created. In this paper, we propose to analyze structured queries to help identifying missing metadata. We conduct a study on Semantic MediaWiki (SMW), one of the most popular Semantic Web applications to date, analyzing structured "ask"-queries in public SMWinstances. Based on that, we describe Semantic Need, an extension for SMW which guides contributors to provide semantic annotations, and summarize feedback from an online survey among 30 experienced SMW users.".
• 187 abstract "We study the problem of evolution for Knowledge Bases (KBs) expressed in Description Logics (DLs) of the DL-Lite family. DL-Lite is at the basis of OWL 2 QL, one of the tractable fragments of OWL 2, the recently proposed revision of theWeb Ontology Language.We propose some fundamental principles that KB evolution should respect. We review known model and formula-based approaches for evolution of propositional theories. We exhibit limitations of a number of model-based approaches: besides the fact that they are either not expressible in DL-Lite or hard to compute, they intrinsically ignore the structural properties of KBs, which leads to undesired properties of KBs resulting from such an evolution. We also examine proposals on update and revision of DL KBs that adopt the model-based approaches and discuss their drawbacks. We show that known formula-based approaches are also not appropriate for DL-Lite evolution, either due to high complexity of computation, or because the result of such an action of evolution is not expressible in DL-Lite. Building upon the insights gained, we propose two novel formula-based approaches that respect our principles and for which evolution is expressible in DL-Lite. For our approaches we also developed polynomial time algorithms to compute evolution of DL-Lite KBs.".
• 192 abstract "Analysing the performance of OWL reasoners on expressive OWL ontologies is an ongoing challenge. In this paper, we present a new approach to performance analysis based on justifications for entailments of OWL ontologies. Justifications are minimal subsets of an ontology that are sufficient for an entailment to hold, and are commonly used to debug OWL ontologies. In JustBench, justifications form the key unit of test, which means that individual justifications are tested for correctness and reasoner performance instead of entire ontologies or random subsets. Justifications are generally small and relatively easy to analyse, which makes them very suitable for transparent analytic micro-benchmarks. Furthermore, the JustBench approach also allows us to isolate reasoner errors and inconsistent behaviour. We present the results of initial experiments using JustBench with FaCT++, HermiT, and Pellet. Finally, we show how JustBench can be used by reasoner developers and ontology engineers seeking to understand and improve the performance characteristics of reasoners and ontologies.".
• 199 abstract "Recent technology developments in the area of services on the Web are marked by the proliferation of Web applications and APIs. The implementation and evolution of applications based on Web APIs is, however, hampered by the lack of automation that can be achieved with current technologies. Research on semantic Web services is there fore trying to adapt the principles and technologies that were devised for traditional Web services, to deal with this new kind of services. In this paper we show that currently more than 80% of the Web APIs require some form of authentication. Therefore authentication plays a major role for Web API invocation and should not be neglected in the context of mashups and composite data applications. We present a thorough anal ysis carried out over a body of publicly available APIs that determines the most commonly used authentication approaches. In the light of these results, we propose an ontology for the semantic annotation of Web API authentication information and demonstrate how it can be used to cre ate semantic Web API descriptions. We evaluate the applicability of our approach by providing a prototypical implementation, which uses au thentication annotations as the basis for automated service invocation.".
• 209 abstract "Increasingly user-generated content is being utilised as a source of information, however each individual piece of content tends to contain low levels of information. In addition, such information tends to be informal and imperfect in nature; containing imprecise, subjective, ambiguous expressions. However the content does not have to be interpreted in isolation as it is linked, either explicitly or implicitly, to a network of interrelated content; it may be grouped or tagged with similar content, comments may be added by other users or it may be related to other content posted at the same time or by the same author or members of the author's social network. This paper generally examines how ambiguous concepts within user-generated content can be assigned a specific/formal meaning by considering the expanding context of the information, i.e. other information contained within directly or indirectly related content, and specifically considers the issue of toponym resolution of locations.".
• 218 abstract "The Web of Data currently coming into existence through the Linked Open Data (LOD) effort is a major milestone in realizing the Semantic Web vision. However, the development of applications based on LOD faces difficulties due to the fact that the different LOD datasets are rather loosely connected pieces of information. In particular, links between LOD datasets are almost exclusively on the level of instances, and schema-level information is being ignored. In this paper, we therefore present a system for finding schema-level links between LOD datasets in the sense of ontology alignment. Our system, called BLOOMS, is based on the idea of bootstrapping information already present on the LOD cloud. We also present a comprehensive evaluation which shows that BLOOMS outperforms state-of-the-art ontology alignment systems on LOD datasets. At the same time, BLOOMS is also competitive compared with these other systems on the Ontology Evaluation Alignment Initiative Benchmark datasets.".
• 219 abstract "In this paper we present a method for semantic annotation of texts, which is based on a deep linguistic analysis (DLA) and Inductive Logic Programming (ILP). The combination of DLA and ILP have following benefits: Manual selection of learning features is not needed. The learning procedure has full available linguistic information at its disposal and it is capable to select relevant parts itself. Learned extraction rules can be easily visualized, understood and adapted by human. A description, implementation and initial evaluation of the method are the main contributions of the paper.".
• 225 abstract "Ontological metamodeling has a variety of applications yet only very restricted forms are supported by OWL 2 directly. We propose a novel encoding scheme enabling class-based metamodeling inside the domain ontology with full reasoning support through standard OWL 2 reasoning systems. We demonstrate the usefulness of our method by applying it to the OntoClean methodology. En passant, we address performance problems arising from the inconsistency diagnosis strategy originally proposed for OntoClean by introducing an alternative technique where sources of conflicts are indicated by means of marker predicates.".
• 228 abstract "While the number and size of Semantic Web knowledge bases increases, their maintenance and quality assurance are still difficult. In this article, we present ORE, a tool for repairing and enriching OWL ontologies. State-of-the-art methods in ontology debugging and supervised machine learning form the basis of ORE and are adapted or extended so as to work well in practice. ORE supports the detection of a variety of ontology modelling problems and guides the user through the process of resolving them. Furthermore, the tool allows to extend an ontology through (semi-)automatic supervised learning. A wizard-like process helps the user to resolve potential issues after axioms are added.".
• 234 abstract "Systems based on statistical and machine learning methods have been shown to be extremely effective and scalable for the analysis of large amount of textual data. However, in the recent years, it becomes evident that one of the most important directions of improvement in natural language processing (NLP) tasks, like word sense disambiguation, coreference resolution, relation extraction, and other tasks related to knowledge extraction, is by exploiting semantics. While in the past, the unavailability of rich and complete semantic descriptions constituted a serious limitation of their applicability, nowadays, the Semantic Web made available a large amount of logically encoded information (e.g. ontologies, RDF(S)-data, linked data, etc.), which constitutes a valuable source of semantics. However, web semantics cannot be easily plugged into machine learning systems. Therefore the objective of this paper is to define a reference methodology for combining semantic information available in the web under the form of logical theories, with statistical methods for NLP. The major problems that we have to solve to implement our methodology concern (i) the selection of the correct and minimal knowledge among the large amount available in the web, (ii) the representation of uncertain knowledge, and (iii) the resolution and the encoding of the rules that combine knowledge retrieved from Semantic Web sources with semantics in the text. In order to evaluate the appropriateness of our approach, we present an application of the methodology to the problem of intra-document coreference resolution, and we show by means of some experiments on the standard dataset, how the injection of knowledge leads to the improvement of this task performance.".
• 241 abstract "Facilitating the seamless evolution of RDF knowledge bases on the Semantic Web presents still a major challenge. In this work we devise EvoPat - a pattern-based approach for the evolution and refactoring of knowledge bases. The approach is based on the definition of basic evolution patterns, which are represented declaratively and can capture simple evolution and refactoring operations on both data and schema levels. For more advanced and domain-specific evolution and refactorings, several simple evolution patterns can be combined into a compound one. We performed a comprehensive survey of possible evolution patterns with a combinatorial analysis of all possible before/after combinations, resulting in an extensive catalog of usable evolution patterns. Our approach was implemented as an extension for the OntoWiki semantic collaboration platform and framework.".
• 243 abstract "Formal policies allow the non-ambiguous definition of situations in which usage of certain entities are allowed, and enable the automatic evaluation whether a situation is compliant. This is useful for example in applications using data provided via standardized interfaces. The low technical barriers of integrating such data sources is in contrast to the manual evaluation of natural language policies as they currently exist. Usage situations can themselves be regulated by policies, which can be restricted by the policy of a used entity. Consider for example the Google Maps API, which requires that applications using the API must be available without a fee, i.e. the application's policy must not require a payment. In this paper we present a policy language that can express such constraints on other policies, i.e. a self-policing policy language. We validate our approach by realizing a use case scenario, using a policy engine developed for our language.".
• 247 abstract "Dialogue interaction between customers and products improves presentation of relevant product information in in-store shopping situations. Thus, information needs of customers can be addressed more intuitive. In this article, we describe how access to product information can be improved based on dynamic linkage of heterogeneous knowledge representations. We therefore introduce a conceptual model of dialogue interaction based on multiple knowledge resources for in-store shopping situations and empirically test its utility with end-users.".

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