MOTIVATION: The field of toxicogenomics (the application of '-omics' technologies to risk assessment of compound toxicities) has expanded in the last decade, partly driven by new legislation, aimed at reducing animal testing in chemical risk assessment but mainly as a result of a paradigm change in toxicology towards the use and integration of genome wide data. Many research groups worldwide have generated large amounts of such toxicogenomics data. However, there is no centralized repository for archiving and making these data and associated tools for their analysis easily available. RESULTS: The Data Infrastructure for Chemical Safety Assessment (diXa) is a robust and sustainable infrastructure storing toxicogenomics data. A central data warehouse is connected to a portal with links to chemical information and molecular and phenotype data. diXa is publicly available through a user-friendly web interface. New data can be readily deposited into diXa using guidelines and templates available online. Analysis descriptions and tools for interrogating the data are available via the diXa portal. AVAILABILITY AND IMPLEMENTATION: http://www.dixa-fp7.eu CONTACT: [email protected]; [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

In this work we present the rule-based approach used to evaluate the quality of scientific datasets in a policy support context. The used case study refers to real datasets in a context where low data quality limits the accuracy of the analysis results and, consequently, the significance of the provided policy advice. The applied solution consists in the identification of types of constraints that can be useful as data quality rules and in the development of a software tool to evaluate a dataset on the basis of a set of rules expressed in the XML\nmarkup language. As rule types we selected some types of data constraints and dependencies already proposed in data quality works, but we experimented also the use of order dependencies and existence constraints. The case study was used to develop and test the adopted solution, which is anyway generally applicable to other contexts.

We present a graph-based object model that may be used as a uniform framework for direct manipulation of multimedia information. After an introduction motivating the need for abstraction and structuring mechanisms in hypermedia systems, we introduce the data model and the notion of perspective, a form of data abstraction that acts as a user interface to the system, providing control over the visibility of the objects and their properties. A perspective is defined to include an intension and an extension. The intension is defined in terms of a pattern, a subgraph of the schema graph, and the extension is the set of pattern-matching instances. Perspectives, as well as database schema and instances, are graph structures that can be manipulated in various ways. The resulting uniform approach is well suited to a visual interface. A visual interface for complex information systems provides high semantic power, thus exploiting the semantic expressibility of the underlying data model, while maintaining ease of interaction with the system. In this way, we reach the goal of decreasing cognitive load on the user, with the additional advantage of always maintaining the same interaction style. We present a visual retrieval environment that effectively combines filtering, browsing, and navigation to provide an integrated view of the retrieval problem. Design and implementation issues are outlined for MORE (Multimedia Object Retrieval Environment), a prototype system relying on the proposed model. The focus is on the main user interface functionalities, and actual interaction sessions are presented including schema creation, information loading, and information retrieval.