Aim:
The workshop aims at gathering both the scientific and the technology communities for two main purposes: on the one hand, to rediscover and develop the amount/asset of astrophysics data from facilities managed or contributed by INAF and, on the other hand, to better focus on concepts and challenges related to new generation data archives.
The astronomical archives of INAF and their contents, accessibility, maintenance and preservation of data, future prospects of development, as well as the interactions with historical partners of INAF (such as ASI, SSCD and other) are some of the topics that will be addressed in the first part of the workshop. Particular attention will be paid to any proposals aiming at optimizing the availability and accessibility of data archives already present within INAF.
Ample space will be given to the ongoing shift in prospect to keep up with the scientific projects’ needs of the Big Data era, and with those of the most modern observing and computational facilities.
Experiences, tools and applications traditionally belonging to international archives such as those at ESO, CADC, CDS etc. will be presented by world-known experts of information technologies for astrophysics. In such archives astronomers no longer experience the traditional approach to scientific data. Instead, they benefit from a new archiving facility concept where the scientific contents of data are comprehensively explored through the definition of user space and computation resources, the availability of applications for data exploration and analysis as well as collaborative tools for resource sharing, up to the definition of DOI codes associated to the scientific datum.
Ample ground for discussion will be granted through dedicated sessions to the definition of the astrophysical community needs in terms of availability, simplicity and opportunities of use of INAF data archives within the international astrophysical community, as well as in terms of computation and storage support, and of the exploration and optimal extraction of the scientific content of data.
