The emerging field of AstroInformatics, while on the one hand appears crucial to face the technological challenges, on the other is opening new exciting perspectives for new astronomical discoveries through the implementation of advanced data mining procedures. The complexity of astronomical data and the variety of scientific problems, however, call for innovative algorithms and methods as well as for an extreme usage of ICT technologies. The DAME (DAta Mining & Exploration) Program exposes a series of web-based services to perform scientific investigation on astronomical massive data sets. The engineering design and requirements, driving its development since the beginning of the project, are projected towards a new paradigm of Web based resources, which reflect the final goal to become a prototype of an efficient data mining framework in the data-centric era. © 2012 SPIE.
Data mining and knowledge discovery resources for astronomy in the web 2.0 age / Cavuoti, S.; Brescia, M.; Longo, G.. - 8451:(2012). (Intervento presentato al convegno Software and Cyberinfrastructure for Astronomy II tenutosi a Amsterdam; Netherlands nel 1 July 2012 through 4 July 2012) [10.1117/12.925321].
Data mining and knowledge discovery resources for astronomy in the web 2.0 age
Cavuoti, S.;Brescia, M.;Longo, G.
2012
Abstract
The emerging field of AstroInformatics, while on the one hand appears crucial to face the technological challenges, on the other is opening new exciting perspectives for new astronomical discoveries through the implementation of advanced data mining procedures. The complexity of astronomical data and the variety of scientific problems, however, call for innovative algorithms and methods as well as for an extreme usage of ICT technologies. The DAME (DAta Mining & Exploration) Program exposes a series of web-based services to perform scientific investigation on astronomical massive data sets. The engineering design and requirements, driving its development since the beginning of the project, are projected towards a new paradigm of Web based resources, which reflect the final goal to become a prototype of an efficient data mining framework in the data-centric era. © 2012 SPIE.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.