@article{
 title = {Special issue for data intensive eScience},
 type = {article},
 year = {2012},
 pages = {303-306},
 volume = {30},
 websites = {http://link.springer.com/10.1007/s10619-012-7107-1},
 month = {10},
 publisher = {Springer},
 day = {25},
 id = {47d46aad-337b-302a-8fc8-043ced14dac8},
 created = {2018-01-23T20:26:56.663Z},
 file_attached = {false},
 profile_id = {42d295c0-0737-38d6-8b43-508cab6ea85d},
 last_modified = {2020-05-11T14:43:39.385Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Qiu2012},
 source_type = {GEN},
 folder_uuids = {36d8ccf4-7085-47fa-8ab9-897283d082c5,023ec473-8727-4d72-856c-6687cf1caa00},
 private_publication = {false},
 abstract = {The Special Issue of Distributed Parallel Databases journal, 2012, discusses novel data processing techniques for this new data-driven world. This data intensive eScience special issue encouraged researchers to submit and present original work related to the latest trends in preservation, movement, access and analysis of massive datasets that require new tools to support all aspects of data-intensive investigation in science. Atkinson and colleagues present an architecture for data intensive science applications with three important components: a canonical language (DISPEL), a registry and an enactment platform. Bui and researchers describe the design and implementation of ROARS, a robust object archival system for storing scientific data with the write-once-read-many access mode. Gadelha presents MTCProv, a provenance management system for manytask scientific computing that focuses on workflow-level provenance architecture and the details of a new query language SPQL and its use on details of execution metadata.},
 bibtype = {article},
 author = {Qiu, Judy and Gannon, Dennis},
 doi = {10.1007/s10619-012-7107-1},
 journal = {Distributed and Parallel Databases},
 number = {5-6}
}

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