Call for Papers

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Most areas of science, simulations and experiments are flooded with data, with some areas facing exabytes of data in near term. This includes not only static, but also dynamic datasets (where data is continuously streamed and need to be analyzed in real time). This trend towards more data is likely to continue in the foreseeable future.

Everyone – from scientists and artists to citizens and representatives – faces daunting problems in making use of this expanding digital resource. Our ability to manage, mine, analyze, and visualize the data is fundamental to the knowledge discovery process. The value of data at extreme scale can be fully realized only if we have end-to-end solutions, which demands collective, inter-disciplinary efforts to develop.

The Large Scale Data Analysis and Visualization (LDAV) symposium, to be held in conjunction with IEEE VisWeek 2012, is specifically targeting solutions to this end-to-end problem. It requires attention from a range of experts – from computer science and beyond – the goal of the LDAV symposium is to bring together domain scientists, data analytics and visualization researchers, users, designers and artists to foster common ground for solving problems that face us now, and those that face us in the years ahead.

Best Paper Award

LDAV committee will award a Best Paper award to the authors whose submission is deemed the strongest to the conference according to the reviewing criteria.  Best Paper award will be announced at the LDAV reception.


Papers Submission Deadline: Reference LDAV Important Dates

Papers Format Requirements can be found here.

Paper Submission Site Go to the submission site log in, and select 'Submit to LDAV 2012 Papers'

All papers should be directly related to collection, analysis, manipulation or visualization of large-scale data. Topics of interest include, but are not limited to:


  • ▪ Data collection, management and curation
  • ▪ Novel, extreme or innovative methods for understanding and interacting with data
  • ▪ Streaming methods for analysis, collection and visualization
  • ▪ Advanced hardware for data handling or visualization
  • ▪ Collaboration or co-design of data analysis with domain scientists
  • ▪ Distributed or Multi-threaded approaches
  • ▪ MapReduce-based methods, algorithms or approaches
  • ▪ Hierarchical data storage, retrieval or rendering
  • ▪ Novel interaction techniques specific to large data
  • ▪ Topics in cognitive issues specific to manipulating and understanding large data
  • ▪ Case studies (4 pages is sufficient)
  • ▪ Industry solutions for large data

Papers on any topic can be short (4 pages) or long (8 pages), with the author determining length based on the content. Because the symposium will include a variety of presentation lengths, the LDAV committee will offer presentation slots independent of the length of paper.