%0 Conference Paper %1 Simmhan:gbpse:2006 %A Simmhan, Yogesh %A Pallickara, Sangmi %A Vijayakumar, Nithya %A Plale, Beth %B Grid-Based Problem Solving Environments %D 2007 %E Gaffney, Patrick %E Pool, James %I Springer Boston %K LEAD, calder, data escience, iu, karma, management, mylead, peer portal, provenance, reviewed %P 317--333 %R 10.1007/978-0-387-73659-4_17 %T Data Management in Dynamic Environment-driven Computational Science %V 239 %X Advances in numerical modeling, computational hardware and problem solving environments have driven the growth of computational science over the past decades. Science gateways, based on service oriented architectures and scientific workflows, provide yet another step in democratizing access to advanced numerical and scientific tools, computational resource and massive data storage, and fostering collaborations. Dynamic, data-driven applications, such as those found in weather forecasting, present interesting challenges to Science Gateways, which are being addressed as part of the LEAD Cyberinfrastructure project. In this article, we discuss three important data related problems faced by such adaptive data-driven environments: managing a user’s personal workspace and metadata on the Grid, tracking the provenance of scientific workflows and data products, and continuous data mining over observational weather data.

@inproceedings{Simmhan:gbpse:2006, abstract = {Advances in numerical modeling, computational hardware and problem solving environments have driven the growth of computational science over the past decades. Science gateways, based on service oriented architectures and scientific workflows, provide yet another step in democratizing access to advanced numerical and scientific tools, computational resource and massive data storage, and fostering collaborations. Dynamic, data-driven applications, such as those found in weather forecasting, present interesting challenges to Science Gateways, which are being addressed as part of the LEAD Cyberinfrastructure project. In this article, we discuss three important data related problems faced by such adaptive data-driven environments: managing a user’s personal workspace and metadata on the Grid, tracking the provenance of scientific workflows and data products, and continuous data mining over observational weather data.}, added-at = {2023-04-07T07:37:58.000+0200}, author = {Simmhan, Yogesh and Pallickara, Sangmi and Vijayakumar, Nithya and Plale, Beth}, biburl = {https://www.bibsonomy.org/bibtex/254ce8e266a580c0c3a1a8c40bfd94ed5/vinayaka2000}, booktitle = {Grid-Based Problem Solving Environments}, doi = {10.1007/978-0-387-73659-4_17}, editor = {Gaffney, Patrick and Pool, James}, interhash = {2ae149d872a90ae297dd5021052f952a}, intrahash = {54ce8e266a580c0c3a1a8c40bfd94ed5}, keywords = {LEAD, calder, data escience, iu, karma, management, mylead, peer portal, provenance, reviewed}, owner = {Simmhan}, pages = {317--333}, publisher = {Springer Boston}, series = {IFIP Advances in Information and Communication Technology}, timestamp = {2023-04-07T07:37:58.000+0200}, title = {Data Management in Dynamic Environment-driven Computational Science}, volume = 239, year = 2007 }