The Mirror DBMS at TREC-8

The database group at University of Twente participates in TREC8 using the Mirror DBMS, a prototype database system especially designed for multimedia and web retrieval. From a database perspective, the purpose has been to check whether we can get sufficient performance, and to prepare for the very large corpus track in which we plan to participate next year. From an IR perspective, the experiments have been designed to learn more about the effect of the global statistics on the ranking

Quality of Service for Information Access

Information is available in many forms from different sources, in distributed locations; access to information is supported by networks of varying performance; the cost of accessing and transporting the information varies for both the source and the transport route. Users who vary in their preferences, background knowledge required to interpret the information and motivation for accessing it, gather information to perform many different tasks. This position paper outlines some of these variations in information provision and access, and explores the impact these variations have on the user’s task performance, and the possibilities they make available to adapt the user interface for the presentation of information

The CDF Data Handling System

The Collider Detector at Fermilab (CDF) records proton-antiproton collisions at center of mass energy of 2.0 TeV at the Tevatron collider. A new collider run, Run II, of the Tevatron started in April 2001. Increased luminosity will result in about 1~PB of data recorded on tapes in the next two years. Currently the CDF experiment has about 260 TB of data stored on tapes. This amount includes raw and reconstructed data and their derivatives. The data storage and retrieval are managed by the CDF Data Handling (DH) system. This system has been designed to accommodate the increased demands of the Run II environment and has proven robust and reliable in providing reliable flow of data from the detector to the end user. This paper gives an overview of the CDF Run II Data Handling system which has evolved significantly over the course of this year. An outline of the future direction of the system is given.Comment: Talk from the 2003 Computing in High Energy and Nuclear Physics (CHEP03), La Jolla, Ca, USA, March 2003, 7 pages, LaTeX, 4 EPS figures, PSN THKT00

Development of Distributed Research Center for analysis of regional climatic and environmental changes

We present an approach and first results of a collaborative project being carried out by a joint team of researchers from the Institute of Monitoring of Climatic and Ecological Systems, Russia and Earth Systems Research Center UNH, USA. Its main objective is development of a hardware and software platform prototype of a Distributed Research Center (DRC) for monitoring and projecting of regional climatic and environmental changes in the Northern extratropical areas. The DRC should provide the specialists working in climate related sciences and decision-makers with accurate and detailed climatic characteristics for the selected area and reliable and affordable tools for their in-depth statistical analysis and studies of the effects of climate change. Within the framework of the project, new approaches to cloud processing and analysis of large geospatial datasets (big geospatial data) inherent to climate change studies are developed and deployed on technical platforms of both institutions. We discuss here the state of the art in this domain, describe web based information-computational systems developed by the partners, justify the methods chosen to reach the project goal, and briefly list the results obtained so far

Decentralized provenance-aware publishing with nanopublications

Publication and archival of scientific results is still commonly considered the responsability of classical publishing companies. Classical forms of publishing, however, which center around printed narrative articles, no longer seem well-suited in the digital age. In particular, there exist currently no efficient, reliable, and agreed-upon methods for publishing scientific datasets, which have become increasingly important for science. In this article, we propose to design scientific data publishing as a web-based bottom-up process, without top-down control of central authorities such as publishing companies. Based on a novel combination of existing concepts and technologies, we present a server network to decentrally store and archive data in the form of nanopublications, an RDF-based format to represent scientific data. We show how this approach allows researchers to publish, retrieve, verify, and recombine datasets of nanopublications in a reliable and trustworthy manner, and we argue that this architecture could be used as a low-level data publication layer to serve the Semantic Web in general. Our evaluation of the current network shows that this system is efficient and reliable