Data access and integration in the ISPIDER proteomics grid

Grid computing has great potential for supporting the integration of complex, fast changing biological data repositories to enable distributed data analysis. One scenario where Grid computing has such potential is provided by proteomics resources which are rapidly being developed with the emergence of affordable, reliable methods to study the proteome. The protein identifications arising from these methods derive from multiple repositories which need to be integrated to enable uniform access to them. A number of technologies exist which enable these resources to be accessed in a Grid environment, but the independent development of these resources means that significant data integration challenges, such as heterogeneity and schema evolution, have to be met. This paper presents an architecture which supports the combined use of Grid data access (OGSA-DAI), Grid distributed querying (OGSA-DQP) and data integration (AutoMed) software tools to support distributed data analysis. We discuss the application of this architecture for the integration of several autonomous proteomics data resources

06472 Abstracts Collection - XQuery Implementation Paradigms

From 19.11.2006 to 22.11.2006, the Dagstuhl Seminar 06472 ``XQuery Implementation Paradigms'' was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

Visually querying object-oriented databases

Bibliography: pages 141-145.As database requirements increase, the ability to construct database queries efficiently becomes more important. The traditional means of querying a database is to write a textual query, such as writing in SQL to query a relational database. Visual query languages are an alternative means of querying a database; a visual query language can embody powerful query abstraction and user feedback techniques, thereby making them potentially easier to use. In this thesis, we develop a visual query system for ODMG-compliant object-oriented databases, called QUIVER. QUIVER has a comprehensive expressive power; apart from supporting data types such as sets, bags, arrays, lists, tuples, objects and relationships, it supports aggregate functions, methods and sub-queries. The language is also consistent, as constructs with similar functionality have similar visual representations. QUIVER uses the DOT layout engine to automatically layout a query; QUIVER queries are easily constructed, as the system does not constrain the spatial arrangement of query items. QUIVER also supports a query library, allowing queries to be saved, retrieved and shared among users. A substantial part of the design has been implemented using the ODMG-compliant database system O₂, and the usability of the interface as well as the query language itself is presented. Visual queries are translated to OQL, the standard query language proposed by the ODMG, and query answers are presented using O₂ Look. During the course of our investigation, we conducted a user evaluation to compare QUIVER and OQL. The results were extremely encouraging in favour of QUIVER

Greeks and Trojans Together

This paper describes a comprehensive solution for the integration of object oriented ontology representation frameworks with logic-based agent communication frameworks. The proposed solution addresses the problem at both the agent communication level and the agent implementation level. At the agent communication level, we propose to extend logic content languages with some domain independent operators that allow building logic constructs as propositions from domain dependent entities defined in an object oriented ontology. At the implementation level, we propose to use object-oriented databases as the support for the agent information. Finally, we propose an automatic mechanism for translating agent messages using the extended content language into ODMG OQL commands, which are then used to interact with the object-oriented database. This binding mechanism relies on a special purpose data dictionary representing the mapping between the domain ontology and the agent internal database

Web and Semantic Web Query Languages

A number of techniques have been developed to facilitate powerful data retrieval on the Web and Semantic Web. Three categories of Web query languages can be distinguished, according to the format of the data they can retrieve: XML, RDF and Topic Maps. This article introduces the spectrum of languages falling into these categories and summarises their salient aspects. The languages are introduced using common sample data and query types. Key aspects of the query languages considered are stressed in a conclusion

K2/Kleisli and GUS: Experiments in Integrated Access to Genomic Data Sources

The integration of heterogeneous data sources and software systems is a major issue in the biomed ical community and several approaches have been explored: linking databases, on-the- fly integration through views, and integration through warehousing. In this paper we report on our experiences with two systems that were developed at the University of Pennsylvania: an integration system called K2, which has primarily been used to provide views over multiple external data sources and software systems; and a data warehouse called GUS which downloads, cleans, integrates and annotates data from multiple external data sources. Although the view and warehouse approaches each have their advantages, there is no clear winner . Therefore, users must consider how the data is to be used, what the performance guarantees must be, and how much programmer time and expertise is available to choose the best strategy for a particular application

Reasoning & Querying – State of the Art

Various query languages for Web and Semantic Web data, both for practical use and as an area of research in the scientific community, have emerged in recent years. At the same time, the broad adoption of the internet where keyword search is used in many applications, e.g. search engines, has familiarized casual users with using keyword queries to retrieve information on the internet. Unlike this easy-to-use querying, traditional query languages require knowledge of the language itself as well as of the data to be queried. Keyword-based query languages for XML and RDF bridge the gap between the two, aiming at enabling simple querying of semi-structured data, which is relevant e.g. in the context of the emerging Semantic Web. This article presents an overview of the field of keyword querying for XML and RDF

A Domain-Specific Conceptual Query System

This thesis presents the architecture and implementation of a query system resulted from a domain-specific conceptual data modeling and querying methodology. The query system is built for a high level conceptual query language that supports dynamically user-defined domain-specific functions and application-specific functions. It is DBMS-independent and can be translated to SQL and OQL through a normal form. Currently, it has been implemented in neuroscience domain and can be applied to any other domain