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| 001 | 860784 | ||
| 005 | 20230127125335.0 | ||
| 024 | 7 | _ | |a 10.1109/eScience.2018.00051 |2 doi |
| 024 | 7 | _ | |a WOS:000459856400043 |2 WOS |
| 037 | _ | _ | |a FZJ-2019-01447 |
| 100 | 1 | _ | |a Schultz, Martin |0 P:(DE-Juel1)6952 |b 0 |u fzj |
| 111 | 2 | _ | |a 2018 IEEE 14th International Conference on e-Science (e-Science) |c Amsterdam |d 2018-10-29 - 2018-11-01 |w Netherlands |
| 245 | _ | _ | |a A Web Service Architecture for Objective Station Classification Purposes |
| 260 | _ | _ | |c 2018 |b IEEE |
| 300 | _ | _ | |a 283 - 284 |
| 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 1550157979_16807 |2 PUB:(DE-HGF) |
| 520 | _ | _ | |a The Tropospheric Ozone Assessment Report (TOAR) has recently pioneered the use of global Earth Observation data to derive a globally consistent scheme for characterizing the local environment of stations measuring weather and atmospheric composition. Here, we are building on the TOAR concept and expand it to a set of web services, which will allow for a flexible, automated characterization of any point location through standardized REST APIs. These services shall be freely available to the community and thus pave the way for new concepts to analyze global monitoring data and evaluate numerical models. |
| 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 |
| 536 | _ | _ | |0 G:(DE-Juel-1)ESDE |a Earth System Data Exploration (ESDE) |c ESDE |x 1 |
| 588 | _ | _ | |a Dataset connected to CrossRef Conference |
| 700 | 1 | _ | |a Apweiler, Sander |0 P:(DE-Juel1)164455 |b 1 |u fzj |
| 700 | 1 | _ | |a Vogelsang, Jan |0 P:(DE-Juel1)173676 |b 2 |u fzj |
| 700 | 1 | _ | |a Hagemeier, Bjorn |0 P:(DE-Juel1)132123 |b 3 |u fzj |
| 700 | 1 | _ | |a Kleinert, Felix |0 P:(DE-Juel1)176602 |b 4 |u fzj |
| 700 | 1 | _ | |a Mallmann, Daniel |0 P:(DE-Juel1)132181 |b 5 |u fzj |
| 773 | _ | _ | |a 10.1109/eScience.2018.00051 |
| 856 | 4 | _ | |u https://juser.fz-juelich.de/record/860784/files/08588670.pdf |y Restricted |
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| 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 2019 |
| 920 | 1 | _ | |0 I:(DE-Juel1)JSC-20090406 |k JSC |l Jülich Supercomputing Center |x 0 |
| 980 | _ | _ | |a contrib |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a I:(DE-Juel1)JSC-20090406 |
| 980 | _ | _ | |a UNRESTRICTED |
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