Regular papers

Takahiro Kawamura
Deployment of Semantic Analysis to Call Center

Ludovic Langevine and Paul Bone
The Logic of Insurance: an Ontology-Centric Pricing Application

Parvathy Meenakshy and John Walker
Applying Semantic Web technologies in Product Information Management at NXP Semiconductors

Tony Hammond and Michele Pasi 
Linked data experience at Macmillan: Building discovery services for scientific and scholarly content on top of a semantic data model

José Gutiérrez-Cuellar and Jose Manuel Gomez-Perez.
HAVAS 18 Lab: A Knowledge Graph for Innovation in the Media Industry

Osma Suominen, Sini Pessala, Jouni Tuominen, Mikko Lappalainen, 
Susanna Nykyri, Henri Ylikotila, Matias Frosterus and Eero Hyvönen.
Deploying National Ontology Services: From ONKI to Finto

Sofia Cramerotti, Marco Buccio, Giampiero Vaschetto, Luciano Serafini and Marco Rospocher, Elena Cardillo and Ivan Donadello.
ePlanning: an Ontology-based System for Building Individualized Education Plans for Students with Special Educational Needs

Pechakucha papers

Tope Omitola, John Davies, Alistair Duke, Hugh Glaser and Nigel Shadbolt
Ontology-Based Linking of Social, Open, and Enterprise Data for Business Intelligence

Harry Halpin
The W3C Social Web Initiative

Tabea Tietz, Jörg Waitelonis, Joscha Jäger and Harald Sack
Smart Media Navigator: Visualizing Recommendations based on Linked Data

Ulli Waltinger
Smart Data Access: Semantic Web Technologies for Energy Diagnostics

Nico Lavarini and Silvia Melegari
Semantic Technology for Oil & Gas Business

Pinar Gocebe, Oguz Dikenelli, Umut Kose and Juan F. Sequeda
Semantic Web based Container Monitoring System for the Transportation Industry

Gokce Banu Laleci Erturkmen, Landen Bain and Ali Anil Sinaci.
keyCRF: Using Semantic Metadata Registries to Populate an eCRF with EHR Data

Frederik Malfait and Josephine Gough.
RDF Implementation of Clinical Trial Data Standards

Kwangsoo Kim, Eunju Lee, Soonhyun Kwon, Dong-Hwan Park and Seong-Il Jin
Health and Environment Monitoring Service for Solitary Seniors

Rajaraman Kanagasabai, Anitha Veeramani, Duy Ngan Le, Ghim-Eng Yap, James Decraene and Amy Shi-Nash
Using Semantic Technologies to Mine Customer Insights in Telecom Industry

V. Richard Benjamins, David Cadenas, Pedro Alonso, Antonio Valderrabanos and Josu Gomez
The voice of the customer for Digital Telcos

Andreas Blumauer
SKOS as a Key Element in Enterprise Linked Data Strategies

Bart van Leeuwen
iNowit, linked data as key element for innovation in emergency response

Ana Sasa Bastinos, Peter Haase, Georg Heppner, Stefan Zander and Nadia Ahmed
ReApp Store – a semantic AppStore for applications in the robotics domain

Bernard Gorman, Jakub Marecek and Jia Yuan Yu
Traffic Management using RTEC in OWL 2 RL

Zhe Wu and Jay Banerjee
Efficient Application of Complex Graph Analytics on Very Large Real World RDF Datasets

Dong Liu, Eleni Mikroyannidi and Robert Lee
Integrating Semantic Web Technologies in the Architecture of BBC Knowledge & Learning Beta Online Pages

Paolo Bouquet, Giovanni Adinolfi, Lorenzo Zeni and Stefano Bortoli
SICRaS: a semantic big data platform for fighting tax evasion and supporting social policy making

Jun Wook Lee, Yong Woo Kim and Soonhyun Kwon
Semantic WISE: An Applying of Semantic IoT Platform for Weather Information Service Engine

Tong Ruan, Haofen Wang, Fanghuai Hu, Jun Ding and Kai Lu
Building and Exploring Marine Oriented Knowledge Graph for ZhouShan Library

Jeff Pan, Yuan Ren, Gabriela Montiel and Zhe Wu
Fast In-Memory Reasoner for Oracle NoSQL Database EE: Uncover hidden relationships that exist in your enterprise data

Roberto Garcia and Nick Sincaglia
Semantic Web Technologies for User Generated Content and Digital Distribution Copyright Management

Systap Presentation

Zhisong Fu, Harish Kumar Dasari, Bradley Bebee, Martin Berzins, Bryan Thompson 
MapGraph - Graph processing at 30 billion edges per second on NVIDIA GPUs


MapGraph is a disruptive technology that delivers extreme performance for graph problems on many-core hardware.  MapGraph can be run on a laptop, on EC2 HPC GPU compute nodes, and on large GPU compute clusters.  With processing speeds of up to 3 billion edges per second on a single GPU, MapGraph changes what is possible with your data.
Many-core computing is the future.  CPU architectures are not getting any faster. Continued performance gains must come from many-core technologies such as GPUs or the Intel Xeon Phi.  GPUs are widely known for their role in games, high-performance computing, and high FLOPS/watt ratio.  However, graph algorithms are data-intensive, not compute intensive, and have degree dependent parallelism.  As a consequence, graph algorithms place an extreme burden on the memory bus and communications network.  
SYSTAP and the Scientific Computing and Imaging Institute have developed a capability for extreme performance parallel graph algorithms on GPUs from laptops to large GPU clusters.  MapGraph provides a scalable technology for data-intensive workloads that addresses the data-dependent parallelism, memory, and communication bottlenecks.  I will review this research and present our roadmap for this technology.