Data Provenance and Data Management in eScience

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Liu, Qing (Επιμελητής έκδοσης), Bai, Quan (Επιμελητής έκδοσης), Giugni, Stephen (Επιμελητής έκδοσης), Williamson, Darrell (Επιμελητής έκδοσης), Taylor, John (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
• Σειρά: Studies in Computational Intelligence, 426
• Θέματα: Engineering.; Artificial intelligence.; Engineering, general.; Artificial Intelligence (incl. Robotics).

eScience allows scientific research to be carried out in highly distributed environments. The complex nature of the interactions in an eScience infrastructure, which often involves a range of instruments, data, models, applications, people and computational facilities, suggests there is a need for d...

Πίνακας περιεχομένων:

• Provenance Model for Randomized Controlled Trials
• Evaluating Workflow Trust Using Hidden Markov Modeling and Provenance Data
• Unmanaged Workflows: Their Provenance and Use
• Sketching Distributed Data Provenance
• A Mobile Cloud with Trusted Data Provenance Services for Bioinformatics Research
• Data Provenance and Management in Radio Astronomy: A Stream Computing Approach
• Using Provenance to Support Good Laboratory Practice in Grid Environments.