posted by organizer: groppe || 7818 views || tracked by 14 users: [display]

SBD 2016 : International Workshop on Semantic Big Data

FacebookTwitterLinkedInGoogle

Link: http://www.ifis.uni-luebeck.de/~groppe/sbd/2016
 
When Jul 1, 2016 - Jul 1, 2016
Where San Francisco, USA
Submission Deadline Feb 15, 2016
Notification Due Apr 15, 2016
Categories    semantic web   big data   data management
 

Call For Papers

******************************************************
International Workshop on Semantic Big Data (SBD 2016)
http://www.ifis.uni-luebeck.de/~groppe/sbd
******************************************************
at ACM SIGMOD 2016, San Francisco, USA

** Aims of the Workshop **

The current World-Wide Web enables an easy, instant access to a vast amount of online information. However, the content in the Web is typically for human consumption, and is not tailored for machine processing. The Semantic Web is hence intended to establish a machine-understandable Web, and is currently also used in many other domains and not only in the Web. The World Wide Web Consortium (W3C) has developed a number of standards around this vision. Among them is the Resource Description Framework (RDF), which is used as the data model of the Semantic Web. The W3C has also defined SPARQL as RDF query language, RIF as rule language, and the ontology languages RDFS and OWL to describe schemas of RDF. The usage of common ontologies increases interoperability between heterogeneous data sets, and the proprietary ontologies with the additional abstraction layer facilitate the integration of these data sets. Therefore, we can argue that the Semantic Web is ideally designed to work in heterogeneous Big Data environments.

We define Semantic Big Data as the intersection of Semantic Web data and Big Data. There are masses of Semantic Web data freely available to the public - thanks to the efforts of the linked data initiative. According to http://stats.lod2.eu/ the current freely available Semantic Web data is approximately 90 billion triples in over 3,300 datasets, many of which are accessible via SPARQL query servers called SPARQL endpoints. Everyone can submit SPARQL queries to SPARQL endpoints via a standardized protocol, where the queries are processed on the datasets of the SPARQL endpoints and the query results are sent back in a standardized format. Hence not only Semantic Big Data is freely available, but also distributed execution environments for Semantic Big Data are freely accessible. This makes the Semantic Web an ideal playground for Big Data research.

The goal of this workshop is to bring together academic researchers and industry practitioners to address the challenges and report and exchange the research findings in Semantic Big Data, including new approaches, techniques and applications, make substantial theoretical and empirical contributions to, and significantly advance the state of the art of Semantic Big Data.

** Types of Papers **

The workshop solicits papers of different type:
- Research Papers propose new approaches, theories or techniques related to Semantic Big Data including new data structures, algorithms and whole systems. They should make substantial theoretical and empirical contributions to the research field.
- Experiments and Analysis Papers focus on the experimental evaluation of existing approaches including data structures and algorithms for Semantic Big data and bring new insights through the analysis of these experiments. Results of Experiments and Analysis Papers can be e.g. showing benefits of well-known approaches in new settings and environments, open new research problems by demonstrating unexpected behavior or phenomena, or compare a set of traditional approaches in an experimental survey.
- Application Papers report practical experiences on applications of Semantic Big Data. Application Papers might describe how to apply Semantic Web technologies to specific application domains with big data demands like social networks, web search, e-business, collaborative environments, e-learning, medical informatics, bioinformatics and geographic information system. Application Papers might describe applications using linked data in a new way.
- Vision Papers identify emerging new or future research issues and directions, and describe new research visions having demands for Semantic Big Data. The new visions will potentially have great impacts on society.

** Topics of Interest **

We welcome papers on the following topics:
- Semantic Data Management, Query Processing and Optimization in
- Big Data
- Cloud Computing
- Internet of Things
- Graph Databases
- Federations
- Spatial and Spatio-Temporal Data
- Evaluation strategies for Semantic Big Data of Rule-based Languages like RIF and SWRL
- Ontology-based Approaches for Modeling, Mapping, Evolution and Real-world ontologies in the context of Semantic Big Data
- Reasoning Approaches (Real-World Applications, Efficient Algorithms) especially designed for Semantic Big Data environments
- Linked Data
- Integration of Heterogeneous Linked Data
- Real-World Applications
- Statistics and Visualizations
- Quality
- Ranking Techniques
- Provenance
- Mining and Consuming Linked Data
- Semantic Web stream processing (Dynamic Data, Temporal Semantics)
- Semantic Internet of Things
- Semantic Smart Homes/Companies/Cities
- Performance, Evaluation and Benchmarking of Semantic Web Technologies, Applications and Databases
- Semantic Web Services
- Semantic Big Data Archives
- Efficient Archiving and Preservation Techniques
- Evolution Representation
- Compression Approaches
- Querying Techniques
- Semantic Big Data on Emergent Hardware Technologies
- FPGA
- GPU
- SSD
- Main-Memory Databases


** Workshop Chairs **

Sven Groppe, University of Lübeck, Germany
Le Gruenwald, University of Oklahoma, USA


** Program Committee **

Muhammad Intizar Ali, DERI, National University of Ireland, Ireland
Carlos Buil Aranda, Universidad Técnica Federico Santa María, Chile
Feng Cao, IBM China Research Laboratory, China
Isabel Cruz, University of Illinois at Chicago, USA
Paulo Rupino da Cunha, University of Coimbra, Portugal
Melike Şah Direkoglu, Near East University, North Cyprus
Julian Dolby, IBM Research, USA
Vadim Ermolayev, Zaporozhye National University, Ukraine
Javier D. Fernández, Vienna University of Economics and Business, WU Vienna, Austria
Carlos Juiz García, Universitat de les Illes Balears, Spain
Panagiotis Germanakos, University of Cyprus, Cyprus
Katja Gilly de La Sierra-Llamazares, Miguel Hernandez University, Spain
Ekaterini Ioannou, Technical University of Crete, Greece
Prudhvi Janga, University of Cincinnati and Amazon Web Services, USA
Ioannis Konstantinou, National Technical University of Athens, Greece
Nectarios Koziris, National Technical University of Athens, Greece
Herbert Kuchen, University of Münster, Germany
Wookey Lee, Inha University, Korea
Isaac Lera, Universitat de les Illes Balears, Spain
Xiang Lian, University of Texas - Pan American Texas, USA
Qing Liu, CSIRO, Australia
Nuno Lopes, Smarter Cities Technology Centre, IBM Research, Dublin, Ireland
Fadi Maali, National University of Ireland Galway, Ireland
Ioana Manolescu, INRIA and Université Paris-Sud, France
Daniel Miranker, The University of Texas at Austin, USA
Z. Meral Özsoyoglu, Case Western Reserve University, USA
Grażyna Paliwoda-Pękosz, Cracow University of Economics, Poland
Nikolaos Papailiou, National Technical University of Athens, Greece
Richard Picking, Glyndwr University, UK
Alfredo Pulvirenti, University of Catania, Italy
Louiqa Raschid, University of Maryland, USA
Sherif Sakr, School of Computer Science and Engineering University of New South Wales, Australia
Ismael Sanz, Universitat Jaume I, Spain
Stephan Seufert, Max-Planck Institute for Informatics, Saarbrücken, Germany
Rudi Studer, Institute AIFB, Karlsruhe Institute of Technology (KIT), Germany
Dezhao Song, Research and Development of Thomson Reuters, USA
Martin Theobald, University of Ulm, Germany
Dimitrios Tsoumakos, Department of Informatics, Ionian University, Greece
Juergen Umbrich, Vienna University of Economics and Business, Vienna, Austria
Dongyan Zhao, Peking University Beijing, China
Xiang ZHAO, National University of Defense Technology, China
Weiguo Zheng, Chinese University of Hong Kong, China
Dimitrios Zissis, University of the Aegean, Greece
Lei Zou, Peking University, China


** Important Dates **

Submission: 15 February 2016
Notification: 15 April 2016
Workshop: 1 July 2016


** Submission **

Authors are invited to submit original, unpublished research papers that are not being considered for publication in any other forum.

Manuscripts should be formatted using the camera-ready templates in the ACM proceedings double-column format. Papers cannot exceed 6 pages in length.

Accepted papers will be published online in the ACM digital library.

We describe manuscript preparation and submission procedure at http://www.ifis.uni-luebeck.de/~groppe/sbd/submit

Related Resources

ICBICC 2024   2024 International Conference on Big Data, IoT, and Cloud Computing (ICBICC 2024)
IEEE COINS 2024   IEEE COINS 2024 - London, UK - July 29-31 - Hybrid (In-Person & Virtual)
BDCAT 2024   IEEE/ACM Int’l Conf. on Big Data Computing, Applications, and Technologies
ACM-Ei/Scopus-CCISS 2024   2024 International Conference on Computing, Information Science and System (CCISS 2024)
IEEE BigData 2024   2024 IEEE International Conference on Big Data
ICoSR 2024   2024 3rd International Conference on Service Robotics
DSIT 2024   7th International Conference on Data Science and Information Technology
SoCAV 2024   2024 International Symposium on Connected and Autonomous Vehicles (SoCAV 2024)
Singapore--CDICS 2024   The 2024 2nd International Conference on Data, Information and Computing Science (CDICS 2024)
CFP-ICBDAA 2024   The 2024 International Conference on Big Data Analysis and Application (ICBDAA 2024)