ASONAM 2027FAB 2027
Big Data is an emerging research trend in many disciplines. The Big Data research includes challenges like analysis, capture, curation, search, sharing, storage, transfer, visualization, and privacy violations. The trend to larger data sets equates to additional information that could be derived from analysis of a single large set of related data, as well as comparing and correlating information from more than one datasets that allow correlations to be found to spot business trends, prevent diseases, combat crime, customer behaviour patterns and many more. To build and enable infrastructures to handle and process Big Data may need to focus on velocity, variety, volume, variability, veracity and complexity of large-scale datasets. Accepted and presented papers will be included in ASONAM 2026 Conference Proceedings and forwarded for inclusion in Springer LNCS. The conference proceedings will be submitted for EI indexing as part of Springer LNCS. The proceedings will be also covered by several other indexes, including DBLP, SCOPUS, etc. High-quality research papers accepted for publication in the conference proceedings will be invited to submit an extended version for a book to be published in Springer's Lecture Notes in Social Networks (LNSN) series, subject to additional peer reviewing.