BigDataMAPS seeks to promote novel contributions in the field of big data processing and management, big data analytics and big data privacy and security. The aim of this workshop is to become a regular, interdisciplinary exchange forum for researchers and practitioners interested in big data as a research object. By exchanging research results, experiences, and products, the ultimate goal is to conceive new trends and ideas on designing, implementing and evaluating solutions for efficient, safe, reliable and compliant information sharing, with an eye to the cross-relations between ICT and regulatory aspects of data management.
Information sharing is essential for today's business and societal transactions. Nevertheless, such a sharing should not violate the security and privacy requirements either dictated by Law to protect data subjects or by internal regulations, which can be provided both at the organization and at the individual level. An effectual, rapid, and unfailing electronic data sharing among different parties, while protecting legitimate rights on these data, is a key issue with several shades. Among them, how to translate the high-level law obligations, business constraints, and users' requirements into system-level security and privacy policies, and how to engineer efficient and practical technical solutions for policy definition and enforcement.
Topics of interest for this workshop include but are not limited to the following, and should not be limited to an IT perspective: Anonymity in the cloud; Applied cryptography in the cloud; Agent-based modeling and simulation; Big data integration; Big data mining; Big data modeling; Big data quality; Big data semantics; Big data storage strategies; Big data warehousing and OLAP; Cloud architectures; Crowdsourcing and collaborative analyses; Complex (semi-structured, stream, textual, graph, multimedia, open, linked...) data; Data availability, integrity, privacy, reliability... in the cloud; Data lakes; Dataviz; Energy-efficient computing; Distributed and/or parallel processing and computing environments; Machine learning, deep learning; Metadata management; NoSQL and NewSQL databases; On-demand analytics; Performance optimization and benchmarks; Real-time analytics; Scalability; Smart Cloud. Moreover, applications may lie in the fields of Digital humanities, Healthcare, Manufacturing, Smart cities, Agriculture, Bioinformatics, Supply chain management, Customer relationship management, Social media, Internet of things, Recommender systems, Alert systems, Mobile applications, etc.