Annual Meeting 2019 of the Astronomische Gesellschaft, Stuttgart, Germany
The importance of publicly available and accessible astronomical data sets for the feasibility and effectiveness of research in astronomy and astrophysics has been shown many times in the past years. From last year, perhaps the most spectacular example is the flood of results employing data release 2 of Gaia, facilitated at least in part by a well-designed, Virtual Observatory-based data dissemination and query infrastructure.
New instruments coming online in the next few years, from Euclid to SKA to LSST, will still require significant evolution as well as development of new methods to enable similar science success stories.
This is not merely a question of publication techniques. It also involves application machine learning, computational statistics or neural networks. Software development for astronomical machinery, for instrument data pipelines, and analysis of data still call for new approaches.
We invite you to share your experiences and ideas, learn from successful applications, and discuss problems, obstacles and challenges of publishing and exploiting both large and diverse data in our science.
We specially call for contributions to a session:
Demonstrate your favorite software / tool for doing astronomy!
Tuesday, 17.09.2019, 14:00 - 16:50 , Room (9.11)
Wednesday, 18.09.2019, 14:00 - 17:00 (9.11)
H. Enke, K. Polsterer, J.K. Wambsganss
Tuesday,17.09.2019
Virtual Observatory and Infrastructure, 14:00 -14:50
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O. Streicher (AIP) | The IVOA Provenance standard for astrophysical data |
V. Brinnel (DESY) | Transient alert processing and analysis using AMPEL (Alert Management, Photometry and Evaluation of Lightcurves) |
Break | |
The NFDI (Nationale Forschungsdaten Infrastruktur) and Astrophysics Participation :15:00-16:50
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Harry Enke (AIP) | Intro : The NFDI Landscape |
Michael Kramer (MPIfR) | Astro-NFDI |
Joachim Wambsganss (ZAH) | RFII (Rat für Informationsinfrastruktur) perspective |
Ralf-Jürgen Dettmar (RUB) | NFDI Expert Committee |
Wednesday, 18.09.2019
Machine learning 14:00 -15:30
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Kai Polsterer (HITS) | From Photometric Redshift to Improved Weather Forecasts |
Erica Hopkins (HITS) | Can crowdsourcing be replaced by GPUs? |
G. Guiglion (AIP), Gal Matijevic | Galactic Archeology with RAVE and APOGEE using Convolutional Neural Networks |
Gal Matijevic (AIP) | Artifact detection on photographic plates with convolutional neural networks |
Break | |
Virtual Observatory and Infrastructure, 16:00 - 17:30
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Christian Dersch (U. Marburg) | Applausequery - a PyVO application for highlevel access to astronomical photoplate database |
Markus Demleitner (ZAH) | Reducing Bottlenecks in TAP Cross-Server Queries |
Antonio D’Isanto (HITS) | ESCAPE: building the infrastructure for the next generation astronomy |
If you have any further questions, please don't hesitate to contact us
Harry Enke: henke [at] aip [dot] de
Kai Polsterer: kai.polsterer [at] h-its [dot] org
Joachim Wambsganss: jkw [at] ari [dot] uni-heidelberg [dot] de