anchor.diff:  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,demo,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,demo,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.
  +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,demo,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,demo,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_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,demo,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. "
  +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,demo,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,
  +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
  
positive.code: demo_22,22,John P. Mccrae,Mccrae,Yuzu: Publishing Any Data as Linked Data,demo,Poster and Demo session,47,John P. Mccrae,demo_22.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"Linked data is one of the most important methods for improving the applicability of data, however most data is not in linked data formats and raising it to linked data is still a significant challenge. We present Yuzu, an application that makes it easy to host legacy data in JSON, XML or CSV as linked data, while providing a clean interface with advanced features. The ease-of-use of this framework is shown by its adoption for a number of existing datasets including WordNet.
  "
  demo_29,29,"Evgeny Kharlamov, Bernardo Cuenca Grau, Ernesto Jimenez-Ruiz, Steffen Lamparter, Gulnar Mehdi, Martin Ringsquandl, Yavor Nenov, Stephan Grimm, Mikhail Roshchin and Ian Horrocks",Kharlamov,SOMM: Industry Oriented Ontology Management Tool,demo,Poster and Demo session,17,Evgeny Kharlamov,demo_29.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"In this demo we present the SOMM system that resulted from an ongoing collaboration between Siemens and the University of Oxford. The goal of this collaboration is to facilitate design and management of ontologies that capture conceptual information models underpinning various industrial applications. SOMM supports engineers with little background on semantic technologies in the creation of such ontologies and in populating them with data. SOMM implements a fragment of OWL 2 RL extended with a form of integrity constraints for data validation, and it comes with support for schema and data reasoning, as well as for ontology integration. We demonstrate functionality of SOMM on two scenarios from energy and manufacturing domains."
  demo_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,demo,Poster and Demo session,22,Atsuko Yamaguchi,demo_95.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"Linked Open Data (LOD) is a powerful mechanism for linking different datasets published on the Web, which is expected to create new value of data through mash-up over various datasets on the Web. One of the important needs to obtain data from LOD is to find a path of resources connecting given two classes, each of which has an end resource of the path. 
  In this study, the two technologies for the approach are introduced: a labeled multi graph named class graph to compute class-class relationships and an RDF specification named SPARQL Builder Metadata to obtain and store required metadata for construction of a class graph. In addition, as a practical application, we introduce the SPARQL Builder system, which assists users in writing semantic queries for LOD."
  doctoralconsortium_18,18,Radityo Eko Prasojo,Prasojo,Entity-Relationship Extraction from Wikipedia Unstructured Text ,doctoralconsortium,Session 1,1,Radityo Eko Prasojo,doctoralconsortium_18.pdf,,2016-10-18T11:00:00,2016-10-18T11:15:00,"Wikipedia has been the primary source of information for many automatically-generated Semantic Web data sources. However, they suffer from incompleteness since they largely do not cover information contained in the unstructured texts of Wikipedia. Our goal is to extract structured entity-relationships in RDF from such unstructured texts, ultimately using them to enrich existing data sources. Our extraction technique is aimed to be topic-independent, leveraging grammatical dependency of sentences and context semantic refinement. Preliminary evaluations of the proposed approach has shown some promising results."
  research_127,127,"Dilshod Ibragimov, Katja Hose, Torben Bach Pedersen and Esteban Zimanyi",Ibragimov,Optimizing Aggregate SPARQL Queries using Materialized RDF Views,research,Querying,3,Dilshod Ibragimov,research_127.pdf,502,2016-10-19T14:40:00,2016-10-19T15:00:00,"During the past couple of years, more and more data has been published as native RDF datasets. In this setup, both the size of the datasets and the need to process aggregate queries represent challenges for standard SPARQL query processing techniques. To overcome these limitations, materialized views can be created and used as a source of precomputed partial results during query processing. However, materialized view techniques, as proposed in relational databases, do not support RDF specifics, such as incompleteness and the need to support implicit (derived) information. Therefore, to overcome these challenges, this paper proposes MARVEL – the approach consisting of a view selection algorithm based on an RDF-specific cost model, a view definition syntax. and an algorithm for rewriting SPARQL queries using materialized RDF views. The experimental evaluation shows that the approach can improve query response time by more than an order of magnitude and is able to efficiently handle RDF specifics."
  
negative.code: 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."
  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.
  