MUMMERING Platform Idea's & ubiquitous data analysis
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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MUMMERING Platform Idea's & ubiquitous data analysis. / Munk, Rasmus; Vinter, Brian.
Communicating Process Architectures 2017 and 2018, WoTUG-39 and WoTUG-40 - Proceedings of CPA 2017 (WoTUG-39) and Proceedings of CPA 2018 (WoTUG-40). red. / Jan Baekgaard Pedersen; Kevin Chalmers; Jan F. Broenink; Brian Vinter; Kevin Vella; Peter H. Welch; Marc L. Smith; Kenneth Skovhede. IMIA and IOS Press, 2019. s. 323-333 (Concurrent Systems Engineering Series, Bind 70).Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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TY - GEN
T1 - MUMMERING Platform Idea's & ubiquitous data analysis
AU - Munk, Rasmus
AU - Vinter, Brian
PY - 2019
Y1 - 2019
N2 - The growth from terabytes of 3D imaging data and soon approaching petabytes from material analysis has left the scientists involved with a set of challenges. In particular, the ability to efficiently analyze an ever growing collection of material tomography scans. The MUMMERING research project aims to solve this by providing ability to submit workflows to automate the process of analyzing the collected data. We explore and present our initial design thoughts in this endeavor. This includes a proposal to utilize the IDMC system developed at UCPH to provide an efficient method in terms of scheduling and execution of workflows. Beyond this mere exploration of thoughts about a potential solution for the MUMMERING project, this paper will also we introduce our initial work in providing ubiquitous access to the produced datasets. The aim here is to provide a simple API for loading/storing datasets during an image analysis, by providing this universal data access library (i,e. mig utils). With this we hope to help the non computer scientists involved in defining imaging analysis programs that easily either can executed locally during the experimentation phase or subsequently scheduled by a workflow scheduler.
AB - The growth from terabytes of 3D imaging data and soon approaching petabytes from material analysis has left the scientists involved with a set of challenges. In particular, the ability to efficiently analyze an ever growing collection of material tomography scans. The MUMMERING research project aims to solve this by providing ability to submit workflows to automate the process of analyzing the collected data. We explore and present our initial design thoughts in this endeavor. This includes a proposal to utilize the IDMC system developed at UCPH to provide an efficient method in terms of scheduling and execution of workflows. Beyond this mere exploration of thoughts about a potential solution for the MUMMERING project, this paper will also we introduce our initial work in providing ubiquitous access to the produced datasets. The aim here is to provide a simple API for loading/storing datasets during an image analysis, by providing this universal data access library (i,e. mig utils). With this we hope to help the non computer scientists involved in defining imaging analysis programs that easily either can executed locally during the experimentation phase or subsequently scheduled by a workflow scheduler.
KW - Data analysis
KW - MUMMERING
KW - Scientific workflows
KW - X-ray imaging
U2 - 10.3233/978-1-61499-949-2-323
DO - 10.3233/978-1-61499-949-2-323
M3 - Article in proceedings
AN - SCOPUS:85082400522
T3 - Concurrent Systems Engineering Series
SP - 323
EP - 333
BT - Communicating Process Architectures 2017 and 2018, WoTUG-39 and WoTUG-40 - Proceedings of CPA 2017 (WoTUG-39) and Proceedings of CPA 2018 (WoTUG-40)
A2 - Pedersen, Jan Baekgaard
A2 - Chalmers, Kevin
A2 - Broenink, Jan F.
A2 - Vinter, Brian
A2 - Vella, Kevin
A2 - Welch, Peter H.
A2 - Smith, Marc L.
A2 - Skovhede, Kenneth
PB - IMIA and IOS Press
T2 - 39th WoTUG Conference on Communicating Process Architectures, CPA 2017 and 40th WoTUG Conference on Communicating Process Architectures, CPA 2018
Y2 - 19 August 2018 through 22 August 2018
ER -
ID: 241090444