Knowledge Discovery in Big Data from Astronomy and Earth Observation: Astrogeoinformatics bridges the gap between astronomy and geoscience in the context of applications, techniques and key principles of big data. Machine learning and parallel computing are increasingly becoming cross-disciplinary as the phenomena of Big Data is becoming common place. This book provides insight into the common workflows and data science tools used for big data in astronomy and geoscience. After establishing similarity in data gathering, pre-processing and handling, the data science aspects are illustrated in the context of both fields. Software, hardware and algorithms of big data are addressed.
Finally, the book offers insight into the emerging science which combines data and expertise from both fields in studying the effect of cosmos on the earth and its inhabitants.
Part I: Data 1. Methodologies for Knowledge Discovery Processes in Context of AstroGeoInformatics Peter Butka, Peter Bednár, Juliana Ivancáková 2. Historical Background of Big Data in Astro and Geo Context Christian Muller Part II: Information 3. AstroGeoInformatics: From Data Acquisition to Further Application Bianca Schoen-Phelan 4. Synergy in Astronomy and Geosciences Mikhail Minin, Angelo Pio Rossi 5. Surveys, Catalogues, Databases, and Archives of Astronomical Data Irina Vavilova, Ludmila Pakuliak, Iurii Babyk, Andrii Elyiv, Daria Dobrycheva, Olga Melnyk 6. Surveys, Catalogues, Databases/Archives, and State-of-the-Art Methods for Geoscience Data Processing Lachezar Filchev, Lyubka Pashova, Vasil Kolev, Stuart Frye 7. High-Performance Techniques for Big Data Processing Philipp Neumann, Julian Kunkel 8. Query Processing and Access Methods for Big Astro and Geo Databases Karine Zeitouni, Mariem Brahem, Laurent Yeh, Atanas Hristov 9. Real-Time Stream Processing in Astronomy Veljko Vujcic, Darko Jevremovic Part III: Knowledge 10. Time Series Ashish Mahabal 11. Advanced Time Series Analysis of Generally Irregularly Spaced Signals: Beyond the Oversimplified Methods Ivan L. Andronov 12. Learning in Big Data: Introduction to Machine Learning Khadija El Bouchefry, Rafael S. de Souza 13. Deep Learning – an Opportunity and a Challenge for Geo- and Astrophysics Christian Reimers, Christian Requena-Mesa 14. Astro- and Geoinformatics – Visually Guided Classification of Time Series Data Roman Kern, Tarek Al-Ubaidi, Vedran Sabol, Sarah Krebs, Maxim Khodachenko, Manuel Scherf 15. When Evolutionary Computing Meets Astro- and Geoinformatics Zaineb Chelly Dagdia, Miroslav Mirchev Part IV: Wisdom 16. Multiwavelength Extragalactic Surveys: Examples of Data Mining Irina Vavilova, Daria Dobrycheva, Maksym Vasylenko, Andrii Elyiv, Olga Melnyk 17. Applications of Big Data in Astronomy and Geosciences: Algorithms for Photographic Images Processing and Error Elimination Ludmila Pakuliak, Vitaly Andruk 18. Big Astronomical Datasets and Discovery of New Celestial Bodies in the Solar System in Automated Mode by the CoLiTec Software Sergii Khlamov, Vadym Savanevych 19. Big Data for the Magnetic Field Variations in Solar-Terrestrial Physics and Their Wavelet Analysis Bozhidar Srebrov, Ognyan Kounchev, Georgi Simeonov 20. International Database of Neutron Monitor Measurements: Development and Applications D. Sapundjiev, T. Verhulst, S. Stankov 21. Monitoring the Earth Ionosphere by Listening to GPS Satellites Liubov Yankiv-Vitkovska, Stepan Savchuk 22. Exploitation of Big Real-Time GNSS Databases for Weather Prediction Nataliya Kablak, Stepan Savchuk 23. Application of Databases Collected in Ionospheric Observations by VLF/LF Radio Signals Aleksandra Nina 24. Influence on Life Applications of a Federated Astro-Geo Database Christian Muller
Petr Škoda has been involved in astroinformatics and has a long-term experience in using and lecturing the astronomical Virtual observatory. One of the proposers of COST BigSkyEarth Action and its MC member. BigSkyEarth is the working group behind the idea of the book and a conference about the same topic. Fathalrahman Adam has good understanding of classical machine learning and new concepts, along with hands-on experience and published papers. He is involved in large scale applications using satellite data for earth observation, mainly multi-spectral data. He is a member of BigSkyEarth COST Action.
