Data* Track – Call for Papers

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Submission and publication: Ongoing

Track editors: Manish Parashar (Rutgers University) and George K. Thiruvathukal (Loyola University Chicago)

The data-centric era is characterized by a wide range of diverse data sources, from extreme scale simulations to instruments, experiments, and pervasive sensor systems. Increasing data quantity and availability has the potential to revolutionize science, engineering, and society in general. However, it will also create challenges—such as data heterogeneity, quality uncertainty, and transporting and processing costs—that will require new paradigms and practices in data management and analytics and supporting software stacks before that potential can be realized.

This peer-reviewed track covers all things data—from data science and analytics to extreme data. The goal is to explore fundamental challenges and state-of-the-art solutions, such as innovative algorithms, implementation frameworks, and software stacks that can accelerate insights from extreme data. We are particularly interested in submissions that address real deployments and experiences in production environments with an emphasis on reproducible results, as well as end-to-end application workflows and relevant experiences with real scientific and engineering domain applications.

We strongly encourage submissions that include multimedia, data, and community content, which will be featured online. If your submission includes such materials, please let the track editors know at cise-data@computer.org.

Submission Guidelines

Before submitting, we encourage authors to send a 250-word abstract at cise-data@computer.org so that the track editors can evaluate whether your idea fits within the scope of this special track.

When writing your article, please refer to the CiSE-specific author guidelines and the general author guidelines. Authors are asked to submit high-quality original work that has neither appeared in nor is under consideration by other journals.  All submissions will be peer-reviewed following standard journal practices. Manuscripts based on previously published conference papers must be extended substantially to include at least 30 percent new material.

Please submit electronically through ScholarOne Manuscripts, selecting this track option and including complete contact information for all authors. If you have any questions about submitting your article in ScholarOne Manuscripts, contact the peer-review coordinator at cise@computer.org.

Questions?

Contact the track editors at cise-data@computer.org.