==== ACM Transactions on Data Science Special Issue on Data Science for Next-generation Big Data ==== Guest Editors: Yanyan Shen, Anh Dinh, H. V. Jagadish https://dl.acm.org/pb-assets/static_journal_pages/tds/pdf/tds-cfp-special-issue-data-science-next-gen-big-data-1603646817537.pdf Background The first age of Big Data started roughly 10 years ago. It has had an enormous impact in many fields of science. It underlies the rapid development of data-driven applications and gives rise to many innovative data processing systems. Ten years on, Big Data is entering a new generation. In particular, data is being used at a much larger, global scale. Furthermore, there is a trend of multiple data owners coming together to perform collaborative data analytics, and many data-driven business decisions are made based on statistical analytics from multi-source, multimodal, and worldwide data. The new generation of Big Data opens the door for innovative data-driven applications that are not possible even in the early age of Big Data. However, the new scale, both in terms of the data, and the number of participants, bring significant challenges ranging from secure data sharing to federated data analytics. At the same time, emerging technologies such as 5G, AI and blockchains demand high-performance, scalable and secure data management. It is therefore crucial to have new theories, algorithms, and systems, for future applications that make various trade-offs between security, performance, and data quality, in this new age of Big Data. Research efforts from multiple disciplines that contribute to data science including statistical theory, data management, data mining, machine learning, etc., are needed to realize the potentials of next-generation Big Data. Topics of interests include, but not limited to, the following: > Federated data collection and statistical analysis > Scalable data management for 5G, AI, and blockchains > Multi-domain, multi-party data analytics and AI practices > Data security for distributed learning > Privacy-preserving data sharing for federated learning > Data lake management systems, theory, and applications Important Dates * Submissions deadline: March 31st, 2021 * First-round review decisions: June 30th, 2021 * Deadline for revision submissions: September 30th, 2021 * Notification of final decisions: November 30th, 2021 * Tentative publication: January 31st, 2022 Submission Information Before submitting, refer to the TDS journal scope (https://dl.acm.org/journal/tds/charter) and author guidelines (https://dl.acm.org/journal/tds/author-guidelines). All manuscripts considered must be prepared using the ACM template format and submitted as a PDF via the Manuscript Central submission site at https://mc.manuscriptcentral.com/tds. Select the paper type "Special Issue on Data Science for Next-generation Big Data".