********************************************************************************** CALL FOR PAPERS Special Issue on Breakthroughs on Cross-Cutting Data Management, Data Analytics and Applied Data Science Information Systems Frontiers (Springer journal) - https://link.springer.com/journal/10796 ************************************************************************************ ***Time Scale*** Submission Due: April 30th, 2019 1st Review Notification: July 31th, 2019 Revision Due: September 30th, 2019 Final Notification: October 31th, 2019 ***Goal*** Over the last few years, research on database and information system technologies has been rapidly evolving thanks to the new paradigms of software and hardware adopted by modern scientific and more invasive applications. Presently, a huge and heterogeneous amount of data can be efficiently collected, integrated, stored, managed, andanalyzed for novel and more interesting data-driven applications. The growing relevance of non-traditional domains such as bioinformatics, social networking, mobile computing, sensor applications, smart cities, and gaming are generating increasing quantities of data complex in contents, heterogeneous in formats and often order of Terabytes in amount. These novel domains result in articulate ecosystems that include areas such as human resources,business processes, processes of data and information, IoT, mobile equipment etc. This scenario provides unprecedented opportunities to work on exciting problems, but also raises many new challenges for data management, storage, process and mining. Heterogeneous data collected from different sources should be adequately combined, integrated and stored to ensure efficient and effective data exploration and understanding. Moreover, while information sharing is essential in today's business and social networks, such sharing should not violate security and privacy requirements. Particular attention should also be devoted to the involvement of the end-user in the entire process to enhance her/his exploitation and understanding of data and knowledge as well as to make the user a valuable data provider. Data management and analytics solutions will perform better when users can interact with systems and the systems take account of the cognitive and physiological characteristics of the people involved to provide personalized data processing and analytics. The aim of this special issue is to disseminate cutting-edge contributions from various application domains representing new trends in the far reaching research areas of databases, information systems and data analytics. The special issue is expected to include papers that span a wide range of topics in the field of data collection, integration, storage, mining, knowledge, and visualization, from methodological, technological and applied data science innovation aspects. Contributions in this special issue should be of interest to a large and varied cross-disciplinary audience of researchers and practitioners involved or interested from different perspectives in this topic. The special issue welcomes submissions of technical, experimental, methodological papers, application papers, and papers on experience reports in real-life domains. ***Topics of interest include, but are not limited to:*** - Research challenges on data management and analytics - Methodologies, models, algorithms, and architectures for data science - Big Data frameworks and architectures - Data warehouses and large-scale databases - NoSQL and NewSQL databases - Metadata management - Scalable and/or descriptive data mining algorithms - Real-time analytics - Machine learning and deep learning techniques for knowledge discovery - Reinforcement learning models - Cloud computing techniques for data science - Crowdsourcing and collaborative analyses - Personalization and recommendation techniques for Big and small Data - Question answering techniques and systems - Visualization methods for data-intensive applications - Applied data science - Experiences with data-driven project development and deployment In one of - though not limited to - the following application scenarios: - Bio-sciences and healthcare - Internet of Things - Urban economy and urban environments - Financial applications - Customer relationship management - Agriculture - Mobile applications - e-commerce - Business analytics and finance - User-generated content (like tweets, micro-blog) - Industry 4.0 ***Guest Editors*** Silvia Chiusano (Politecnico di Torino, Torino, Italy) silvia.chiusano@polito.it Tania Cerquitelli (Politecnico di Torino, Torino, Italy) tania.cerquitelli@polito.it Robert Wrembel (Poznan University of Technology, Poznan, Poland) Robert.Wrembel@cs.put.poznan.pl Daniele Quercia (Nokia Bell Labs, Cambridge, UK) daniele.quercia@gmail.com ***Submission guidelines*** Paper submissions must conform to the Information Systems Frontiers format guidelines available at http://www.springer.com/business/business+information+systems/journal/10796 Manuscripts must be submitted to the ISF-Springer online submission system at http://www.editorialmanager.com/isfi. Authors need to select: "Special issue: Breakthroughs on Cross-Cutting Data Management, Data Analytics and Applied Data Science" during the submission process. Submissions to this Special Issue must represent original material that has been neither submitted to, nor published in, any other journal. A submission based on one or more papers that appeared elsewhere should have at least 30% of novel valuable content that extends the original work (the original papers should be referenced and the novel contributions should be clearly stated in the submitted paper).