anchor.diff:  each of them with their own expressivity.
   However, there is no generic client available that can handle querying over multiple interfaces.
   This increases the complexity of combining datasets and designing new interfaces.
  -One can imagine the difficulties that arise
  -when trying to create a client querying various interfaces at the same time,
  +One can imagine the difficulties that arise 
  +when trying to create a client querying various interfaces at the same time, 
   that can be discovered just in time.
   To this end, I aim to design a generic Linked Data querying engine
   capable of handling different interfaces that can easily be extended.
  
positive.code: research_siow_9,9,"Eugene Siow, Thanassis Tiropanis and Wendy Hall",siow,SPARQL-to-SQL on Internet of Things Databases and Streams,research,Streams,2,Eugene Siow,paper_M29_.pdf,501,2016-10-20T13:30:00,2016-10-20T14:50:00,"To realise a semantic Web of Things, the challenge of achieving efficient Resource Description Format (RDF) storage and SPARQL query performance on Internet of Things (IoT) devices with limited resources has to be addressed. State-of-the-art SPARQL-to-SQL engines have been shown to outperform RDF stores on some benchmarks. In this paper, we describe an optimisation to the SPARQL-to-SQL approach, based on a study of time-series IoT data structures, that employs metadata abstraction and efficient translation by reusing existing SPARQL engines to produce Linked Data `just-in-time'. We evaluate our approach against RDF stores, state-of-the-art SPARQL-to-SQL engines and streaming SPARQL engines, in the context of IoT data and scenarios. We show that storage efficiency, with succinct row storage, and query performance can be improved from 2 times to 3 orders of magnitude."
  research_suchanek_10,10,"Fabian M. Suchanek, Colette Menard, Meghyn Bienvenu and Cyril Chapellier",suchanek,Can you imagine... a language for combinatorial creativity?,research,Knowledge Representation,3,Fabian M. Suchanek,paper_M49_.pdf,502,2016-10-19T11:00:00,2016-10-19T12:20:00," Combinatorial creativity combines existing concepts in a novel way in order to produce a new concept. For example, we can imag- ine jewelry that measures blood pressure. For this, we would combine the concept of jewelry with the capabilities of medical devices. Combinato- rial creativity can be used to develop new business ideas, to find plots for books or movies, or simply to disrupt conventional thinking. In this paper, we propose a formal language for combinatorial creativity, based on description logics. We show that our language can be used to model existing inventions and (to a limited degree) to generate new concepts.
  "
  research_taheriyan_30,30,"Mohsen Taheriyan, Craig Knoblock, Pedro Szekely and José Luis Ambite",taheriyan,Leveraging Linked Data to Discover Semantic Relations within Data Sources,research,Enriching Data Sources,2,Mohsen Taheriyan,paper_M107_.pdf,502,2016-10-21T15:30:00,2016-10-21T16:50:00,"Advances in information extraction have enabled the automatic construction of large knowledge graphs (KGs) like DBpedia, Freebase, Yago and Wikidata. These KGs are inevitably bound to be incomplete. To fill in the gaps, data correlations in the KG can be analyzed to infer Horn rules and to predict new facts. However, Horn rules do not take into account possible exceptions, so that predicting facts via such rules introduces errors.
  To overcome this problem,  we present a method for effective revision of learned Horn rules by effectively incorporating exceptions (i.e., negated atoms) into their bodies. This way errors are largely reduced. We apply our method to discover rules with exceptions from real-world KGs. Our experimental results demonstrate the effectiveness of the developed method and the improvements in accuracy for KG completion by rule-based fact prediction."
  research_third_1,1,"Allan Third, George Gkotsis, Eleni Kaldoudi, George Drosatos, Nick Portokallidis, Stefanos Roumeliotis, Kalliopi Pafilis and John Domingue",third,Integrating medical scientific knowledge with the semantically Quantified Self,research,Medical Applications,1,Allan Third,paper_M305_.pdf,501,2016-10-21T13:30:00,2016-10-21T14:50:00,"In recent years RDF and OWL have become the most common knowledge representation languages in use on the Web, propelled by the recommendation of the W3C. In this paper we examine an alternative way to represent knowledge based on Prototypes. This Prototype based representation has different properties, which we argue to be
  more suitable for data sharing and reuse on the Web. Prototypes avoid the distinction between classes and instances and provide means for objects based data sharing and reuse.
  
  In this paper we discuss the requirements and design principles for Knowledge Representation based on Prototypes on the Web, after which we propose a formal syntax and semantics. We show how to embed knowledge representation based on Prototypes in the current Semantic Web standard stack. An implementation and practical evaluation of the system is presented in a separate resource paper."
  research_tiddi_14,14,"Ilaria Tiddi, Mathieu d'Aquin and Enrico Motta",tiddi,Learning to Assess Linked Data Relationships Using Genetic Programming,research,Linked Data Measurement,2,Ilaria Tiddi,paper_M167_.pdf,503,2016-10-20T13:30:00,2016-10-20T14:50:00,"Mapping data to a shared domain ontology is a key step in publishing semantic content on the Web. Most of the work on automatically mapping structured and semi-structured sources to ontologies focuses on semantic labeling, i.e., annotating data fields with ontology classes and/or properties. However, a precise mapping that fully recovers the intended meaning of the data needs to describe the semantic relations between the data fields too. We present a novel approach to automatically discover the semantic relations within a given data source. We mine the small graph patterns occurring in Linked Open Data and combine them to build a graph that will be used to infer semantic relations. We evaluated our approach on datasets from different domains. Mining patterns of maximum length five, our method achieves an average precision of 75% and recall of 77% for a dataset with very complex mappings to the domain ontology, increasing up to 86% and 82%, respectively, for simpler ontologies and mappings."
  research_wudage_25,25,Melisachew Wudage Chekol and Giuseppe Pirrò,wudage,Containment of Expressive SPARQL Navigational Queries,research,Querying,2,Melisachew Wudage Chekol ,research_wudage_25.pdf,502,2016-10-19T14:00:00,2016-10-19T15:20:00,"Query containment is one of the building block of query optimization techniques. In the relational world, query containment is a well-studied problem. At the same time it is well-understood that relational queries are not enough to cope with graph-structured data, where one is interested in expressing queries that capture navigation in the graph. This paper contributes a study on the problem of query containment for an expressive class of navigational queries called Extended Property Paths (EPPs). EPPs are more expressive than previous navigational extensions of SPARQL like property paths and nested regular expressions, for which containment has already been studied. We attack the problem of EPPs (and SPARQL with EPPs) containment and provide complexity bounds.
  "
  research_zhang_20,20,"Lei Zhang, Achim Rettinger and Ji Zhang",zhang,A Probabilistic Model for Time-Aware Entity Recommendation,research,Search (I),4,Lei Zhang,paper_M88_.pdf,502,2016-10-20T13:30:00,2016-10-20T14:50:00,"In recent years, there has been an increasing efforts to develop techniques for related entity recommendation, where the task is to retrieve a ranked list of related entities given a keyword query. Another trend in the area of information retrieval (IR) is to take temporal aspects of a given query into account when assessing the relevance of documents. However, while this has become an established functionality in document search engines, the significance of time, especially when explicitly given, has not been recognized for entity recommendation, yet. We address this gap by introducing the task of time-aware entity recommendation. We propose the first probabilistic model that takes time-awareness into consideration for entity recommendation by leveraging heterogeneous knowledge of entities extracted from different data sources publicly available on the Web. We extensively evaluate the proposed approach and our experimental results show considerable improvements compare to time-agnostic entity recommendation approaches."
  research_zhang_21,21,"Lei Zhang, Achim Rettinger and Ji Zhang",zhang,A Knowledge Base Approach to Cross-lingual Keyword Query Interpretation,research,Search (I),3,Lei Zhang,paper_M90_.pdf,502,2016-10-20T13:30:00,2016-10-20T14:50:00,"The amount of entities in large knowledge bases available on the Web has been increasing rapidly, making it possible to propose new ways of intelligent information access. In addition, there is an impending need for technologies that can enable cross-lingual information access. As a simple and intuitive way of specifying information needs, keyword queries enjoy widespread usage, but suffer from the challenges including ambiguity, incompleteness and cross-linguality. In this paper, we present a knowledge base approach to cross-lingual keyword query interpretation by transforming keyword queries in different languages to their semantic representation, which can facilitate query disambiguation and expansion, and also bridge the language barriers of queries. The experimental results show that our approach achieves both high efficiency and effectiveness and considerably outperforms the baselines."
  research_zhang_38,38,"Xiaowang Zhang, Zhiyong Feng, Xin Wang, Guozheng Rao and Wenrui Wu",zhang,Context-Free Path Queries on RDF Graphs,research,Querying,4,Xiaowang Zhang,paper_M120_.pdf,502,2016-10-19T14:00:00,2016-10-19T15:20:00,"Navigational graph queries are an important class of queries that can extract implicit binary relations over the nodes of input graphs. Most of the navigational query languages used in the RDF community, e.g. property paths in W3C SPARQL 1.1 and nested regular expressions in nSPARQL, are based on the regular expressions. It is known that regular expressions have limited expressivity; for instance, some natural queries, like same generations-queries} are not expressible with regular expressions. To overcome this limitation, in this paper, we present cfSPARQL, an extension of SPARQL query language equipped with context-free grammars. The cfSPARQL language is strictly more expressive than property paths and nested expressions. The additional expressivity can be used for modelling graph similarities, graph summarization and ontology alignment. Despite the increasing expressivity, we show that cfSPARQL still enjoys a low computational complexity and can be evaluated efficiently."
  research_zhu_22,22,"Linhong Zhu, Majid Ghasemi-Gol, Pedro Szekely, Aram Galstyan and Craig Knoblock",zhu,Unsupervised Entity Resolution on Multi-type Graphs,research,Ontology Matching,4,Linhong Zhu,paper_M270_.pdf,503,2016-10-20T10:30:00,2016-10-20T11:50:00,"We address the problem of performing entity resolution on RDF graphs containing multiple types of nodes, using the links between instances of different types to improve the accuracy. For example, in a graph of products and manufacturers the goal is to resolve all the products and all the manufacturers. We formulate this problem as multi-type graph summarization problem, which involves clustering the nodes in each type that refer to the same entity into one super node and creating weighted links among super nodes that summarize the inter-cluster links in the original graph. Experiments show that the proposed approach outperforms several state-of-the-art generic entity resolution approaches, especially in data sets with one-to-many, many-to-many relations and attributes with missing values."
  resource_allik_16,16,"Alo Allik, György Fazekas and Mark Sandler",allik,Ontological Representation of Audio Features,resource,Ontologies (II),3,Alo Allik,paper_R59_.pdf,503,2016-10-21T13:30:00,2016-10-21T14:50:00,"Feature extraction algorithms in Music Informatics aim at deriving statistical and semantic information directly from audio signals. These may be ranging from energies in several frequency bands to musical information such as key, chords or rhythm. There is an increasing diversity and complexity of features and algorithms in this domain and applications call for a common structured representation to facilitate interoperability, reproducibility and machine interpretability. We propose a solution relying on Semantic Web technologies that is designed to serve a dual purpose (1) to represent computational workflows of audio features and (2) to provide a common structure for feature data to enable the use of Open Linked Data principles and technologies in Music Informatics. The Audio Feature Ontology is based on the analysis of existing tools and music informatics literature, which was instrumental in guiding the ontology engineering process. The ontology provides a descriptive framework for expressing different conceptualisations of the audio feature extraction domain and enables designing linked data formats for representing feature data. In this paper, we discuss important modelling decisions and introduce a harmonised ontology library consisting of modular interlinked ontologies that describe the different entities and activities involved in music creation, production and publishing."
  resource_burns_15,15,"Gully Burns, Ulf Hermjakob and José Luis Ambite",burns,Abstract Meaning Representations as Linked Data,resource,Natural Language Processing,2,Gully Burns,paper_R58_.pdf,503,2016-10-21T10:30:00,2016-10-21T11:50:00,"Significant advances in Natural Language Processing (NLP) research are fostered when high-quality annotated corpora were provided for general use. In an effort to develop a sembank (i.e., an annotated corpus dedicated to capturing the semantic meaning of a large set of annotated sentences), NLP researchers have developed the Abstract Meaning Representation (AMR) formulation. Each AMR is a rooted, labeled graph that represents the semantics of a single sentence. Nodes in the core AMR graph represent concepts/entities (such as nouns, PropBank frames, etc.) and edges represent relations between concepts, (such a frame-specific arguments, roles, etc.). AMRs have been used to annotate corpora of classic books, newstext and the biomedical research literature. Research is progressing on creating automatic parsers to generate AMRs directly from textual input. In the work described here, we map the AMR representation to a linked data format (AMR-LD), adopting the ontological formulation of the underlying AMR faithfully. We describe the process of generating AMR-LD data from standard AMRs derived from biomedical research articles, including mapping named entities to well-known linked-data resources, such as Uniprot and PubChem, as well as an open-source software to convert AMR data to RDF. We describe the benefits of AMR-LD, including convenient analysis using SPARQL queries and ontology inferences, and embedding into the web of Linked Data. Finally, we discuss the possible impact of semantic web representations that are directly derived from natural language."
  resource_daniele_3,3,"Laura M. Daniele, Monika Solanki, Frank Den Hartog and Jasper Roes",daniele,Interoperability for Smart Appliances in the IoT World,resource,Smart Planet,4,Laura M. Daniele,paper_R13_.pdf,503,2016-10-19T14:00:00,2016-10-19T15:20:00,"Household appliances are set to become highly intelligent, smart and networked devices in the near future. Systematically deployed on the Internet of Things (IoT), they would be able to form complete energy consuming, producing, and managing ecosystems. Smart systems are technically very heterogeneous, and standardized interfaces on a sensor and device level are therefore needed. However, standardization in IoT has largely focused at the technical communication level, leading to a large number of different solutions based on various standards and protocols, with limited attention to the common semantics contained in the message data structures exchanged at the technical level. The Smart Appliance REFerence ontology (SAREF) is a shared model of consensus developed in close interaction with the industry and with the support of the European Commission. It is published as a technical specification by ETSI and provides an important contribution to achieve semantic interoperability for smart appliances. This paper builds on the success achieved in standardizing SAREF and presents SAREF4EE, an extension of SAREF. SAREF4EE has been created in collaboration with the EEBus and Energy@Home industry associations to interconnect their (different) data models. By using SAREF4EE, smart appliances from different manufacturers that support the EEBus or Energy@Home standards can easily communicate with each other using any energy management system at home or in the cloud."
  resource_du_14,14,"Heshan Du, Vania Dimitrova, Derek Magee, Anthony Cohn, Ross Stirling, Giulio Curioni, Barry Clarke and Helen Reeves",du,An Ontology of Soil Properties and Processes,resource,Ontologies (II),2,Heshan Du,paper_R50_.pdf,503,2016-10-21T13:30:00,2016-10-21T14:50:00,"Assessing the Underworld (ATU) is a large interdisciplinary UK research project addressing urban infrastructure challenges, especially how to make streetworks more efficient and sustainable. One of the key challenges it addresses is integrated inter-asset maintenance. As the assets on the surface of the ground (e.g. pavements) and those buried under it (e.g. pipes and cables) are supported by the ground, the properties and processes of soil affect the performance of these assets to a significant degree. In order to make integrated decisions, it is necessary to combine the knowledge and expertise in multiple areas, such as roads, soil, buried assets, sensing, etc. This requires an underpinning knowledge model, in the form of an ontology. Within this context, we present a new ontology for describing soil properties (e.g. soil strength) and processes (e.g. soil compaction), as well as how they affect each other. This ontology can be used to express how the ground affects and is affected by assets buried under the ground or on the ground surface. The ontology is written in OWL 2 and openly available from the University of Leeds data repository: http://doi.org/10.5518/54."
  resource_ermilov_4,4,"Ivan Ermilov, Jens Lehmann, Michael Martin and Sören Auer",ermilov,LODStats: The Data Web Census Dataset,resource,Linked Data Measurement,3,Ivan Ermilov,paper_R18_.pdf,503,2016-10-20T13:30:00,2016-10-20T14:50:00,"Over the past years, the size of the Data Web has increased significantly, which makes obtaining general insights into its growth and structure both more challenging and more desirable. The lack of such insights hinders important data management tasks such as quality, privacy and coverage analysis. In this paper, we present LODStats, which provides a comprehensive picture of the current state of a significant part of the Data Web. LODStats integrates RDF datasets from data.gov, publicdata.eu and datahub.io data catalogs and at the time of writing lists over 9 000 RDF datasets. For each RDF dataset, LODStats collects comprehensive statistics and makes these available in adhering to the LDSO vocabulary. This analysis has been regularly published and enhanced over the past four years at the public platform lodstats.aksw.org. We give a comprehensive overview over the resulting dataset."
  resource_faralli_10,10,"Stefano Faralli, Alexander Panchenko, Chris Biemann and Simone P. Ponzetto",faralli,Linked Disambiguated Distributional Semantic Networks,resource,Natural Language Processing,1,Stefano Faralli,paper_R37_.pdf,503,2016-10-21T10:30:00,2016-10-21T11:50:00,"We present a new hybrid knowledge base that combines the contextual information of distributional models with the conciseness and precision of manually constructed lexical networks. In contrast to dense vector representations, our resource is human readable and interpretable, and can be easily embedded within the Semantic Web ecosystem. Manual evaluation based on human judgments and an extrinsic evaluation on the task of Word Sense Disambiguation both indicate the high quality of the resource, as well as the benefits of enriching top-down lexical knowledge resources with bottom-up distributional information from text."
  resource_garcia_7,7,"Roberto García, Rosa Gil, Juan Manuel Gimeno, Eirik Bakke and David R. Karger",garcia,BESDUI: A Benchmark for End-User Structured Data User Interfaces,resource,Interaction,2,Roberto García,paper_R27_.pdf,503,2016-10-19T11:00:00,2016-10-19T12:20:00,"The Semantic Web Community has invested significant research effort in developing systems for Semantic Web search and exploration. But while it has been easy to assess the systems' computational efficiency, it has been much harder to assess how well different semantic systems help their users find and browse information. In this article, we propose and demonstrate the use of a benchmark for evaluating them, similar to the TREC benchmark for evaluating traditional search engines. Our benchmark includes a set of typical user tasks and a well-defined procedure for assigning a measure of performance on those tasks to a semantic system. We demonstrate its application to one such system, Rhizomer. We intend for this work to initiate a community conversation that will lead to a general accepted framework for comparing systems and measuring, and thus encouraging, progress towards better semantic search and exploration tools."
  resource_giovanni_6,6,"Andrea Giovanni Nuzzolese, Anna Lisa Gentile, Valentina Presutti and Aldo Gangemi",giovanni,Conference Linked Data: the ScholarlyData project,resource,Linked Data,1,Andrea Giovanni Nuzzolese,paper_R25_.pdf,503,2016-10-20T10:30:00,2016-10-20T11:50:00,"The Semantic Web Dog Food (SWDF) is the reference linked dataset of the Semantic Web community about papers, people, organisations, and events related to its academic conferences. In this paper we analyse the existing problems of generating, representing and maintaining Linked Data for the SWDF. With this work (i) we provide a refactored and cleaned SWDF dataset; (ii) we use a novel data model which improves the Semantic Web Conference Ontology, adopting best ontology design practices and (iii) we provide an open source maintenance workflow to support a healthy grow of the dataset beyond the Semantic Web conferences."
  resource_graux_12,12,"Damien Graux, Louis Jachiet, Pierre Geneves and Nabil Layaida",graux,SPARQLGX: Efficient Distributed Evaluation of SPARQL with Apache Spark,resource,Querying/SPARQL (I),2,Damien Graux,paper_R46_.pdf,501,2016-10-20T10:30:00,2016-10-20T11:50:00,"SPARQL is the W3C standard query language for querying data expressed in the Resource Description Framework (RDF). The increasing amounts of RDF data available raise a major need and research interest in building efficient and scalable distributed SPARQL query evaluators. In this context, we propose and share SPARQLGX: our implementation of a distributed RDF datastore based on Apache Spark. SPARQLGX is designed to leverage existing Hadoop infrastructures for evaluating SPARQL queries. SPARQLGX relies on a translation of SPARQL queries into executable Spark code that adopts evaluation strategies according to (1) the storage method used and (2) statistics on data. We show that SPARQLGX makes it possible to evaluate SPARQL queries on billions of triples distributed across multiple nodes, while providing attractive performance figures. We report on experiments which show how SPARQLGX compares to related state-of-the-art implementations. Using a simple design, SPARQLGX already represents an interesting alternative in several scenarios. We share it as a resource for the further construction of efficient SPARQL evaluators."
  resource_hernandez_20,20,"Daniel Hernandez, Aidan Hogan, Cristian Riveros, Carlos Rojas and Enzo Zerega",hernandez,"Querying Wikidata: Comparing SPARQL, Relational and Graph Databases",resource,Querying/SPARQL (I),3,Daniel Hernandez,paper_R69_.pdf,501,2016-10-20T10:30:00,2016-10-20T11:50:00,"In this paper, we experimentally compare the efficiency of various database engines for the purposes of querying the Wikidata knowledge-base, which can be conceptualised as a directed edge-labelled where edges can be annotated with meta-information called qualifiers. We select two popular SPARQL databases (Virtuoso, Blazegraph), a popular relational database (PostgreSQL), and a popular graph database (Neo4J) for comparison and discuss various options as to how Wikidata can be represented in the models of each engine. We design a set of experiments to test the relative query performance of these representations in the context of their respective engines. We first execute a large set of atomic lookups to establish a baseline performance for each test setting, and subsequently perform experiments on instances of more complex graph patterns based on real-world examples. We conclude with a summary of the strengths and limitations of the engines observed."
  resource_hu_5,5,"Wei Hu, Haoxuan Li, Zequn Sun, Xinqi Qian, Lingkun Xue, Ermei Cao and Yuzhong Qu",hu,Clinga: Bringing Chinese Physical and Human Geography in Linked Open Data,resource,Linked Data,4,Wei Hu,paper_R23_.pdf,503,2016-10-20T10:30:00,2016-10-20T11:50:00,"While the geographical domain has long been involved as an important part of the Linked Data, the small amount of Chinese linked geographical data hinders the integration and sharing of both Chinese and cross-lingual knowledge. In this paper, we contribute to the development of a new Chinese linked geographical dataset named Clinga, by obtaining data from the largest Chinese wiki encyclopedia. We manually design a new geography ontology to categorize a wide range of physical and human geographical entities, and carry out an automatic discovery of links to existing knowledge bases. The resulted Clinga dataset contains over half million Chinese geographical entities and is open access."
  resource_joshi_21,21,"Amit Joshi, Pascal Hitzler and Guozhu Dong",joshi,LinkGen: Multipurpose Linked Data Generator,resource,Linked Data,3,Amit Joshi,paper_R73_.pdf,503,2016-10-20T10:30:00,2016-10-20T11:50:00,"The paper presents a synthetic linked data generator that can generate a large amount of RDF data based on certain statistical distribution. Data generation is platform independent, supports streaming mode and produces output in N-Triples and N-Quad format. Different sets of output can be generated using various configuration parameters and the outputs are reproducible. Unlike existing generators, our generator accepts any vocabulary and can supplement the output with noisy and inconsistent data. The generator has an option to inter-link instances with real ones provided that the user supplies entities from real datasets."
  resource_link_24,24,"Vincent Link, Steffen Lohmann and Florian Haag",link,OntoBench: Generating Custom OWL 2 Benchmark Ontologies,resource,Reasoning,4,Vincent Link,paper_R88_.pdf,503,2016-10-21T15:30:00,2016-10-21T16:50:00,"A variety of tools for visualizing, editing, and documenting OWL ontologies have been developed in the last couple of years. The OWL coverage and conformance of these tools usually needs to be tested during development or for evaluation and comparison purposes. However, in particular for the testing of special OWL concepts and concept combinations, it can be tedious to find suitable ontologies and test cases. We have developed OntoBench, a generator for OWL 2 benchmark ontologies that can be used to test and compare ontology visualizers and related tools. In contrast to existing OWL benchmarks, OntoBench does not focus on scalability and performance but OWL coverage and concept combinations. Consistent benchmark ontologies are dynamically generated based on OWL 2 language constructs selected in a graphical user interface. OntoBench is available on GitHub and as a public service, making it easy to use the tool and generate custom ontologies or ontology fragments."
  resource_loseto_13,13,"Giuseppe Loseto, Saverio Ieva, Filippo Gramegna, Michele Ruta, Floriano Scioscia and Eugenio Di Sciascio",loseto,Linked Data (in low-resource) Platforms: a mapping for Constrained Application Protocol,resource,Knowledge Graphs,4,Giuseppe Loseto,paper_R48_.pdf,501,2016-10-19T11:00:00,2016-10-19T12:20:00,"This paper proposes a mapping of the Linked Data Platform (LDP) specification for Constrained Application Protocol (CoAP). Main motivation stems from the fact that LDP W3C Recommendation presents resource management primitives for HTTP only. Hence, use cases related to Web of Things scenarios, where HTTP-based communication and infrastructures are unfeasible, are partially neglected. A general translation of LDP-HTTP requests and responses is provided, as well as a fully comprehensive framework for HTTP-to-CoAP proxying. The theoretical work is corroborated by an experimental campaign using the W3C Test Suite for LDP."
  resource_mauri_18,18,"Andrea Mauri, Jean-Paul Calbimonte, Daniele Dell'Aglio, Marco Balduini, Marco Brambilla, Emanuele Della Valle and Karl Aberer",mauri,TripleWave: Spreading RDF Streams on the Web,resource,Streams,4,Andrea Mauri,paper_R62_.pdf,501,2016-10-20T13:30:00,2016-10-20T14:50:00,"Processing data streams is increasingly gaining a momentum, given the need to process these flows of information in real time and at Web scale.
  In this context, RDF Stream Processing (RSP) and Stream Reasoning (SR) have emerged as solutions to combine semantic technologies with stream and event processing techniques.
  Research in these areas has proposed an ecosystem of solutions to query, reason and perform real time processing over heterogeneous and distributed data streams on the Web.
  However, so far one basic building block has been missing: a mechanism to disseminate and exchange RDF streams on the Web.
  In this work we close this gap, proposing TripleWave, a reusable and generic tool that enables the publication of RDF streams on the Web.
  The features of TripleWave have been derived from requirements of real use-cases, and consider a diverse set of scenarios, independent of any specific RSP implementation.
  TripleWave can be fed with existing Web streams (e.g. Twitter and Wikipedia streams) or time-annotated RDF datasets (e.g. the LinkedSensorData set), and it can be invoked through both pull- and push-based mechanisms, thus also enabling RSP engines to automatically register and receive data from TripleWave."
  resource_parsia_19,19,"Bijan Parsia, Nicolas Matentzoglu, Rafael S. Gonçalves, Birte Glimm and Andreas Steigmiller",parsia,The OWL Reasoner Evaluation (ORE) 2015 Resources,resource,Reasoning,3,Bijan Parsia,paper_R65_.pdf,503,2016-10-21T15:30:00,2016-10-21T16:50:00,"The OWL Reasoner Evaluation (ORE) Competition is an annual competition (with an associated workshop) which pits OWL 2 compliant reasoners against each other on various standard reasoning tasks over naturally occurring problems. The 2015 competition was the third of its sort and had 14 reasoners competing in six tracks comprising three tasks (consistency, classification, and realisation) over two profiles (OWL 2 DL and EL). In this paper, we outline the design of the competition and present the infrastructure used for its execution: the corpora of ontologies, the competition framework, and the submitted systems. All resources are publicly available on the Web, allowing users to easily re-run the 2015 competition, or reuse any of the ORE infrastructure for reasoner experiments or ontology analysis."
  resource_peroni_8,8,"Silvio Peroni, Giorgia Lodi, Luigi Asprino, Aldo Gangemi and Valentina Presutti",peroni,FOOD: FOod in Open Data,resource,Linked Data,2,Silvio Peroni,paper_R28_.pdf,503,2016-10-20T10:30:00,2016-10-20T11:50:00,"This paper describes the outcome of an e-government project named FOOD, FOod in Open Data, which was carried out in the context of a collaboration between the Institute of Cognitive Sciences and Technologies of the Italian National Research Council, the Italian Ministry of Agriculture (MIPAAF) and the Italian Digital Agency (AgID). In particular, we implemented several ontologies for describing protected names of products (wine, pasta, fish, oil, etc.). In addition, we present the process carried out for producing and publishing a LOD dataset containing data extracted from existing Italian policy documents on such products and compliant with the aforementioned ontologies."
  resource_rebele_2,2,"Thomas Rebele, Fabian M. Suchanek, Johannes Hoffart, Joanna Biega, Erdal Kuzey and Gerhard Weikum",rebele,"YAGO: a Multilingual Knowledge Base from Wikipedia, Wordnet, and Geonames",resource,Multilinguality,1,Thomas Rebele,paper_R4_.pdf,501,2016-10-19T14:00:00,2016-10-19T15:20:00,"YAGO is a large knowledge base that is built automatically from Wikipedia, WordNet and GeoNames. The project combines information from 10 Wikipedias of different languages, thus giving the knowledge a multilingual dimension. It also attaches spatial and temporal information to many facts, and thus allows the user to query the data over space and time. YAGO focuses on extraction quality and achieves a manually evaluated precision of 95%. In this paper, we explain from a general perspective how YAGO is built from its sources, how its quality is evaluated, how a user can access it, and how other projects utilize it."
  resource_ristoski_1,1,"Petar Ristoski, Gerben Klaas Dirk de Vries and Heiko Paulheim",ristoski,A Collection of Benchmark Datasets for Systematic Evaluations of Machine Learning on the Semantic Web,resource,Embeddings & Neural Approaches,2,Petar Ristoski,paper_R1_.pdf,502,2016-10-20T15:30:00,2016-10-20T16:50:00,"In the recent years, several approaches for machine learning on the Semantic Web have been proposed. However, no extensive comparisons between those approaches have been undertaken, in particular due to a lack of publicly available, acknowledged benchmark datasets. In this paper, we present a collection of 22 benchmark datasets at different sizes, derived from existing Semantic Web datasets as well as from external classification and regression problems linked to datasets in the Linked Open Data cloud. Such a collection of datasets can be used to conduct qualitative performance testing and systematic comparisons of approaches."
  resource_solanki_11,11,"Monika Solanki, Bojan Božić, Markus Freudenberg, Dimitris Kontokostas, Christian Dirschl and Rob Brennan",solanki,Enabling combined Software and Data engineering at Web-scale: The ALIGNED suite of Ontologies,resource,Ontologies (II),1,Monika Solanki,paper_R45_.pdf,503,2016-10-21T13:30:00,2016-10-21T14:50:00,"Effective, collaborative integration of software services and big data to develop insightful analytics, for Web-scale systems, is now a crucial techno-economic challenge. This requires new combined data and software engineering processes and tools. Semantic metadata standards such as RDFS and OWL, and linked data principles, provide a technical grounding for such integrated systems given an appropriate model of the domain. In this paper we introduce the ALIGNED suite of ontologies or vocabularies specifically designed to model the information exchange needs of combined software and data engineering processes. The models have been deployed to enable: tool-chain integration, such as the exchange of data quality reports; cross-domain communication, such as interlinked data and software unit testing; mediation of the system design process through the capture of design intents and as a source of context for model-driven software engineering processes. These ontologies are deployed in trial live web-scale, data-intensive system development environments in both the commercial and academic domains. We exemplify the usage of the suite on a complex collaborative software and data engineering scenario from the legal information system domain."
  resource_sygkounas_22,22,"Efstratios Sygkounas, Giuseppe Rizzo and Raphaël Troncy",sygkounas,A Replication Study of the Top Performing Systems in SemEval Twitter Sentiment Analysis,resource,Natural Language Processing,3,Efstratios Sygkounas,paper_R81_.pdf,503,2016-10-21T10:30:00,2016-10-21T11:50:00,"We performed a thorough replicate study of the top systems performing in the yearly SemEval Twitter Sentiment Analysis task. We highlight some differences between the results obtained by the top systems and the ones we are able to compute. We also propose SentiME, an ensemble system composed of 5 state-of-the-art sentiment classifiers. SentiME first trains the different classifiers using the Bootstrap Aggregating Algorithm. The classification results are then aggregated using a linear function that averages the classification distributions of the different classifiers. SentiME has also been tested over the SemEval2015 test set, properly trained with the SemEval2015 train test, outperforming the best ranked system of the challenge. "
  resource_tonon_23,23,"Alberto Tonon, Victor Felder, Djellel Eddine Difallah and Philippe Cudré-Mauroux",tonon,VoldemortKG: Mapping schema.org and Web Entities to Linked Open Data,resource,Knowledge Graphs,1,Alberto Tonon,paper_R87_.pdf,501,2016-10-19T11:00:00,2016-10-19T12:20:00,"Increasingly, Web pages mix entities coming from different sources and represented in several different ways. It can thus happen that the same entity is both described by using schema.org annotations and by creating a text anchor pointing to its Wikipedia page. Often, those representations provide complementary information which is not exploited since those entities are disjoint.
  
  In this project, we explore the extent to which entities represented in different ways repeat on the Web, how they are related, and how they complement (or link) to each other. Our initial experiments show that we can unveil a previously (unexploited) knowledge graph by applying simple instance matching techniques on a large collection of schema.org annotations and DBpedia. The resulting knowledge graph aggregates entities (often tail entities) scattered across several Web pages, and complements existing DBpedia entities with new facts and properties.
  
  In order to facilitate further investigations in how to mine such information, we are releasing i) an excerpt of all CommonCrawl web pages containing both Wikipedia and schema.org annotations, ii) the toolset to extract this information and perform knowledge graph construction and mapping onto DBpedia, as well as iii) the resulting knowledge graph (VoldemortKG) obtained via label matching techniques."
  resource_wang_9,9,"Haofen Wang, Zhijia Fang, Jorge Gracia, Julia Bosque-Gil and Tong Ruan",wang,Zhishi.lemon：On Publishing Zhishi.me as Linguistic Linked Open Data,resource,Multilinguality,3,Haofen Wang,paper_R36_.pdf,501,2016-10-19T14:00:00,2016-10-19T15:20:00,"Recently, a growing number of linguistic resources in different languages have been published and interlinked as part of the Linguistic Linked Open Data (LLOD) cloud. However, in comparison to English and other prominent languages, the presence of Chinese in such a cloud is still limited, despite the fact that Chinese is the most spoken language worldwide. Publishing more Chinese language resources in the LLOD cloud can benefit both academia and industry to better understand the language itself and to further build multilingual applications that will improve the flow of data and services across countries. In this paper, we describe Zhishi.lemon, a newly developed dataset based on the lemon model that constitutes the lexical realization of Zhishi.me, one of the largest Chinese datasets in the Linked Open Data (LOD) cloud. Zhishi.lemon combines the lemon core with the lemon translation module in order to build a linked data lexicon in Chinese with translations into Spanish and English. Links to BabelNet (a vast multilingual encyclopedic resource) have been provided as well. We also present a showcase of this module along with the technical details of transforming Zhishi.me to Zhishi.lemon. We have made the dataset accessible on the Web for both humans (via a Web interface) and software agents (with a SPARQL endpoint)."
  resource_wilmering_17,17,"Thomas Wilmering, György Fazekas and Mark B. Sandler",wilmering,AUFX-O: Novel Methods for the Representation of Audio Processing Workflows,resource,Ontologies (II),4,Thomas Wilmering,paper_R60_.pdf,503,2016-10-21T13:30:00,2016-10-21T14:50:00,"This paper introduces the Audio Effects Ontology (AUFX-O) building on previous theoretical models describing audio processing units and workflows in the context of music production. We discuss important conceptualisations of different abstraction layers, their necessity to successfully model audio effects, and their application method. We present use cases concerning the application of effects in music production projects, and the creation of audio effect metadata facilitating a linked data service exposing information about effect implementations. By doing so, we show how our model benefits knowledge sharing, and enables reproducibility and analysis of audio production workflows."
  
negative.code: As the PhD is still in an early phase, we hope to narrow the scope in the next months,
  based on feedback of the doctoral consortium."
  journal_saleem_6,6,"Muhammad Saleem,  Yasar Khan,  Ali Hasnain,  Ivan Ermilov and Axel-Cyrille Ngonga Ngomo",saleem,A Fine-Grained Evaluation of SPARQL Endpoint Federation Systems,journal,Querying/SPARQL (I),4,Muhammad Saleem,http://www.semantic-web-journal.net/content/fine-grained-evaluation-sparql-endpoint-federation-systems-2,501,2016-10-20T10:30:00,2016-10-20T11:50:00,"The Web of Data has grown enormously over the last years. Currently, it comprises a large compendium of interlinked and distributed datasets from multiple domains. Running complex queries on this compendium often requires accessing data from different endpoints within one query. The abundance of datasets and the need for running complex query has thus motivated a considerable body of work on SPARQL query federation systems, the dedicated means to access data distributed over the Web of Data. However, the granularity of previous evaluations of such systems has not allowed deriving of insights concerning their behavior in different steps involved during federated query processing. In this work, we perform extensive experiments to compare state-of-the-art SPARQL endpoint federation systems using the comprehensive performance evaluation framework FedBench. In addition to considering the tradition query runtime as an evaluation criterion, we extend the scope of our performance evaluation by considering criteria, which have not been paid much attention to in previous studies. In particular, we consider the number of sources selected, the total number of SPARQL ASK requests used, the completeness of answers as well as the source selection time. Yet, we show that they have a significant impact on the overall query runtime of existing systems. Moreover, we extend FedBench to mirror a highly distributed data environment and assess the behavior of existing systems by using the same performance criteria. As the result we provide a detailed analysis of the experimental outcomes that reveal novel insights for improving current and future SPARQL federation systems."
  journal_nuzzolese_1,1,"Andrea Giovanni Nuzzolese, Valentina Presutti, Aldo Gangemi, Silvio Peroni and Paolo Ciancarini",nuzzolese,Aemoo: Linked Data exploration based on Knowledge Patterns,journal,Search (II),3,Andrea Giovanni Nuzzolese,http://dx.doi.org/10.1016/j.websem.2015.12.001,504+505,2016-10-20T15:30:00,2016-10-20T16:50:00,"This paper presents a novel approach to Linked Data exploration that uses Encyclopedic Knowledge Patterns (EKPs) as relevance criteria for selecting, organising, and visualising knowledge. EKP are discovered by mining the linking structure of Wikipedia and evaluated by means of a user-based study, which shows that they are cognitively sound as models for building entity summarisations. We implemented a tool named Aemoo that supports EKP-driven knowledge exploration and integrates data coming from heterogeneous resources, namely static and dynamic knowledge as well as text and Linked Data. Aemoo is evaluated by means of controlled, task-driven user experiments in order to assess its usability, and ability to provide relevant and serendipitous information as compared to two existing tools: Google and RelFinder."
  journal_mazumdar_2,2,"Suvodeep Mazumdar, Daniela Petrelli,  Khadija Elbedweihy,  Vitaveska Lanfranchi and Fabio Ciravegna",mazumdar,Affective Graphs: The Visual Appeal of Linked Data,journal,Interaction,4,Suvodeep Mazumdar,http://www.semantic-web-journal.net/content/affective-graphs-visual-appeal-linked-data,504+505,2016-10-19T11:00:00,2016-10-19T12:20:00,"The essence and value of Linked Data lies in the ability of humans and machines to query, access and reason upon highly structured and formalised data. Ontology structures provide an unambiguous description of the structure and content of data. While a multitude of software applications and visualization systems have been developed over the past years for Linked Data, there is still a significant gap that exists between applications that consume Linked Data and interfaces that have been designed with significant focus on aesthetics. Though the importance of aesthetics in affecting the usability, effectiveness and acceptability of user interfaces have long been recognised, little or no explicit attention has been paid to the aesthetics of Linked Data applications. In this paper, we introduce a formalised approach to developing aesthetically pleasing semantic web interfaces by following aesthetic principles and guidelines identified from literature. We apply such principles to design and develop a generic approach of using visualizations to support exploration of Linked Data, in an interface that is pleasing to users. This provides users with means to browse ontology structures, enriched with statistics of the underlying data, facilitating exploratory activities and enabling visual query for highly precise information needs. We evaluated our approach in three ways: an initial objective evaluation comparing our approach with other well-known interfaces for the semantic web and two user evaluations with semantic web researchers."
  journal_rospocher_8,8,"Marco Rospocher, Marieke van Erp, Piek Vossen, Antske Fokkens, Itziar Aldabe, German Rigau, Aitor Soroa, Thomas Ploeger and Tessel Bogaard",rospocher,Building event-centric knowledge graphs from news,journal,Natural Language Processing,4,Marco Rospocher,http://dx.doi.org/10.1016/j.websem.2015.12.004,504+505,2016-10-21T10:30:00,2016-10-21T11:50:00,"Knowledge graphs have gained increasing popularity in the past couple of years, thanks to their adoption in everyday search engines. Typically, they consist of fairly static and encyclopedic facts about persons and organizations–e.g. a celebrity’s birth date, occupation and family members–obtained from large repositories such as Freebase or Wikipedia. In this paper, we present a method and tools to automatically build knowledge graphs from news articles. As news articles describe changes in the world through the events they report, we present an approach to create Event-Centric Knowledge Graphs (ECKGs) using state-of-the-art natural language processing and semantic web techniques. Such ECKGs capture long-term developments and histories on hundreds of thousands of entities and are complementary to the static encyclopedic information in traditional knowledge graphs. We describe our event-centric representation schema, the challenges in extracting event information from news, our open source pipeline, and the knowledge graphs we have extracted from four different news corpora: general news (Wikinews), the FIFA world cup, the Global Automotive Industry, and Airbus A380 airplanes. Furthermore, we present an assessment on the accuracy of the pipeline in extracting the triples of the knowledge graphs. Moreover, through an event-centered browser and visualization tool we show how approaching information from news in an event-centric manner can increase the user’s understanding of the domain, facilitates the reconstruction of news story lines, and enable to perform exploratory investigation of news hidden facts."""
  journal_gerber_11,11,"Daniel Gerber, Diego Esteves, Jens Lehmann, Lorenz Bühmann, Ricardo Usbeck, Axel-Cyrille Ngonga Ngomo and René Speck",gerber,DeFacto - Temporal and multilingual Deep Fact Validation,journal,Knowledge Graphs,3,Daniel Gerber,http://dx.doi.org/10.1016/j.websem.2015.08.001,501,2016-10-19T11:00:00,2016-10-19T12:20:00,"One of the main tasks when creating and maintaining knowledge bases is to validate facts and provide sources for them in order to ensure correctness and traceability of the provided knowledge. So far, this task is often addressed by human curators in a three-step process: issuing appropriate keyword queries for the statement to check using standard search engines, retrieving potentially relevant documents and screening those documents for relevant content. The drawbacks of this process are manifold. Most importantly, it is very time-consuming as the experts have to carry out several search processes and must often read several documents. In this article, we present DeFacto (Deep Fact Validation)—an algorithm able to validate facts by finding trustworthy sources for them on the Web. DeFacto aims to provide an effective way of validating facts by supplying the user with relevant excerpts of web pages as well as useful additional information including a score for the confidence DeFacto has in the correctness of the input fact. To achieve this goal, DeFacto collects and combines evidence from web pages written in several languages. In addition, DeFacto provides support for facts with a temporal scope, i.e., it can estimate in which time frame a fact was valid. Given that the automatic evaluation of facts has not been paid much attention to so far, generic benchmarks for evaluating these frameworks were not previously available. We thus also present a generic evaluation framework for fact checking and make it publicly available."
  journal_mccrae_7,7,"John P. McCrae, Mihael Arcan, Kartik Asooja, Jorge Gracia, Paul Buitelaar and Philipp Cimiano",mccrae,Domain Adaptation for Ontology Localization,journal,Multilinguality,4,John P. McCrae,http://dx.doi.org/10.1016/j.websem.2015.12.001,501,2016-10-19T14:00:00,2016-10-19T15:20:00,"Ontology localization is the task of adapting an ontology to a different cultural context, and has been identified as an important task in the context of the Multilingual Semantic Web vision. The key task in ontology localization is translating the lexical layer of an ontology, i.e., its labels, into some foreign language. For this task, we hypothesize that the translation quality can be improved by adapting a machine translation system to the domain of the ontology. To this end, we build on the success of existing statistical machine translation (SMT) approaches, and investigate the impact of different domain adaptation techniques on the task. In particular, we investigate three techniques: (i) enriching a phrase table by domain-specific translation candidates acquired from existing Web resources, (ii) relying on Explicit Semantic Analysis as an additional technique for scoring a certain translation of a given source phrase, as well as (iii) adaptation of the language model by means of weighting n-grams with scores obtained from topic modelling. We present in detail the impact of each of these three techniques on the task of translating ontology labels. We show that these techniques have a generally positive effect on the quality of translation of the ontology and that, in combination, they provide a significant improvement in quality. "
  journal_arenas_12,12,"Marcelo Arenas, Bernardo Cuenca Grau, Evgeny Kharlamov, Šarūnas Marciuška and Dmitriy Zheleznyakov",arenas,Faceted search over RDF-based knowledge graphs,journal,Search (II),2,Marcelo Arenas,http://dx.doi.org/10.1016/j.websem.2015.12.002,504+505,2016-10-20T15:30:00,2016-10-20T16:50:00,"Knowledge graphs such as Yago and Freebase have become a powerful asset for enhancing search, and are being intensively used in both academia and industry. Many existing knowledge graphs are either available as Linked Open Data, or they can be exported as RDF datasets enhanced with background knowledge in the form of an OWL 2 ontology. Faceted search is the de facto approach for exploratory search in many online applications, and has been recently proposed as a suitable paradigm for querying RDF repositories. In this paper, we provide rigorous theoretical underpinnings for faceted search in the context of RDF-based knowledge graphs enhanced with OWL 2 ontologies. We identify well-defined fragments of SPARQL that can be naturally captured using faceted search as a query paradigm, and establish the computational complexity of answering such queries. We also study the problem of updating faceted interfaces, which is critical for guiding users in the formulation of meaningful queries during exploratory search. We have implemented our approach in a fully-fledged faceted search system, SemFacet, which we have evaluated over the Yago knowledge graph."
  journal_vandenbussche_3,3,"Pierre-Yves Vandenbussche, Ghislain A. Atemezing, Maria Poveda and Bernard Vatant",vandenbussche,Linked Open Vocabularies (LOV): a gateway to reusable semantic vocabularies on the Web,journal,Ontologies (I),1,Pierre-Yves Vandenbussche,http://www.semantic-web-journal.net/content/linked-open-vocabularies-lov-gateway-reusable-semantic-vocabularies-web-1,501,2016-10-20T15:30:00,2016-10-20T16:50:00,"One of the major barriers to the deployment of Linked Data is the difficulty that data publishers have in determining which vocabularies to use to describe the semantics of data. This system report describes Linked Open Vocabularies (LOV), a high quality catalogue of reusable vocabularies for the description of data on the Web. The LOV initiative gathers and makes visible indicators that have not been previously harvested such as the interconnections between vocabularies, version history along with past and current referent (individual or organization). The report details the various components of the system along with some innovations such as the introduction of a property-level boost in the vocabulary search scoring which takes into account the property's type (e.g rdfs:label, dc:comment) associated with a matching literal value. By providing an extensive range of data access methods (full-text search, SPARQL endpoint, API, data dump or UI), the project aims at facilitating the reuse of well-documented vocabularies in the Linked Data ecosystem. The adoption of LOV by many applications and methods shows the importance of such a set of vocabularies and related features for the ontology design activity and the publication of data on the Web."
  journal_calvanese_4,4,"Diego Calvanese, Benjamin Cogrel, Sarah Komla-Ebri, Roman Kontchakov, Davide Lanti, Martin Rezk, Mariano Rodriguez-Muro and Guohui Xiao",calvanese,Ontop: Answering SPARQL queries over relational databases,journal,Querying/SPARQL (II),3,Diego Calvanese,http://www.semantic-web-journal.net/content/ontop-answering-sparql-queries-over-relational-databases-1,502,2016-10-21T13:30:00,2016-10-21T14:50:00,"We present Ontop, an open-source Ontology-Based Data Access (OBDA) system that allows for querying relational data sources through a conceptual representation of the domain of interest, provided in terms of an ontology, to which the data sources are mapped. Key features of Ontop are its solid theoretical foundations, a virtual approach to OBDA, which avoids materializing triples and is implemented through the query rewriting technique, extensive optimizations exploiting all elements of the OBDA architecture, its compliance to all relevant W3C recommendations (including SPARQL queries, R2RML mappings, and OWL 2 QL and RDFS ontologies), and its support for all major relational databases."
  journal_lephuoc_9,9,Danh Le-Phuoc,lephuoc,Operator-aware approach for boosting performance in RDF stream processing,journal,Streams,3,Danh Le-Phuoc,http://dx.doi.org/10.1016/j.websem.2016.04.001,501,2016-10-20T13:30:00,2016-10-20T14:50:00,"To enable efficiency in stream processing, the evaluation of a query is usually performed over bounded parts of (potentially) unbounded streams, i.e., processing windows “slide” over the streams. To avoid inefficient re-evaluations of already evaluated parts of a stream in respect to a query, incremental evaluation strategies are applied, i.e., the query results are obtained incrementally from the result set of the preceding processing state without having to re-evaluate all input buffers. This method is highly efficient but it comes at the cost of having to maintain processing state, which is not trivial, and may defeat performance advantages of the incremental evaluation strategy. In the context of RDF streams the problem is further aggravated by the hard-to-predict evolution of the structure of RDF graphs over time and the application of sub-optimal implementation approaches, e.g., using relational technologies for storing data and processing states which incur significant performance drawbacks for graph-based query patterns. To address these performance problems, this paper proposes a set of novel operator-aware data structures coupled with incremental evaluation algorithms which outperform the counterparts of relational stream processing systems. This claim is demonstrated through extensive experimental results on both simulated and real datasets."
  journal_zaveri_5,5,"Amrapali Zaveri, Anisa Rula, Andrea Maurino, Ricardo Pietrobon, Jens Lehmann and Sören Auer",zaveri,Quality Assessment for Linked Data: A Survey,journal,Linked Data Measurement,4,Amrapali Zaveri,http://www.semantic-web-journal.net/content/quality-assessment-linked-data-survey,504+505,2016-10-20T13:30:00,2016-10-20T14:50:00,"The development and standardization of semantic web technologies has resulted in an unprecedented volume of data being published on the Web as Linked Data (LD). However, we observe widely varying data quality ranging from extensively curated datasets to crowdsourced and extracted data of relatively low quality. In this article, we present the results of a systematic review of approaches for assessing the quality of LD. We gather existing approaches and analyze them qualitatively. In particular, we unify and formalize commonly used terminologies across papers related to data quality and provide a comprehensive list of 18 quality dimensions and 69 metrics. Additionally, we qualitatively analyze the 30 core approaches and 12 tools using a set of attributes. The aim of this article is to provide researchers and data curators a comprehensive understanding of existing work, thereby encouraging further experimentation and development of new approaches focused towards data quality, specifically for LD."
  journal_vegagorgojo_10,10,"Guillermo Vega-Gorgojo, Laura Slaughter, Martin Giese, Simen Heggestøyl, Ahmet Soylu and Arild Waaler",vegagorgojo,Visual query interfaces for semantic datasets: an evaluation study,journal,Interaction,3,Guillermo Vega-Gorgojo,http://dx.doi.org/10.1016/j.websem.2016.01.002,504+505,2016-10-19T11:00:00,2016-10-19T12:20:00,"The rapid growth of the Linked Open Data cloud, as well as the increasing ability to lift relational enterprise datasets to a semantic, ontology-based level means that vast amounts of information are now available in a representation that closely matches the conceptualizations of the potential users of this information. This makes it interesting to create ontology based, user-oriented tools for searching and exploring this data. Although initial efforts were intended for tech users with knowledge of SPARQL/RDF, there are ongoing proposals designed for lay users. One of the most promising approaches is to use visual query interfaces, but more user studies are needed to assess their effectiveness. In this paper, we compare the effect on usability of two important paradigms for ontology-based query interfaces: form-based and graph-based interfaces. In order to reduce the number of variables affecting the comparison, we performed a user study with two state-of-the-art query tools developed by ourselves, sharing a large part of the code base: the graph-based tool OptiqueVQS*, and the form-based tool PepeSearch. We evaluated these tools in a formal comparison study with 15 participants searching a Linked Open Data version of the Norwegian Company Registry. Participants had to respond to 6 non-trivial search tasks using alternately OptiqueVQS* and PepeSearch. Even without previous training, retrieval performance and user confidence were very high, thus suggesting that both interface designs are effective for searching RDF datasets. Expert searchers had a clear preference for the graph-based interface, and mainstream searchers obtained better performance and confidence with the form-based interface. While a number of participants spontaneously praised the capability of the graph interface for composing complex queries, our results evidence that graph interfaces are difficult to grasp. In contrast, form interfaces are more learnable and relieve problems with disorientation for mainstream users. We have also observed positive results introducing faceted search and dynamic term suggestion in semantic search interfaces."
  poster_takatsuki_10,10,"Terue Takatsuki, Mikako Saito, Sadahiro Kumagai, Eiki Takayama, Kazuya Ohshima, Nozomu Ohshiro, Kai Lenz, Nobuhiko Tanaka, Norio Kobayashi and Hiroshi Masuya",takatsuki,A RDF based Portal of Biological Phenotype Data produced in Japan,poster,Poster,25,Terue Takatsuki,paper10.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_yu_70,70,"Ran Yu, Besnik Fetahu, Ujwal Gadiraju and Stefan Dietze",yu,A Survey on Challenges in Web Markup Data for Entity Retrieval,poster,Poster,54,Ran Yu,paper70.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_yoon_85,85,"Seungjun Yoon, Sejin Chun, Xiongnan Jin and Kyong-Ho Lee",yoon,A Unified Interface for Optimizing Continuous Query in Heterogeneous RDF Stream Processing Systems,poster,Poster,50,Seungjun Yoon,paper85.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_sungmin_31,31,"Joo Sungmin, Seiji Koide, Hideaki Takeda, Daisuke Horyu, Akane Takezaki and Tomokazu Yoshida",sungmin,Agriculture Activity Ontology : An ontology for core vocabulary of agriculture activity,poster,Poster,21,Joo Sungmin,paper31.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_lanti_82,82,"Davide Lanti, Guohui Xiao and Diego Calvanese",lanti,An Evaluation of VIG with the BSBM Benchmark,poster,Poster,52,Davide Lanti,paper82.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_zhao_44,44,"Lihua Zhao, Naoya Arakawa, Hiroaki Wagatsuma and Ryutaro Ichise",zhao,An Ontology based Map Converter for Intelligent Vehicles,poster,Poster,3,Lihua Zhao,paper44.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_ren_43,43,"Xiangnan Ren, Olivier Curé, Houda Khrouf, Zakia Kazi-Aoul and Yousra Chabchoub",ren,Apache Spark and Apache Kafka at the rescue of distributed RDF Stream Processing engines,poster,Poster,48,Xiangnan Ren,paper43.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_mei_8,8,"Jing Mei, Wen Sun, Jing Li, Haifeng Liu, Xiang Li, Yiqin Yu and Guotong Xie",mei,Building Evidence Graph for Clinical Decision Support,poster,Poster,26,Jing Mei,paper8.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_urakawa_15,15,"Makoto Urakawa, Masaru Miyazaki, Hiroshi Fujisawa, Masahide Naemura and Ichiro Yamada",urakawa,Constructing Curriculum Ontology and Dynamic Learning Path Based on Resource Description Framework,poster,Poster,44,Makoto Urakawa,paper15.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_takaai_94,94,Motoyuki Takaai and Yohei Yamane,takaai,Constructing Semantic Networks of Development Activities from Weekly Reports,poster,Poster,16,Motoyuki Takaai ,paper94.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_song_90,90,"Yuting Song, Taisuke Kimura, Biligsaikhan Batjargal and Akira Maeda",song,Cross-Language Record Linkage using Word Embedding driven Metadata Similarity Measurement,poster,Poster,14,Yuting Song,paper90.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_yamaguchi_95,95,"Atsuko Yamaguchi, Kouji Kozaki, Kai Lenz, Yasunori Yamamoto, Hiroshi Masuya and Norio Kobayashi",yamaguchi,Data Acquisition by Traversing Class-Class Relationships over the Linked Open Data,poster,Poster,22,Atsuko Yamaguchi,paper95.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_agtrickauer_104,104,"Henning Agt-Rickauer, Jörg Waitelonis, Tabea Tietz and Harald Sack",agtrickauer,Data Integration for the Media Value Chain,poster,Poster,10,Henning Agt-Rickauer,paper104.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_fang_107,107,"Lu Fang, Qingliang Miao and Yao Meng",fang,DBpedia Entity Type Inference Using Categories,poster,Poster,42,Lu Fang,paper107.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_kume_93,93,"Satoshi Kume, Hiroshi Masuya, Yosky Kataoka and Norio Kobayashi",kume,Development of an Ontology for an Integrated Image Analysis Platform to enable Global Sharing of Microscopy Imaging Data,poster,Poster,23,Satoshi Kume,paper93.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_demeester_110,110,"Ben De Meester, Anastasia Dimou, Ruben Verborgh and Erik Mannens",demeester,Discovering and Using Functions via Content Negotiation,poster,Poster,41,Ben De Meester,paper110.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_solanki_19,19,"Monika Solanki, Bojan Bozic, Markus Freudenberg, Dimitris Kontokostas, Rob Brennan and Christian Dirschl",solanki,Enabling combined software and data engineering: the ALIGNED suite of ontologies,poster,Poster,45,Monika Solanki,paper19.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_liu_53,53,"Zhihui Liu, Weimin Ge, Xiaowang Zhang and Zhiyong Feng",liu,Enhancing Rule-based OWL Reasoning on Spark,poster,Poster,37,Zhihui Liu,paper53.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_martin_72,72,Peter Patel-Schneider and David Martin,martin,EXISTStential Aspects of SPARQL,poster,Poster,28,Peter Patel-Schneider ,paper72.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_mirza_4,4,"Paramita Mirza, Simon Razniewski and Werner Nutt",mirza,"Expanding Wikidata's Parenthood Information by 178%, or How To Mine Relation Cardinality Information",poster,Poster,18,Paramita Mirza,paper4.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_nuzzolese_56,56,"Andrea Giovanni Nuzzolese, Anna Lisa Gentile, Valentina Presutti and Aldo Gangemi",nuzzolese,Generating Conference Linked Open Data in One Click,poster,Poster,19,Andrea Giovanni Nuzzolese,paper56.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_fionda_67,67,"Valeria Fionda, Melisachew Wudage Chekol and Giuseppe Pirrò",fionda,Gize: A Time Warp in the Web of Data,poster,Poster,43,Valeria Fionda,paper67.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_rinciog_76,76,Octavian Rinciog and Vlad Posea,rinciog,GovLOD: Towards to a Linked Open Data Portal,poster,Poster,4,Octavian Rinciog ,paper76.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_basharat_96,96,"Amna Basharat, Khaled Rasheed and I. Budak Arpinar",basharat,Harnessing Crowds and Experts for Semantic Annotation of the Qur'an,poster,Poster,31,Amna Basharat,paper96.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_pareti_28,28,Paolo Pareti,pareti,Human-Machine Collaboration over Linked Data,poster,Poster,2,Paolo Pareti,paper28.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_morita_106,106,"Takeshi Morita, Yu Sugawara, Ryota Nishimura and Takahira Yamaguchi",morita,Implementing Customer Reception Service in Robot Cafe using Stream Reasoning and ROS based on PRINTEPS,poster,Poster,8,Takeshi Morita,paper106.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_wilmering_60,60,Thomas Wilmering and Mark B. Sandler,wilmering,Interdisciplinary Classification of Audio Effects in the Audio Effect Ontology,poster,Poster,47,Thomas Wilmering ,paper60.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_zhang_40,40,"Junzhao Zhang, Bingyi Zhang, Xiaowang Zhang and Zhiyong Feng",zhang,IRSMG: Accelerating Inexact RDF Subgraph Matching on the GPU,poster,Poster,34,Junzhao Zhang,paper40.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_peroni_86,86,"Silvio Peroni, David Shotton and Fabio Vitali",peroni,Jailbreaking your reference lists: the OpenCitations project strikes again,poster,Poster,30,Silvio Peroni,paper86.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_mccrae_23,23,John P. McCrae and Philipp Cimiano,mccrae,"LIXR: Quick, succinct conversion of XML to RDF",poster,Poster,55,John P. McCrae ,paper23.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_seydoux_101,101,"Nicolas Seydoux, Khalil Drira, Nathalie Hernandez and Thierry Monteil",seydoux,Lowering knowledge : Making constrained devices semantically interoperable,poster,Poster,6,Nicolas Seydoux,paper101.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_gandon_41,41,"Fabien Gandon, Raphaël Boyer, Olivier Corby and Alexandre Monnin",gandon,Materializing the editing history of Wikipedia as linked Data in DBpedia,poster,Poster,17,Fabien Gandon,paper41.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_saif_66,66,"Hassan Saif, Miriam Fernandez, Matthew Rowe and Harith Alani",saif,On the Role of Semantics for Detecting pro-ISIS Stances on Social Media,poster,Poster,32,Hassan Saif,paper66.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_harrow_57,57,"Ian Harrow, Martin Romacker, Andrea Splendiani, Stefan Negru, Peter Woollard, Scott Markel, Yasmin Alam-Faruque, Martin Koch, Erfan Younesi, James Malone and Ernesto Jimenez-Ruiz",harrow,Ontologies Guidelines for Best Practice and a Process to Evaluate Existing Ontologies Mapping Tools and Algorithms,poster,Poster,46,Ian Harrow,paper57.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_subercaze_50,50,Julien Subercaze and Christophe Gravier,subercaze,Parallel sort-merge-join reasoning,poster,Poster,39,Julien Subercaze ,paper50.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_ongenae_100,100,"Femke Ongenae, Femke De Backere, Jelle Nelis, Stijn De Pestel, Christof Mahieu, Shirley Elprama, Charlotte Jewell, An Jacobs, Pieter Simoens and Filip De Turck",ongenae,Personalized robot interactions to intercept behavioral disturbances of people with dementia,poster,Poster,7,Femke Ongenae,paper100.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_chun_49,49,"Sejin Chun, Jooik Jung, Xiongnan Jin, Seungjun Yoon and Kyong-Ho Lee",chun,Proactive Replication of Dynamic Linked Data for Scalable RDF Stream Processing,poster,Poster,49,Sejin Chun,paper49.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_song_17,17,"Zhenyu Song, Xiaowang Zhang and Zhiyong Feng",song,PRONA: A Plugin for Well-Designed Approximate Queries in Jena,poster,Poster,35,Zhenyu Song,paper17.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_fang_18,18,Hong Fang and Xiaowang Zhang,fang,pSPARQL: A Querying Language for Probabilistic RDF (Extended Abstract),poster,Poster,36,Hong Fang ,paper18.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_nguyen_7,7,Khai Nguyen and Ryutaro Ichise,nguyen,Ranking Feature for Classifier-based Instance Matching,poster,Poster,33,Khai Nguyen ,paper7.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_hartig_21,21,Olaf Hartig and Carlos Buil-Aranda,hartig,Reducing the Network Load of Triple Pattern Fragments by Supporting Bind Joins,poster,Poster,53,Olaf Hartig ,paper21.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_lenz_34,34,"Kai Lenz, Hiroshi Masuya and Norio Kobayashi",lenz,RIKEN MetaDatabase: a Database Publication Platform for RIKENs Life-science Researchers that Promotes Research Collaborations over Different Research Area,poster,Poster,24,Kai Lenz,paper34.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_de_paepe_55,55,"Dieter De Paepe, Ruben Verborgh and Erik Mannens",de paepe,Rule-Based Reasoning using State Space Search,poster,Poster,40,Dieter De Paepe,paper55.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_ternai_81,81,Katalin Ternai and Ildikó Szabó,ternai,Semantic Audit Application,poster,Poster,29,Katalin Ternai ,paper81.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_konstantpopoulos_33,33,"Stasinos Konstantopoulos, Angelos Charalambidis, Giannis Mouchakis, Antonis Troumpoukis, Jürgen Jakobitsch and Vangelis Karkaletsis",konstantpopoulos,Semantic Web Technologies and Big Data Infrastructures: SPARQL Federated Querying of Heterogeneous Big Data Stores,poster,Poster,27,Stasinos Konstantopoulos,paper33.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_debruyne_14,14,"Christophe Debruyne, Eamonn Clinton, Lorraine McNerney, Atul Nautiyal and Declan O'Sullivan",debruyne,Serving Ireland's Geospatial Information as Linked Data,poster,Poster,5,Christophe Debruyne,paper14.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_jouault_45,45,"Corentin Jouault, Kazuhisa Seta and Yuki Hayashi",jouault,SOLS: A Semantically Enriched Learning System Using LOD Based Automatic Question Generation,poster,Poster,11,Corentin Jouault,paper45.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_blinkiewicz_62,62,Jarosław Bąk and Michał Blinkiewicz,blinkiewicz,SQuaRE: A Visual Tool For Creating R2RML Mappings,poster,Poster,9,Jarosław Bąk ,paper62.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_wang_64,64,"Changlong Wang, Xiaowang Zhang and Zhiyong Feng",wang,Structure-guiding Modular Reasoning for Expressive Ontologies,poster,Poster,38,Changlong Wang,paper64.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_zhang_36,36,"Wei Emma Zhang, Ermyas Abebe, Quan Z. Sheng and Kerry Taylor",zhang,Towards Building Open Knowledge Base From Programming Question-Answering Communities,poster,Poster,13,Wei Emma Zhang,paper36.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_gravier_51,51,Christophe Gravier and Julien Subercaze,gravier,USE-RB : Benchmarking how Reasoners Work in Harmony with Modern Hardware,poster,Poster,51,Christophe Gravier ,paper51.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_wohlgenannt_37,37,Gerhard Wohlgenannt and Filip Minic,wohlgenannt,Using word2vec to Build a Simple Ontology Learning System,poster,Poster,15,Gerhard Wohlgenannt ,paper37.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_gassen_65,65,"Jonas Bulegon Gassen, Stefano Faralli, Simone Paolo Ponzetto and Jan Mendling",gassen,Who-Does-What: A Knowledge Base of People's Occupations and Job Activities,poster,Poster,20,Jonas Bulegon Gassen,paper65.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_watanabe_11,11,"Masao Watanabe, Kazunari Hashimoto, Seiya Inagi, Yohei Yamane, Seiji Suzuki and Hiroshi Umemoto",watanabe,Working Process Quantification in Factory Using Wearable Sensor Device and Ontology-based Stream Data Processing,poster,Poster,1,Masao Watanabe,paper11.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  poster_lee_103,103,"Jongmin Lee, Youngkyoung Ham and Tony Lee",lee,XB: A Large-scale Korean Knowledge Base for Question Answering Systems,poster,Poster,12,Jongmin Lee,paper103.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,
  research_alshukali_8,8,"Duhai Alshukaili, Alvaro A. A. Fernandes and Norman Paton",alshukali,Structuring Linked Data Search Results Using Probabilistic Soft Logic,research,Search (I),2,Duhai Alshukaili,paper_M38_.pdf,502,2016-10-20T13:30:00,2016-10-20T14:50:00,"On-the-fly generation of integrated representations of Linked Data (LD)
    search results is challenging because it requires successfully automating a number
    of complex subtasks, such as structure inference and matching of
    both instances and concepts, each of which gives rise to uncertain
    outcomes. Such uncertainty is unavoidable given the semantically heterogeneous
    nature of web sources, including LD ones. This paper approaches the problem of 
    structuring LD search results as an evidence-based one. In particular, the paper shows 
    how one formalism (viz., probabilistic soft logic (PSL)) can be exploited to assimilate
    different sources of evidence in a principled way and to beneficial
    effect for users. The paper considers syntactic evidence derived from matching
    algorithms, semantic evidence derived from LD vocabularies, and user
    evidence, in the form of feedback. The main contributions are: sets 
    of PSL rules that model the uniform assimilation of diverse kinds of evidence, 
    an empirical evaluation of how the resulting PSL programs perform in terms 
    of their ability to infer structure in LD search results, and, finally, a concrete
    example of how populating such inferred structures for presentation
    to the end user is beneficial, besides enabling the collection of
    feedback whose assimilation further improves search result presentation."
  research_angles_33,33,Renzo Angles and Claudio Gutierrez,angles,The multiset semantics of SPARQL patterns,research,Querying,1,Renzo Angles ,paper_M232_.pdf,502,2016-10-19T14:00:00,2016-10-19T15:20:00,"The paper determines the algebraic and logic structure produced by  the multiset semantics of the core patterns of SPARQL. We prove that the fragment formed by AND, UNION, OPTIONAL, FILTER, MINUS and SELECT corresponds precisely to both, the intuitive multiset relational algebra (projection, selection, natural join, arithmetic union and except), and multiset classical non-recursive Datalog with safe negation."
  research_bereta_19,19,Konstantina Bereta and Manolis Koubarakis,bereta,Ontop of Geospatial Databases,research,Querying/SPARQL (II),4,Konstantina Bereta ,paper_M98_.pdf,502,2016-10-21T13:30:00,2016-10-21T14:50:00,"In this paper we propose an OBDA approach for accessing geospatial data stored in geospatial relational databases, using the OGC standard GeoSPARQL and R2RML or OBDA mappings. We introduce  extensions  to existing SPARQL-to-SQL approaches to support GeoSPARQL features. We describe the implementation of our approach in the system ontop-spatial, an extension of the OBDA system Ontop for creating  virtual geospatial RDF graphs on top of geospatial relational databases. Last, we present an experimental evaluation of our system using workload and queries from a  recent benchmark. In order to measure the performance of our system,  we compare it to the state-of-the-art geospatial RDF store, and confirm its efficiency."
  research_brasileiro_11,11,"Freddy Brasileiro, Joao Paulo Almeida, Victorio Albani Carvalho and Giancarlo Guizzardi",brasileiro,Expressive Multi-Level Modeling for the Semantic Web,research,Knowledge Representation,4,Freddy Brasileiro,paper_M177_.pdf,502,2016-10-19T11:00:00,2016-10-19T12:20:00,"The assessment of risk in medicine is a crucial task, depending on scientific knowledge derived by rigorous clinical studies regarding the (quantified) factors affecting biological changes, as well as on particular knowledge about the current status of a particular patient. Existing non-semantic risk prediction tools are typically based on hardcoded scientific knowledge, and only cover a very limited range of patient states. This makes them rapidly out of date, and limited in application, particularly for patients with co-morbidities (multiple co-occurring conditions). Semantic Web and Quantified Self technologies make it possible to address this task in a much more principled way, to maximise knowledge and data reuse and minimise maintenance requirements while enabling new and sophisticated applications involving widely-available biometric sensors. 
  
  We present a framework for calculating clinical risk predictions for patients based on automatically-gathered biometric data. This framework relies on generic, reusable ontologies for representing clinical risk, and sensor readings, and reasoning to support the integration of data represented according to these ontologies. This integration makes novel use of Semantic Web technologies, and supports straightforward extension and maintenance by medical professionals. The framework is evaluated in terms of its predictions, extensibility and ease of use for domain experts."
  research_carral_6,6,"David Carral, Cristina Feier and Pascal Hitzler",carral,A Practical Acyclicity Notion for Query Answering over Horn-SRIQ Ontologies,research,Reasoning,1,David Carral,paper_M202_.pdf,504+505,2016-10-21T15:30:00,2016-10-21T16:50:00,"Conjunctive query answering over expressive Horn Description Logic ontologies is a relevant and challenging problem which, in some cases, can be addressed by application of the chase algorithm.
  In this paper, we define a novel acyclicity notion which provides sufficient condition for termination of the restricted chase over Horn-SRIQ ontologies.
  We show that our notions generalize most of the existing acyclicity conditions (both theoretically and empirically) and its use results in a more efficient reasoning procedure.
  Furthermore, we implement a materialization based reasoner for acyclic ontologies which vastly outperforms state-of-the-art reasoners.
  