BIKE 2012 - International Workshop on Big data for Knowledge Engineering

Recently, increasing numbers of data providers have begun to publish Linked data, which enables data from different sources to be connected and queried. By September 2011, the Linked data had grown to 31 billion RDF triples, which were inter-linked by around 504 million links. In particular, these data sets cover diverse domains such as e-government, geographic information, social network, music, scientific publication, biology, and sensor network. Thus, management, analysis, and visualization of these large scale data sets have become major challenges in the web of data. This workshop aims to discuss the state-of-the-art research and development of very large linked data. In particular, we focus on the scalable management (e.g., storage, query processing, search, reasoning, maintenance, etc), analysis, integration, and visualization of large linked data sets. We welcome papers that address fundamental research issues in these challenging areas. We also encourage papers to present architectures and services for data management techniques supporting large scale linked data. The workshop will provide a cross-disciplinary forum for researchers to share their research efforts and ideas between industry and academia. By bringing together representatives of academia and industry, the workshop is also a means for identifying new research problems and disseminating results of the research and practice.
[edit] Topics of Interest
The aim of this workshop is to cover all aspects that relate to research and practical issues of big data processing. Topics of interest include but are not limited to:
Linked data modeling for knowledge extraction
Semantic and social data on the cloud platform
(Governmental) large scale linked data
Data interoperability and exchange
Semantic sensor data
Integrating social and linked data
Scalable solutions for linking linked data
Search, query and analysis on large scale linked data
Reasoning over large scale linked data
Mining of big data
Maintenance of evolving big data
Visualizing large scale linked data
Trends and technologies on big data
General ontologies for (open) linked data
Creating and combining social and linked data
Linked data analysis Entity disambiguation on large scale linked data
Visualizing semantic & linked data