TY - GEN
T1 - Experiment management with metadata-based integration for collaborative scientific research
AU - Wang, Fusheng
AU - Liu, Peiya
AU - Azar, Fred
AU - Pearson, John
AU - Madlmayr, Gerald
PY - 2006
Y1 - 2006
N2 - Scientific research in many fields is increasingly a collaborative effort across multiple institutions and disciplines. Scientific researchers need not only an effective system to manage their data, results, and the experiments that generate the results, but also a platform to integrate, share and search these across multiple institutions. Therefore, researchers are able to reuse experiments, pool expertise and validate approaches. In this paper, we present Sci-Port, a system of experiment management and integration for collaborative scientific research. SciPort's architecture uses i) a general transformation-based data model to represent and link experiment processes; ii) hierarchical data classification across multiple institutions according to research programs' goals and organization; iii) metadatacentric representation that concisely captures the context of experiments; and iv) virtual data integration through centralized metadata integration. The system is built for open source, and the metadata-based representation and integration provides a unified framework and tool set to manage and share experiments for scientific research communities.
AB - Scientific research in many fields is increasingly a collaborative effort across multiple institutions and disciplines. Scientific researchers need not only an effective system to manage their data, results, and the experiments that generate the results, but also a platform to integrate, share and search these across multiple institutions. Therefore, researchers are able to reuse experiments, pool expertise and validate approaches. In this paper, we present Sci-Port, a system of experiment management and integration for collaborative scientific research. SciPort's architecture uses i) a general transformation-based data model to represent and link experiment processes; ii) hierarchical data classification across multiple institutions according to research programs' goals and organization; iii) metadatacentric representation that concisely captures the context of experiments; and iv) virtual data integration through centralized metadata integration. The system is built for open source, and the metadata-based representation and integration provides a unified framework and tool set to manage and share experiments for scientific research communities.
UR - https://www.scopus.com/pages/publications/33749596536
U2 - 10.1109/ICDE.2006.65
DO - 10.1109/ICDE.2006.65
M3 - Conference contribution
SN - 0769525709
SN - 9780769525709
T3 - Proceedings - International Conference on Data Engineering
SP - 96
BT - Proceedings of the 22nd International Conference on Data Engineering, ICDE '06
T2 - 22nd International Conference on Data Engineering, ICDE '06
Y2 - 3 April 2006 through 7 April 2006
ER -