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DMC 2013 - 1st Workshop on “Data Management in the Cloud”

Date2013-03-12

Deadline2012-11-15

VenueMagdeburg, Germany Germany

Keywords

Websitehttps://www.btw-2013.de

Topics/Call fo Papers

Cloud computing is emerging as a cost-effective paradigm for massively scalable, fault-tolerant, and adaptive computation. Cloud computing architectures scale to massive numbers of commodity computers and adapt to changing hardware availability and requirements by dynamically allocating virtualized computing nodes. By providing on-demand scaling capabilities it is not only an attractive paradigm for data management problems but raises several research challenges for storing, querying, and analyzing large amounts of data.
On the other hand, we are witnessing a data revolution in many aspects of human activity, from physics and astronomy research, to online behavior, social network, and governmental data. For example, the Linked Open Data movement has produced a tremendous amount of data stored in distributed and interlinked endpoints forming the Linked Data cloud. The need to efficiently process and analyze these heterogeneous and massive data sets is not adequately met by current commercial and open-source offerings. The database community can therefore play a central role in addressing these challenges.
The DMC workshop will provide a forum to bring together researchers and practitioners interested in data management, cloud computing, and their intersection. It will be the founding workshop for the newly established GI working group “Data Management in the Cloud”. The DMC workshop calls for contributions that address research or system issues in cloud data management, including, but not limited to:
Data analytics and knowledge discovery (in the Linked Open Data cloud)
Data models and query languages
Parallel query processing and optimization
Theoretical models for parallel data processing
Scalable storage and indexing
Linked Open Data management: distributed querying, data views, indexing services
Transaction models
Resource and workload management
Benchmarking, tuning, and testing
Scientific data management
Scalable machine learning
Data privacy and security
System infrastructures
The DMC workshop welcomes descriptions of work-in-progress and preliminary results as well as experience reports, case studies, and demo descriptions. Papers can be written English or German and should not exceed 10 pages in length (LNI style). Papers must be submitted electronically in PDF format. Paper submissions is via EasyChair.

Last modified: 2012-10-18 17:20:10