Big Data Analytics 2014

Recently, data generation at the scale of terabytes/petabytes/exabytes have become commonplace in many scientific and commercial domains. Streaming data, social media content, electronic medical records, astronomy surveys, genomic and proteomic studies and similar areas generate data at a scale that is becoming increasingly difficult to manage using traditional database technologies. Big Data is an umbrella term used for such massive collections of data. Besides volume, analytics has to face challenges like heterogeneity, timeliness, complexity, velocity and privacy issues. The other challenge is to fuse data sources - of same type or multi-modal and perform joint analytics on the integrated data. The scale of such data poses significant challenges for analytics, going beyond what can be supported by conventional data, storage and retrieval models.

The International Conference on Big Data Analytics is set in this backdrop. The conference was conceived as part of a collaboration between the University of Delhi, India and the University of Aizu, Japan. The first two BDA conference was successfully held in New Delhi and Mysore (India) in December 2012 and 2013 respectively.

The goal of the conference is to generate interest among researchers, practitioners and policy makers by exposing them to ground breaking opportunities arising from analysis and processing of massive volumes of data. We invite researchers, developers, policy makers and users to participate in this event to share and discuss the emerging challenges in developing data management and data mining solutions, and frameworks around cloud and distributed computing platforms.

Major topics of interest include but are not limited to:
* Analytics as a Service
* Architectural Design for Big Data
* Big Data Ethics
* Big Data Governance
* Conceptual Models for Analytics
* Cognitive Models for Analytics
* Clustering of Big Data
* Data Centric Networking
* Data Fusion and Multi Modal Analytics
* Data Management in Clouds
* Data Models for Big Data Analytics
* Domain-specific Analytics
* Index Structures for Big Data Analytics
* Interaction Design for Exploratory Analytics
* Machine Learning techniques for Big Data
* Model Discovery from Big Data
* NoSQL and non-standard Data Models
* Physical Data Organization for Big Data
* Predictive Modeling
* Privacy Issues in Big Data Analytics
* Programming Models for Big Data Analytics
* Query Languages and Paradigms
* Rule Mining from Big Data
* Standards for Data Centers
* Scalability and Performance issues
* Security Analytics
* Semantics and Big Data
* Streaming Data Analytics
* Summarization and Materialized views
* Topic Modeling
* Unstructured and Semi-structured Data Mining
* Visual Analytics

Original, high-quality papers addressing the above and related topics are invited. We strongly encourage papers that report experimental work and results. Authors are invited to submit only PDF files. For preparing the manuscript, please see instructions for authors by Springer in the Lecture Notes in Computer Science (LNCS) series (http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0 ).

Research track submissions submissions must not exceed 20 pages in the LNCS style. The submissions will be accepted through EasyChair [https://www.easychair.org/conferences/?conf=bda20140]. Authors are required to submit an abstract of their paper as a expression of interest, before July 28, 2014, 23:59 PST. Full-length papers should be submitted before August 4, 2014, 23:59 PST.