anchor.diff:  journal_9,9,Danh Le-Phuoc,Le-Phuoc,Operator-aware approach for boosting performance in RDF stream processing,journal,Streams,3,Danh Le-Phuoc,http://dx.doi.org/10.1016/j.websem.2016.04.001,501,2016-10-20T14:10:00,2016-10-20T14:30:00,"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_8,8,"Marco Rospocher, Marieke van Erp, Piek Vossen, Antske Fokkens, Itziar Aldabe, German Rigau, Aitor Soroa, Thomas Ploeger, 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+505,2016-10-21T11:30:00,2016-10-21T11:50:00,"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."""
   demo_30,30,"Rivindu Perera, Parma Nand and Gisela Klette",Perera,Lexicalizing DBpedia with Realization Enabled Ensemble Architecture: RealText-lex2 Approach,demo,Poster and Demo session,26,Rivindu Perera,demo_30.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"DBpedia encodes massive amounts of open domain knowledge and is growing by accumulating more triples at the same rate as Wikipedia. However, in order to be able to present the knowledge processed using DBpedia, the applications need to present this knowledge often require natural language formulations of these triples. The RealText-lex2 framework offers a scalable platform to transform these triples to natural language sentences using lexicalization patterns. The framework has evolved from its previous version (RealText-lex) and is comprised of four lexicalization pattern mining modules which derive patterns from a training triple collection. These patterns can be then applied on the new triples given that they satisfy a defined set of constraints."
  -demo_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 and Demo session,21,Joo Sungmin,demo_31.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"This paper proposes Agriculture Activity Ontology(AAO) as a basis of the core vocabulary of agricultural activity. Since concepts of agriculture activities are formed by the various context such as purpose, means, crop, and field, we organize the agriculture activity ontology as a hierarchy of concepts discriminated by various properties such as purpose, means, crop and field. The vocabulary of agricultural activity is then defined as the subset of the ontology. Since the ontology is consistent, extendable, and capable of some inferences thanks to Description Logics, so the vocabulary inherits these features. The vocabulary is also linked to existing vocabularies such as AGROVOC. It is expected to use in the data format in the agricultural IT system. The vocabulary is adopted as the part of ""the guideline for agriculture activity names for agriculture IT systems"" issued by Ministry of Agriculture, Forestry and Fisheries (MAFF), Japan."
  +demo_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,demo,Poster and Demo session,21,Joo Sungmin,demo_31.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"This paper proposes Agriculture Activity Ontology(AAO) as a basis of the core vocabulary of agricultural activity. Since concepts of agriculture activities are formed by the various context such as purpose, means, crop, and field, we organize the agriculture activity ontology as a hierarchy of concepts discriminated by various properties such as purpose, means, crop and field. The vocabulary of agricultural activity is then defined as the subset of the ontology. Since the ontology is consistent, extendable, and capable of some inferences thanks to Description Logics, so the vocabulary inherits these features. The vocabulary is also linked to existing vocabularies such as AGROVOC. It is expected to use in the data format in the agricultural IT system. The vocabulary is adopted as the part of ""the guideline for agriculture activity names for agriculture IT systems"" issued by Ministry of Agriculture, Forestry and Fisheries (MAFF), Japan."
   demo_32,32,"Rivindu Perera, Parma Nand and Gisela Klette",Perera,Enriching Answers in Question Answering Systems using Linked Data,demo,Poster and Demo session,23,Rivindu Perera,demo_32.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"Linked Data has emerged as the most widely used and the most powerful knowledge source for Question Answering (QA). Although Question Answering using Linked Data (QALD) fills in many gaps in the traditional QA models, the answers are still presented as factoids. This research introduces an answer presentation model for QALD by employing Natural Language Generation (NLG) to generate natural language descriptions to present an informative answer. The proposed approach employs lexicalization, aggregation, and referring expression generation to build a human-like enriched answer utilizing the triples extracted from the entities mentioned in the question as well as the entities contained in the answer."
  -demo_33,33,"Stasinos Konstantopoulos, Angelos Charalambidis, Giannis Mouchakis, Antonis Troumpoukis, Jürgen Jakobitsch and Vangelis Karkaletsis",Konstantopoulos,Semantic Web Technologies and Big Data Infrastructures: SPARQL Federated Querying of Heterogeneous Big Data Stores,poster,Poster and Demo session,27,Stasinos Konstantopoulos,demo_33.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"The ability to cross-link large scale data with each other and with structured Semantic Web data, and the ability to uniformly process Semantic Web and other data adds value to both the Semantic Web and to the Big Data community. This paper presents work in progress towards integrating Big Data infrastructures with Semantic Web technologies, allowing for the cross-linking and uniform retrieval of data stored in both Big Data infrastructures and Semantic Web data. The technical challenges involved in achieving this, pertain to both data and system interoperability: we need a way to make the semantics of Big Data explicit so that they can interlink and we need a way to make it transparent for the client applications to query federations of such heterogeneous systems. The paper presents an extension of the Semagrow federated SPARQL query processor that is able to seamlessly federated SPARQL endpoints, Cassandra databases, and Solr databases, and discusses future directions of this line of work."
  -demo_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 and Demo session,24,Kai Lenz,demo_34.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"To promote data dissemination and integration of life science
  +demo_33,33,"Stasinos Konstantopoulos, Angelos Charalambidis, Giannis Mouchakis, Antonis Troumpoukis, Jürgen Jakobitsch and Vangelis Karkaletsis",Konstantopoulos,Semantic Web Technologies and Big Data Infrastructures: SPARQL Federated Querying of Heterogeneous Big Data Stores,demo,Poster and Demo session,27,Stasinos Konstantopoulos,demo_33.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"The ability to cross-link large scale data with each other and with structured Semantic Web data, and the ability to uniformly process Semantic Web and other data adds value to both the Semantic Web and to the Big Data community. This paper presents work in progress towards integrating Big Data infrastructures with Semantic Web technologies, allowing for the cross-linking and uniform retrieval of data stored in both Big Data infrastructures and Semantic Web data. The technical challenges involved in achieving this, pertain to both data and system interoperability: we need a way to make the semantics of Big Data explicit so that they can interlink and we need a way to make it transparent for the client applications to query federations of such heterogeneous systems. The paper presents an extension of the Semagrow federated SPARQL query processor that is able to seamlessly federated SPARQL endpoints, Cassandra databases, and Solr databases, and discusses future directions of this line of work."
  +demo_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,demo,Poster and Demo session,24,Kai Lenz,demo_34.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"To promote data dissemination and integration of life science
   datasets produced in a general research institute, RIKEN, we developed
   an infrastructure database named as ""RIKEN MetaDatabase"", which en-
   ables data publication and integration with Resource Description Frame-
  
positive.code: 
  To address the above challenges, this paper demonstrates SWoTSuite, a toolkit for prototyping SWoT applications. It hides the use of semantic web technologies as much as possible to avoid the burden of designing SWoT applications that involves designing ontologies, annotating sensor data, and using reasoning mechanisms to enrich data. Taking inspiration from sharing and reuse approaches, SWoTSuite reuses data and vocabularies. It leverages existing technologies to build applications. We take a hello world naturopathy application as an example and demonstrate an application development process using SWoTSuite. The demo video is available at URL- http://tinyurl.com/zs9flrt."
  demo_68,68,"Damien Graux, Louis Jachiet, Pierre Geneves and Nabil Layaida",Graux,SPARQLGX in Action: Efficient Distributed Evaluation of SPARQL with Apache Spark,demo,Poster and Demo session,35,Damien Graux,demo_68.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"We demonstrate SPARQLGX: our implementation of a distributed sparql evaluator. We show that SPARQLGX makes it possible to evaluate SPARQL queries on billions of triples distributed across multiple nodes, while providing attractive performance figures."
  demo_67,67,"Valeria Fionda, Melisachew Wudage Chekol and Giuseppe Pirrò",Fionda,Gize: A Time Warp in the Web of Data,poster,Poster and Demo session,43,Valeria Fionda,demo_67.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"We introduce the Gize framework for querying historical RDF data. Gize builds upon two main pillars: a lightweight approach to keep historical data, and an extension of SPARQL called SPARQ–LTL, which incorporates temporal logic primitives to enable a rich class of queries. One striking point of Gize is that its features can be readily made available in existing query processors."
  demo_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 and Demo session,32,Hassan Saif,demo_66.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"From its start, the so-called Islamic State of Iraq and the Levant (ISIL/ISIS) has been successfully exploiting social media networks, most notoriously Twitter, to promote its propaganda and recruit new members, resulting in thousands of social media users adopting pro-ISIS stance every year. Automatic identification of pro-ISIS users on social media has, thus, become the centre of interest for various governmental and research organisations. In this paper we propose a semantic-based approach for radicalisation detection on Twitter. Unlike most previous works, which mainly rely on the lexical and contextual representation of the content published by Twitter users, our approach extracts and makes use of the underlying semantics of words exhibited by these users to identify their pro/anti-ISIS stances. Our results show that classifiers trained from words' semantics outperform those trained from lexical and network features by 2% on average F1-measure.
  "
  demo_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 and Demo session,20,Jonas Bulegon Gassen,demo_65.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"System analysis and design is concerned with the creation of conceptual models. In this paper, we introduce a novel resource called ""Who-Does-What"" (WDW) that supports the creation and quality assurance of such models. WDW provides a knowledge base of activities for classes of people engaged in a wide range of different occupations. The resource is semi-automatically created by populating the manually-created Standard Occupational Classification (SOC) of the US Department of Labor with activities found on the Web."
  demo_64,64,"Changlong Wang, Xiaowang Zhang and Zhiyong Feng",Wang,Structure-guiding Modular Reasoning for Expressive Ontologies,poster,Poster and Demo session,38,Changlong Wang,demo_64.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"We propose a technique that combine an OWL 2 EL reasoner with an OWL 2 reasoner to classify expressive ontologies. We exploit the information implied by the ontology structure to identify a small non-EL ontology that contains necessary axioms to ensure the completeness. In the process of ontology classification, the bulk of workload is delegated to an efficient OWL 2 EL reasoner and the small part of workload is handled by a less efficient OWL 2 reasoner. Experimental results show that our approach leads to a reasonable task assignment and offers a substantial speedup in ontology classification."
  demo_62,62,Michał Blinkiewicz and Jaroslaw Bak,Blinkiewicz,SQuaRE: A Visual Tool For Creating R2RML Mappings,poster,Poster and Demo session,09,Michał Blinkiewicz,demo_62.pdf,3rd Floor,2016-10-19T18:00:00,2016-10-19T21:00:00,"We present the recent progress of SQuaRE, the SPARQL
  Query and R2RML mappings Environment which provides a graphical
  interface for creating R2RML mappings which can be immediately tested
  by executing SPARQL queries. SQuaRE is a web-based tool with easy
  
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,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.
  