Overall Objectives
Scientific Foundations
Application Domains
New Results
Contracts and Grants with Industry
Other Grants and Activities

Section: Overall Objectives


Today's hard problems in data management go well beyond the traditional context of Database Management Systems (DBMS). These problems stem from significant evolutions of data, systems and applications. First, data have become much richer and more complex in formats (e.g., multimedia objects), structures (e.g., semi-structured documents), content (e.g., incomplete or imprecise data), size (e.g., very large volumes), and associated semantics (e.g., metadata, code). The management of such data makes it hard to develop data-intensive applications and creates hard performance problems. Second, data management systems need to scale up to support large-scale distributed systems and deal with both fixed and mobile clients. In a highly distributed context, data sources are typically in high number, autonomous and heterogeneous, thereby making data management difficult. Third, this combined evolution of data and systems gives rise to new, typically complex, applications with ubiquitous, on-line data access: collaborative content management (e.g. Wiki), virtual libraries, virtual stores, global catalogs, services for personal content management, etc.

The general problem can be summarized as complex data management in distributed systems . The Atlas project-team addresses this problem with the objective of designing and validating new solutions with significant advantages in functionality and performance. To tackle this objective, we now focus on data management in two large-scale distributed contexts: the web and P2P systems. In the context of the web, we consider information systems with autonomous participants (with heterogeneous data and different interests) and deal with the problems of data integration, data classification and data access. In the context of P2P systems, we capitalize on our experience in developping the APPA system, with various data management services (replication, caching, queries, clustering, privacy testing, etc.). We have also started to work on data management in a third context, that of multicore, because it promises to revolutionize basic data management tehcniques. In this context, we address the problem of real-time data access through transactional.


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