anchor.diff:  applications. We describe SQuaRE’s main features, its architecture as
   well as technical details."
   application_47,47,"Gregoire Burel, Lara S. G. Piccolo and Harith Alani",Burel,EnergyUse - A Collaborative Semantic Platform for Monitoring and Discussing Energy Consumption,application,Smart Planet,3,Gregoire Burel,application_47.pdf,504+505,2016-10-19T14:40:00,2016-10-19T15:00:00,"Conserving fossil-based energy to reduce carbon emissions is key to slowing down global warming. The 2015 Paris agreement on climate change emphasised the importance of raising public awareness and participation to address this societal challenge. In this paper we introduce EnergyUse; a social and collaborative platform for raising awareness on climate change, by enabling users to view and compare the actual energy consumption of various appliances, and to share and discuss energy conservation tips in an open and social environment. The platform collects data from smart plugs, and exports appliance consumption information and community generated energy tips as linked data. In this paper we report on the system design, data modelling, platform usage and early deployment with a set of 58 initial participants. We also discuss the challenges, lessons learnt, and future platform developments."
  -demo_60,60,Thomas Wilmering and Mark B. Sandler,Wilmering,Interdisciplinary Classification of Audio Effects in the Audio Effect Ontology,poster,Poster and Demo session,47,Thomas Wilmering,demo_60.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"This paper discusses an extension to the Audio Effect Ontology (AUFX-O) for the interdisciplinary classification of audio effect types. The ontology extension implements a unified classification system that draws on knowledge from different music-related disciplines and is designed to facilitate the retrieval of audio effect information based on low-level and semantic aspects. It extends AUFX-O enabling communication between agents from different disciplines within the field of music creation and production. After briefly discussing the ontology, we show how it can be used to efficiently classify and retrieve effect types."
  +demo_60,60,Thomas Wilmering and Mark B. Sandler,Wilmering,Interdisciplinary Classification of Audio Effects in the Audio Effect Ontology,demo,Poster and Demo session,47,Thomas Wilmering,demo_60.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"This paper discusses an extension to the Audio Effect Ontology (AUFX-O) for the interdisciplinary classification of audio effect types. The ontology extension implements a unified classification system that draws on knowledge from different music-related disciplines and is designed to facilitate the retrieval of audio effect information based on low-level and semantic aspects. It extends AUFX-O enabling communication between agents from different disciplines within the field of music creation and production. After briefly discussing the ontology, we show how it can be used to efficiently classify and retrieve effect types."
   resource_46,46,"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,resource_46.pdf,501,2016-10-20T10:50:00,2016-10-20T11:10:00,"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_45,45,"Monika Solanki, Bojan Božić, Markus Freudenberg, Rob Brennan and Dimitris Kontokostas",Solanki,Enabling combined software and data engineering at Web-scale: The ALIGNED suite of ontologies,resource,Ontologies (II),1,Monika Solanki,resource_45.pdf,504+505,2016-10-21T13:30:00,2016-10-21T13:50:00,"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."
   poster_110,110,"Ben De Meester, Anastasia Dimou, Ruben Verborgh, Erik Mannens and Rik Van de Walle",Meester,Discovering and Using Functions via Content Negotiation,poster,Poster and Demo session,41,Ben De Meester,poster_110.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"Data has been made reusable and machine-interpretable by publishing it as Linked Data.
  
positive.code: began to accelerated. Combined with global standardisation activities,
  we expect this database can contribute data integration across the world."
  demo_35,35,Adam Sotona,Sotona,How to feed Apache HBase with petabytes of RDF data: An extremely scalable RDF store based on Eclipse RDF4J framework and Apache HBase database,demo,Poster and Demo session,31,Adam Sotona,demo_35.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"Eclipse RDF4J (formerly known as Sesame) is an open source Java framework for processing RDF data. RDF4J framework is extensible through its Storage And Inference Layer (SAIL) to support various RDF stores and inference engines. Apache HBase is the Hadoop database, a distributed and scalable big data store. It is designed to scale up from single servers to thousands of machines. We have connected RDF4J and HBase to receive an extremely scalable RDF store."
  demo_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 and Demo session,13,Wei Emma Zhang,demo_36.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"In this paper, we propose the rst system, so-called Open Programming Knowledge Extraction (OPKE), to automatically extract knowledge from programming Question-Answering (QA) communities. OPKE is the rst step of building a programming-centric knowledge base. Data mining and Natural Language Processing techniques are leveraged to identify paraphrased questions and construct structured information. Preliminary evaluation shows the eectiveness of OPKE."
  demo_37,37,Gerhard Wohlgenannt and Filip Minic,Wohlgenannt,Using word2vec to Build a Simple Ontology Learning System,poster,Poster and Demo session,15,Gerhard Wohlgenannt,demo_37.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"Ontology learning has been an important research area in the Semantic Web field in the last 20 years. Ontology learning systems generate domain models from data (typically text) using a combination of sophisticated methods. In this poster, we study the use of Google's word2vec to emulate a simple ontology learning system, and compare the results to an existing ""traditional"" ontology learning system.
  "
  resource_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,resource_1.pdf,502,2016-10-20T15:50:00,2016-10-20T16:10:00,"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."
  demo_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 and Demo session,23,Satoshi Kume,demo_93.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"Imaging data are fundamental to life sciences. We aimed to construct a microscopy ontology for an integrated metadata database of optical and electron microscopy images combined with various bio-entities. To realise this, we applied the Resource Description Framework (RDF) to an Open Microscopy Environment (OME) data model, which is the de facto standard to describe optical microscopy images and experimental data. We translated the XML-based OME metadata into the base concept of Web Ontology Language (OWL) as a trial of developing microscopy ontology. We describe the OWL-based ontology of microscopy imaging data and propose 18 upper-level concepts of ontology with missing concepts such as electron microscopy, phenotype data, biosample, and imaging conditions."
  demo_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 and Demo session,14,Yuting Song,demo_90.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"Aiming to link the records that refer to the same entity across multiple databases in different languages, we address the mismatches of wordings between literal translations of metadata in source language and metadata in target language, which cannot be calculated by string-based measures. In this paper, we propose a method based on word embedding, which can capture the semantic similarity relationships among words. The effectiveness of this method is confirmed in linking the same records between Ukiyo-e (Japanese traditional woodblock printing) databases in Japanese and English. This method could be applied to other languages since it makes little assumption about languages."
  demo_91,91,Robin Keskisärkkä,Keskisärkkä,Representing RDF Stream Processing Queries in RSP-SPIN,demo,Poster and Demo session,43,Robin Keskisärkkä,demo_91.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"A number of RDF Stream Processing (RSP) systems have been developed to support the processing of streaming Linked Data, however, due to the lack of a standardized query language they all provide different SPARQL extensions. The RSP Community Group is in the process of developing a standardized RSP query language (RSP-QL), which incorporates many of features of existing RSP language extensions. In this demo paper we describe how RSP-SPIN, a SPIN extension for representing RSP-QL queries, can be used to encapsulate RSP queries as RDF, forming a syntax agnostic representation that can be used to support serialization into multiple RSP language extensions. This could be useful, for example, to reduce the effort required to produce and maintain RSP benchmarks, since developers can focus on a single representation per query, rather than manually implementing and validating queries for several languages in parallel. "
  demo_96,96,"Amna Basharat, Khaled Rasheed and I. Budak Arpinar",Basharat,Harnessing Crowds and Experts for Semantic Annotation of the Qur'an,poster,Poster and Demo session,31,Amna Basharat,demo_96.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"In this paper we illustrate how we harness the power of crowds and specialized experts through automated knowledge acquisition workflows for semantic annotation in specialized and knowledge intensive domains. We undertake the special case of the Arabic script of the Qur'an, a widely studied manuscript, and apply a hybrid methodology of traditional 'crowdsourcing' augmented with 'expertsourcing' for semantically annotating its verses. We demonstrate that our proposed hybrid method presents a promising approach for achieving reliable annotations in an efficient and scalable manner, especially in cases where a high level of accuracy is required in knowledge intense and sensitive domains. "
  resource_4,4,"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,resource_4.pdf,501,2016-10-19T14:00:00,2016-10-19T14:20:00,"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."
  demo_94,94,Motoyuki Takaai and Yohei Yamane,Takaai,Constructing Semantic Networks of Development Activities from Weekly Reports,poster,Poster and Demo session,16,Motoyuki Takaai,demo_94.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"In the development departments of some manufacturing companies,
  there are weekly reports describing the status of events but they are poorly structured plain texts.
  In this report, we propose a method for constructing semantic networks of development activities from weekly reports.
  Our ontology-based method extracts things like events, status and agents from the reports and constructs relations
  
negative.code: journal_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-1,502,2016-10-21T14:10:00,2016-10-21T14:30:00,"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_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),3,Pierre-Yves Vandenbussche,http://www.semantic-web-journal.net/content/linked-open-vocabularies-lov-gateway-reusable-semantic-vocabularies-web-1,501,2016-10-20T16:10:00,2016-10-20T16:30:00,"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_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+505,2016-10-19T12:00:00,2016-10-19T12:20:00,"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_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),2,Andrea Giovanni Nuzzolese,http://www.semantic-web-journal.net/content/aemoo-linked-data-exploration-based-knowledge-patterns-1,504+505,2016-10-20T15:50:00,2016-10-20T16:10:00,"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."
  research_146,146,"Zlatan Dragisic, Valentina Ivanova, Patrick Lambrix, Daniel Faria, Ernesto Jiménez-Ruiz and Catia Pesquita",Dragisic,User validation in ontology alignment,research,Ontology Matching,3,Zlatan Dragisic,research_146.pdf,502,2016-10-20T11:10:00,2016-10-20T11:30:00,"User validation is one of the challenges facing the ontology alignment community, as there are limits to the quality of automated alignment algorithms.
  In this paper we present a broad study on user validation of ontology alignments that encompasses three distinct but interrelated aspects: the profile of the user, the services of the alignment system, and its user interface. We discuss key issues pertaining to the alignment validation process under each of these aspects, and provide an overview of how current systems address them. Finally, we use experiments from the Interactive Matching track of the Ontology Alignment Evaluation Initiative (OAEI) 2015 to assess the impact of errors in alignment validation, and how systems cope with them as function of their services."
  research_90,90,Lei Zhang and Achim Rettinger,Zhang,A Knowledge Base Approach to Cross-lingual Keyword Query Interpretation,research,Search (I),3,Lei Zhang,research_90.pdf,502,2016-10-20T14:10:00,2016-10-20T14:30:00,"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."
  