Enormous amounts of data are already present and still rapidly growing due to data sources such as sensors and social networks. There has been an increasing interest in incorporating these huge amounts of external and unstructured data, normally referred to as “Big Data”, into traditional applications. This necessity has made that traditional database systems and processing need to evolve and accommodate them. We view that several key themes with the Big Data trends include

• managing Big Data projects to discover business values.
• developing an architecture for a Big Data environment to conceptualize goals, tasks, and problem-solving methods to apply to domains.
• Exploring problem-solving methods for Big Data.
• Using a cloud for managing large-scale external and internal data.
• Providing an easy-to-use but powerful services to access/manage/analyze the Big Data in the cloud.
• Exploring and improving the security and privacy of these repositories.

Therefore, this new era of Big Data and cloud environment requires conceptualization and methods to effectively manage Big Data and accomplish intended business goals. Thus, the objective of MoBiD’ 17 is to be an international forum for exchanging ideas on the latest and best proposals for modeling and managing Big Data in this new data-driven paradigm. Papers focusing on novel applications and using conceptual modeling approaches for any aspects of Big Data such as Hadoop and its ecosystems, Big Data Analytics, social networking, security/cyber resilience/privacy, hybrid cloud, Big Data warehousing, data science topics, and industry-specific challenges that arise in Big Data scenarios (e.g. in Customer Relationship Management), and how to approach them from a modelling as well as from an implementation perspective are highly encouraged. The workshop will be a forum for researchers and practitioners who are interested in the different facets related to the use of the conceptual modeling approaches for the development of next generation applications based on Big Data.

The scope of the workshop includes several aspects of conceptual modeling in data-driven paradigm, but is not limited to:

• Agile modeling for big data
• Advanced applications with Hadoop or Spark frameworks
• Application design and architecture of big data environment
• Big Data Analytics
• Data Stream Mining
• Business Process and Dependency Modeling
• Business Intelligence applications and modeling
• Conceptual modeling approaches for Big Data
• Conceptualization for data-drive paradigm
• Data-driven businesses
• Using data science approaches for novel analysis and applications
• Enterprise modeling and architectures for big data projects
• Architectures and Methodologies for Big Data Applications
• (Omni-Channel) CRM Platforms
• Data Integration in Big Data environments
• Data Integration and management for Hadoop ecosystems
• Data virtualization, ELT, or ETL for data integration
• Information packaging
• Knowledge management for big data
• Metamodeling
• Modeling and management for social network data
• Novel applications in Big Data
• Interface design and visualization for big data
• Model-driven development methodologies and approaches
• Differences to Traditional Conceptual Modeling (e.g., in a Data Warehouse context)
• Provenance modeling
• Requirements modeling for Web-based applications
• Security, resiliency and privacy in social networks and other big data environments
• Software as a Service (SaaS) modeling solutions
• Analytics for complex data
• Cloud-based analytics
• Social Media Analytics
• Sensor Analysis
• Stream and In-memory Processing
• Data mining and warehousing over the cloud
• ETL over the cloud
• Hybrid cloud
• Modeling and management in IOT domains
• Smart Cities
• Smart health
• Education for big data and data science

MoBiD 2017 proceedings will be part of the ER2017 Workshop volume published by Springer in the LNCS series. The authors must submit manuscripts using the Springer-Verlag LNCS style for Lecture Notes in Computer Science. See the page
http://www.springer.de/comp/lncs/authors.html
for style files and details. The page limit for workshop papers is 10 pages.

The organizers will oversee a peer-review process for the submitted papers. Manuscripts not submitted in the LNCS style or having more than 10 pages will not be reviewed and thus automatically rejected. The papers need to be original and not submitted or accepted for publication in any other workshop, conference, or journal. Submission to MoBiD 2017 will be electronically only.