Journal Information
Big Data Research
Impact Factor:

Call For Papers
The journal aims to promote and communicate advances in Big Data research by providing a fast and high quality forum for researchers, practitioners and policy makers from the very many different communities working on, and with, this topic.

The journal will accept papers on foundational aspects in dealing with Big Data, as well as papers on specific Platforms and Technologies used to deal with Big Data.

To foster interdisciplinary collaboration between fields, and to showcase the benefits of data driven research, papers demonstrating applications of big data in domains as diverse as Geoscience, Social Web, Finance, e–Commerce, Health Care, Environment and Climate, Physics and Astronomy, Chemistry, life sciences and drug discovery, digital libraries and scientific publications, security and government will also be considered.

The journal may publish whitepapers on policies, standards and best practices.
Last updated by Dou Sun in 2019-12-04
Special Issues
Special Issue on Interactive Big Data Visualization and Analytics
Submission Date: 2020-09-01

Introduction Information Visualization is nowadays one of the cornerstones of Data Science, turning the abundance of Big Data being produced through modern systems into actionable knowledge. Indeed, the Big Data era has realized the availability of voluminous datasets that are dynamic, noisy and heterogeneous in nature. Transforming a data-curious user into someone who can access and analyze that data is even more burdensome now for a great number of users with little or no support and expertise on the data processing part. Thus, the area of data visualization, visual exploration and analysis has gained great attention recently, calling for joint action from different research areas from the HCI, Computer graphics and Data management and mining communities. In this respect, several traditional problems from these communities such as efficient data storage, querying & indexing for enabling visual analytics, new ways for visual presentation of massive data, efficient interaction and personalization techniques that can fit to different user needs are revisited. The modern exploration and visualization systems should nowadays offer scalable techniques to efficiently handle billion objects datasets, limiting the visual response in a few milliseconds along with mechanisms for information abstraction, sampling and summarization for addressing problems related to visual information overplotting. Further, they must encourage user comprehension offering customization capabilities to different user-defined exploration scenarios and preferences according to the analysis needs. Overall, the challenge is to offer self-service visual analytics, i.e. enable data scientists and business analysts to visually gain value and insights out of the data as rapidly as possible, minimizing the role of IT-expert in the loop. This special issue aims to publish work on multidisciplinary research areas spanning from Data Management and Mining to Information Visualization and Human-Computer Interaction. Paper Submission Format and Guidelines All submitted papers must be clearly written in English and must contain only original work, which has not been published by, or is currently under review for, any other journal, conference, symposium, or workshop. Submissions are expected to not exceed 30 pages (including figures, tables, and references) in the journal's single-column format using 11 point font. Detailed submission guidelines are available under "Guide for Authors" at: All manuscripts and any supplementary material should be submitted through the Elsevier Editorial System (EES). The authors must select "VSI: Interactive Visualization" as Article Type when they reach the Article Type step in the submission process. The EES website is located at: All papers will be peer-reviewed by at least three independent reviewers. Requests for additional information should be addressed to the guest editors. Topics for the Special Issue Topics of interest include, but are not limited to: - Visualization, exploration & analytics techniques for various data types; e.g., stream, spatial, high-dimensional, graph - Human-in-the-loop processing - Human-centered databases - Data modeling, storage, indexing, caching, prefetching & query processing for interactive applications - Interactive machine learning - Interactive data mining - User-oriented visualization; e.g., recommendation, assistance, personalization - Visualization & knowledge; e.g., storytelling - Progressive analytics - In-situ visual exploration & analytics - Novel interface & interaction paradigms - Visual representation techniques; e.g., aggregation, sampling, multi-level, filtering - Scalable visual operations; e.g., zooming, panning, linking, brushing - Scientific visualization; e.g., volume visualization - Analytics in the fields of scholarly data, digital libraries, multimedia, scientific data, social data, etc. - Immersive visualization - Interactive computer graphics - Setting-oriented visualization; e.g., display resolution/size, smart phones, visualization over networks - High performance, distributed & parallel techniques - Visualization hardware & acceleration techniques - Linked Data & ontologies visualization - Benchmarks for data visualization & analytics - Case & user studies - Systems & tools
Last updated by Dou Sun in 2019-12-04
Related Conferences