Workshops

Workshops co-located with ICDE 2012:

Data-Driven Decision Guidance and Support Systems (DGSS)

Decision support systems (DSS) are widely used to support business or organizational decision-making at the management, operations and planning levels of an organization. Decision guidance systems (DGS) are decision support systems that go beyond organizing and displaying information, providing actionable recommendations to and extracting knowledge from human decision-makers. More specifically, Decision Guidance and Support Systems (DGSS) often need to

use and mine large amounts of data collected from multiple sources
learn deterministic or stochastic models of underlying processes from historical data
learn objectives or decision preferences from decision makers‚ responses
perform optimization under diverse constraints, e.g., from business or engineering limitations and laws of nature, and
present and justify actionable recommendations to decision makers.

This workshop will bring together DGSS researchers and practitioners to present novel methodologies, models, algorithms, systems, tools, applications and case studies of DGSS. Most importantly, the workshop will be a forum to discuss how to utilize advances from multiple disciplines for building DGSS that can intelligently merge human knowledge and expertise with formal mathematical models to make better decisions. The workshop will include both formal presentations and informal discussion of important research directions in DGSS, and their interactions with Knowledge and data engineering.

Data Engineering meets the Semantic Web (DESWEB)

The 3rd International Workshop on Data Engineering Meets the Semantic Web (DESWEB) aims to bring together researchers, developers and practitioners working in the intersection between Databases and Semantic Web. In particular, DESWEB welcomes papers describing two broad kinds of research: (1) using established database techniques for managing Semantic Web Data; (2) exploring how Semantic Web ideas, principles and technologies can be used to solve data management problems.

Data Management in the Cloud (DMC)

The cloud computing has emerged as a promising computing and business model. By providing on-demand scaling capabilities without any large upfront investment or long-term commitment, it is attracting wide range of users. The database community has also shown great interest in exploiting this new platform for data management services in a highly scalable and cost-efficient manner. As a result, the cloud computing presents challenges and opportunities for data management. The DMC workshop aims at bringing researchers and practitioners in cloud computing and data management systems together to discuss the research issues at the intersection of those areas, and also to draw more attention from the larger data management research community to this new and highly promising field.

Graph Data Management: Techniques and Applications (GDM)

Recently, there has been a lot of interest in the application of graphs in different domains. They have been widely used for data modeling of different application domains such as chemical compounds, multimedia databases, protein networks, social networks and semantic web. With the continued emergence and increase of massive and complex structural graph data, a graph database that efficiently supports elementary data management mechanisms is crucially required to effectively understand and utilize any collection of graphs.

The overall goal of the workshop is to bring people from different fields together, exchange research ideas and results, and encourage discussion about how to provide efficient graph data management techniques in different application domains and to understand the research challenges of such area.

Secure Data Management on Smartphones and Mobiles (SDMSM)

In this workshop, we focus on the data management challenges that arise from the use of enterprise and other privacy sensitive data on mobile devices such as smartphones.

Topics of Interest include (but not limited to)

Enterprise and Device level Support for handling sensitive data
Data transformation of enterprise data on mobile devices
Enterprise data storage mechanisms on mobile devices
Classification and segregation of personal and enterprise data
Regulatory compliance issues of enterprise data on mobile devices
Management and control of on-device sensory data
Smartphone privacy and security policies
Enforcement of enterprise privacy policies on mobile end point devices
Run time monitoring of device resource usage and data flows
Security audit and Forensics
Secure application development
Mobile Application Certification and malware detection
Secure Identity Management
Hardware based security solutions

Self-Managing Database Systems (SMDB)

Autonomic, or self-managing, systems are a promising approach to achieve the goal of systems that are easier to use and maintain in the face of growing system complexity. A system is considered to be autonomic if it is self-configuring, self-optimizing, self-healing and/or self-protecting. The aim of the SMDB workshop is to provide a forum for researchers from both industry and academia to present and discuss ideas and experiences related to self-management and self-organization in all areas of Information Management (IM) ingeneral. SMDB targets not only classical databases but also the new generation of storage engines such as column stores, key-value stores and in-memory databases. Beyond databases SMDB aims to cover autonomic aspects of data intensive systems represented by large-scale map-reduce (e.g., Hadoop) and cloud environments where much work on self-management is needed. Last but not least, SMDB wants to expand its horizons to include self-management of non-traditional, new areas of IM such as social networks and peer-to-peer systems.

Topics of Interest (but not limited to these):

Principles and architecture of autonomic data management systems
Self-capabilities in databases and storage systems
Data management in cloud and multi-tenant databases
Autonomic capabilities in database-as-a-service platforms
Automated testing of data management systems
Automated physical database design and adaptive query tuning
Automated provisioning and integration
Automatic enforcement of information quality
Self-managing distributed / decentralized / peer-to-peer information systems
Self-managing and adaptive aspects in social network systems
Monitoring and diagnostics in data management systems
Policy automation and visualization for datacenter administration
User acceptance and trust of autonomic capabilities
Evaluation criteria and benchmarks for self-managing systems
Use cases and war stories on deploying autonomic capabilities

Spatio Temporal data Integration and Retrieval (STIR)

This workshop is focused on making the research in information integration and retrieval more relevant to the challenges in systems with significant spatial and temporal components. The workshop will build upon traditional themes of interest namely integration architectures, information extraction, record linkage, named entity extraction, source meta-data learning, query execution and optimization. However, we will give special emphasis to how this can be applied to integrating information arising from systems that are (likely to be) deployed over wide geographic spaces, and collects and uses data that changes over time. Sensor based systems for measuring flow of traffic, water consumption etc are one such area of interest. In dealing with such systems, we must also account for noise arising due to the variability in the data collection, sharing and interpretation models techniques used as well as the noise introduced by data loss by the physical devices themselves.