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| 001 | 827958 | ||
| 005 | 20210129225945.0 | ||
| 020 | _ | _ | |a 978-3-319-53861-7 |
| 020 | _ | _ | |a 978-3-319-53862-4 (electronic) |
| 024 | 7 | _ | |a 10.1007/978-3-319-53862-4_20 |2 doi |
| 024 | 7 | _ | |a 0302-9743 |2 ISSN |
| 024 | 7 | _ | |a 1611-3349 |2 ISSN |
| 024 | 7 | _ | |a altmetric:21832845 |2 altmetric |
| 037 | _ | _ | |a FZJ-2017-01986 |
| 041 | _ | _ | |a English |
| 082 | _ | _ | |a 004 |
| 100 | 1 | _ | |a Giesler, André |0 P:(DE-Juel1)132116 |b 0 |e Corresponding author |u fzj |
| 111 | 2 | _ | |a JARA-HPC Symposium, Aachen, Germany, 4 Oct 2016 - 5 Oct 2016 |c Aachen |d 2016-10-04 - 2016-10-05 |w Germany |
| 245 | _ | _ | |a UniProv: A flexible Provenance Tracking System for UNICORE |
| 260 | _ | _ | |a Cham |c 2017 |b Springer International Publishing |
| 295 | 1 | 0 | |a High-Performance Scientific Computing / Di Napoli, Edoardo (Editor) ; Cham : Springer International Publishing, 2017, Chapter 20 ; ISSN: 0302-9743=1611-3349 ; ISBN: 978-3-319-53861-7=978-3-319-53862-4 ; doi:10.1007/978-3-319-53862-4 |
| 300 | _ | _ | |a 233-242 |
| 336 | 7 | _ | |a CONFERENCE_PAPER |2 ORCID |
| 336 | 7 | _ | |a Conference Paper |0 33 |2 EndNote |
| 336 | 7 | _ | |a INPROCEEDINGS |2 BibTeX |
| 336 | 7 | _ | |a conferenceObject |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Conference Paper |2 DataCite |
| 336 | 7 | _ | |a Contribution to a conference proceedings |b contrib |m contrib |0 PUB:(DE-HGF)8 |s 1488884027_24242 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a Contribution to a book |0 PUB:(DE-HGF)7 |2 PUB:(DE-HGF) |m contb |
| 490 | 0 | _ | |a Lecture Notes in Computer Science |v 10164 |
| 520 | _ | _ | |a In this paper we present a flexible provenance managment system called UniProv. UniProv is an ongoing development project providing provenance tracking in scientific workflows and data management particularly in the field of neuroscience, thus allowing users to validateand reproduce tasks and results of their experiments. The primary goal is to equip the commonly used Grid middleware UNICORE and its incorporated workflow engine with the provenance capturing mechanism of UniProv. We also explain an approach for using predefined patterns to ensure compatibility with the W3C PROV Data Model and to map the provenance information properly to a neo4j graph database. |
| 536 | _ | _ | |a 512 - Data-Intensive Science and Federated Computing (POF3-512) |0 G:(DE-HGF)POF3-512 |c POF3-512 |f POF III |x 0 |
| 588 | _ | _ | |a Dataset connected to CrossRef Book Series |
| 700 | 1 | _ | |a Czekala, Myriam |0 P:(DE-Juel1)165674 |b 1 |u fzj |
| 700 | 1 | _ | |a Hagemeier, Björn |0 P:(DE-Juel1)132123 |b 2 |u fzj |
| 700 | 1 | _ | |a Grunzke, Richard |0 P:(DE-HGF)0 |b 3 |
| 773 | _ | _ | |a 10.1007/978-3-319-53862-4_20 |
| 909 | C | O | |o oai:juser.fz-juelich.de:827958 |p VDB |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 0 |6 P:(DE-Juel1)132116 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 1 |6 P:(DE-Juel1)165674 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 2 |6 P:(DE-Juel1)132123 |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |1 G:(DE-HGF)POF3-510 |0 G:(DE-HGF)POF3-512 |2 G:(DE-HGF)POF3-500 |v Data-Intensive Science and Federated Computing |x 0 |4 G:(DE-HGF)POF |3 G:(DE-HGF)POF3 |l Supercomputing & Big Data |
| 914 | 1 | _ | |y 2017 |
| 915 | _ | _ | |a Nationallizenz |0 StatID:(DE-HGF)0420 |2 StatID |
| 915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |
| 920 | _ | _ | |l yes |
| 920 | 1 | _ | |0 I:(DE-Juel1)JSC-20090406 |k JSC |l Jülich Supercomputing Center |x 0 |
| 980 | _ | _ | |a contrib |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a contb |
| 980 | _ | _ | |a I:(DE-Juel1)JSC-20090406 |
| 980 | _ | _ | |a UNRESTRICTED |
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