[esip-semantictech] CFP: International Workshop on Semantic Big Data (SBD 2017)

[Robert R Downs]

Dear Semantic Technology Members,

Please find the CFP, below, which you might find relevant and excuse any 
duplication of this message.

Thanks,

Bob Downs

Robert R. Downs, PhD
Senior Digital Archivist and Senior Staff Associate Officer of Research
Acting Head of Cyberinfrastructure and Informatics Research and Development
Center for International Earth Science Information Network (CIESIN),
The Earth Institute, Columbia University
P.O. Box 1000, 61 Route 9W, Palisades, NY 10964 USA
Voice: 845-365-8985; fax: 845-365-8922
E-mail: rdowns at ciesin.columbia.edu
Columbia University CIESIN Web site: http://www.ciesin.columbia.edu
ORCID: 0000-0002-8595-5134

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CALL FOR PAPERS
International Workshop on Semantic Big Data (SBD 2017)

In conjunction with ACM SIGMOD 2017

May 19, 2017, Raleigh, USA
Submission: January 15, 2017

Web: http://www.ifis.uni-luebeck.de/~groppe/sbd
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** 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 the RDF query 
language, RIF as the 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 150 billion triples in over 2,800 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 types:
   - 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, for example, showing benefits of well-known approaches in 
new settings and environments, opening new research problems by 
demonstrating unexpected behavior or phenomena, or comparing 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 Luebeck, Germany
- Le Gruenwald, University of Oklahoma, USA


** Program Committee **

- Muhammad Intizar Ali, Insight, National University of Ireland, Galway
- Carlos Buil Aranda, Universidad Tecnica Federico Santa Maria, Chile
- Mithun Balakrishna, Lymba Corporation, USA
- Isabel Cruz, University of Illinois at Chicago, USA
- Paulo Rupino da Cunha, University of Coimbra, Portugal
- Melike Sah Direkoglu, Near East University, North Cyprus
- Julian Dolby, IBM Research, USA
- Vadim Ermolayev, Zaporizhzhya National University, Ukraine
- Javier D. Fernandez, Vienna University of Economics and Business, WU 
Vienna, Austria
- Carlos Juiz Garcia, Universitat de les Illes Balears, Spain
- Katja Gilly de La Sierra-Llamazares, Miguel Hernandez University, Spain
- Andreas Harth, Institute AIFB, Karlsruhe Institute of Technology 
(KIT), Germany
- 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 Muenster, Germany
- Wookey Lee, Inha University, Korea
- Isaac Lera, Universitat de les Illes Balears, Spain
- Xiang Lian, University of Texas Rio Grande Valley, USA
- Qing Liu, CSIRO, Australia
- Nuno Lopes, TopQuadrant
- Ioana Manolescu, INRIA and Ecole Polytechnique, France
- Daniel Miranker, The University of Texas at Austin, USA
- Grazyna Paliwoda-Pekosz, Cracow University of Economics, Poland
- Nikolaos Papailiou, National Technical University of Athens, Greece
- Alfredo Pulvirenti, University of Catania, Italy
- Sherif Sakr, School of Computer Science and Engineering University of 
New South Wales, Australia
- Stephan Seufert, Trifacta, Inc., USA
- Omair Shafiq, Carleton University, Canada
- Marta Tatu, Lymba Corporation, 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: January 15, 2017
Notification: March 8, 2017
Workshop: May 19, 2017


** 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