相关费用:有费用︾All new manuscripts submitted to Big Data will be assessed the following mandatory Publishing Services Fees:
Page Charges (assessed upon acceptance): $90/page
Investment in the long-term impact of your manuscript
Big Data offers a number of optional ways to increase the impact of your published work:
Color Figures: Publishing figures in color ensures the detailed nuances of art, images, charts, and figures are accurately and vividly conveyed to readers. Online publication of color figures is free of charge. To publish color figures in print, a fee of $800 applies and covers an unlimited number of figures.
Open Access: Open Access guarantees the broadest possible discoverability, visibility, and access for your work in perpetuity. When you choose to publish open access with us, you become part of an innovative and vibrant community committed to research quality, transparency, and inclusivity. An Article Processing Charge (APC) of $3,600 applies to publishing open access in this journal.
Post-Publication/Retrospective Open Access: Post-publication/retrospective open access applies a CC BY license to your previously published manuscript. Because this option requires the re-processing and re-deposit of your manuscript to hosting platforms and indexing services, a fee of $1,000 applies in addition to the above-mentioned APC.
Errata: Prior to publication, you will receive two (2) proofs of your article to review for accuracy and to ensure the manuscript meets your expectations. Should you require a correction after approval of the final proof and subsequent publication of your manuscript, you may be assessed a fee of $100/affected page, depending on the nature of the request.
投稿方式--官网投稿
研究方向:计算机科学-COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS计算机:跨学科应用;COMPUTER SCIENCE, THEORY METHODS计算机:理论方法
出版地址:MARY ANN LIEBERT, INC, 140 HUGUENOT STREET, 3RD FL, NEW ROCHELLE, USA, NY, 10801
期刊简介:Big Data《大数据》(双月刊). Big Data is the leading peer-reviewed journal covering the challenges and opportunities in collecting, analyzing, and disseminating vast amounts of data. The Journal addresses questions surrounding this powerful and growing field of data science and facilitates the efforts of researchers, business managers, analysts, developers, data scientists, physicists, statisticians, infrastructure developers, academics, and policymakers to improve operations, profitability, and communications within their businesses and institutions.