SciPort: An Adaptable Scientific Data Integration Platform for Collaborative Scientific Research

Fusheng Wang, Gerald Madlmayr

Research output: Chapter in Book/Report/Conference proceedingsConference contribution

4 Citations (Scopus)

Abstract

Scientific data are posing new challenges to data management due to the large volume, complexity and heterogeneity of the data. Meanwhile, scientific collaboration becomes increasingly important, which relies on integrating and sharing data from distributed institutions. In this demo, we present SciPort, a Web-based platform on supporting scientific data management and integration based on peer-to-peer architectures, where researchers can easily collect, publish, and share their complex scientific data across multi-institutions. SciPort provides a general metadata based data model to capture the context description of experiments and link experiment data into comprehensive metadata documents, and supports a hierarchical organization of the overall data space for data browsing. SciPort takes two alternative "peer"-to-"peer" (or peer-database-to-peer-database) based approaches to integrate scientific data: pure peer-to-peer architecture and central server based peer-to-peer architecture. The later provides a virtual view of all published data from multiple local sites and supports complex queries with XQuery. The system provides a unified framework for adaptable architectures and customizable schemas, and supplies comprehensive tool set to manage and share scientific data. SciPort was first prototyped in Siemens Corporate Research, and now becomes a mature product and has been successfully used in both biomedical research and clinical trials for scientific research communities.

Original languageEnglish
Title of host publication33rd International Conference on Very Large Data Bases, VLDB 2007 - Conference Proceedings
EditorsJohannes Gehrke, Christoph Koch, Minos Garofalakis, Karl Aberer, Carl-Christian Kanne, Erich J. Neuhold, Venkatesh Ganti, Wolfgang Klas, Chee-Yong Chan, Divesh Srivastava, Dana Florescu, Anand Deshpande
Pages1310-1313
Number of pages4
ISBN (Electronic)9781595936493
Publication statusPublished - 2007
Event33rd International Conference on Very Large Data Bases - Wien, Austria
Duration: 23 Sep 200727 Sep 2007

Publication series

Name33rd International Conference on Very Large Data Bases, VLDB 2007 - Conference Proceedings

Conference

Conference33rd International Conference on Very Large Data Bases
CountryAustria
CityWien
Period23.09.200727.09.2007

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