Building scalable web applications on top of NoSQL data stores is becoming common practice. Many of these data stores can easily be accessed programmatically, and do not enforce a schema. Software engineers can design the data model on the go, a flexibility that is crucial in agile software development. The typical tasks of database schema management are now handled within the application code, usually involving object mapper libraries. However, today's Integrated Development Environments (IDEs) lack the proper tool support when it comes to managing the combined evolution of the application code and of the schema. Yet simple refactorings such as renaming an attribute at the source code level can cause irretrievable data loss or runtime errors once the application is serving in production. In this demo, we present ControVol, a framework for controlled schema evolution in application development against NoSQL data stores. ControVol is integrated into the IDE and statically type checks object mapper class declarations against the schema evolution history, as recorded by the code repository. ControVol is capable of warning of common yet risky cases of mismatched data and schema. ControVol is further able to suggest quick fixes by which developers can have these issues automatically resolved.

Large amounts of data often require expensive and time-consuming analysis. Therefore, highly scalable and efficient techniques are necessary to process, analyze and discover useful information. Database sampling has proven to be a powerful method to surpass these limitations. Using only a sample of the original large database brings the benefit of obtaining useful information faster, at the potential expense of lower accuracy. In this paper, we demonstrate \vfds, a novel fast database sampling system that maintains the referential integrity of the data. The system is developed over the open-source database management system, MySQL. We present various scenarios to demonstrate the effectiveness of VFDS in approximate query answering, sample size, and execution time, on both real and synthetic databases.

In unstructured information retrieval P2P systems, semantic heterogeneity comes from the use of different ontologies. Semantic interoperability refers to the ability of peers to communicate with each others. We take into account these notions separately, as raising two different problems. Hence we propose two independent and complementary solutions. The GoOD-TA protocol aims at reducing heterogeneity through ontology-driven topology adaptation. DiQuESh is a top-k algorithm for distributed information retrieval that is intended to ensure interoperability. This distinction enables highlighting their respective benefits on the IR performances and leads to a modular architecture. For our experiments we obtained a set of actively used real-world ontologies through the NCBO BioPortal. We implemented GoOD-TA and DiQuESH in Java and used the PeerSim simulator. We first show that GoOD-TA nicely reduces the semantic heterogeneity related to the system topology, handles the evolution of peers' descriptors, and is suitable for dynamic systems. Then, GoOD-TA and DiQuESh are run simultaneously, with a significant increase of precision and recall. This enables to identify the indirect contribution of heterogeneity reduction obtained with GoOD-TA to improving interoperability.

We consider P2P data sharing systems in which each participant uses an ontology to represent information. If all the partipants do not use the same ontology, the system is said to be semantically heterogeneous. Several methods have been proposed to reach a degree of interoperability but thorough evaluation of these methods is prevented by a lack of tools to describe the situations in which they have been tested. In this paper we identify components that impact on the semantic heterogeneneity, and we define several complementary measures to capture the different facets of heterogeneity. Proposed measures allow to characterize the situation in which a method is evaluated, or to measure the heterogeneity reduction produced by another method.