Chair: Herbert Kroehl
The virtual observatory (VO) paradigm has been gaining visibility in communities beyond Astronomy and distributed data systems ( DDS ) have been around for at least 15 years. These efforts are producing numerous successes, lessons learned, new concepts, new designs, and copious experience with changing technologies. Science communities (especially Geosciences) and agencies stand ready to utilize fully these concepts in meeting the challenging explosion of data from instruments and models in the present and next decade.
Motivated by the eGY, which is promoting the use of VO concepts/paradigms or data-intensive activities in the 2007-2008 timeframe, this session will feature 3 invited presentations that represent diverse earth and space science applications of virtual observatory concepts. The session will also feature a panel discussion on virtual observatories that will allow the audience at all levels (science and education users, designers/architects, developers, and data providers) to contribute their experiences.
The oral presentations and the discussion panel are intended to address the following questions: What have we learned in developing and deploying distributed data systems and virtual observatories? How can proper attribution of sources of data be made and tracked in a data-world that is increasingly 'virtual'? Can we clarify the role semantics (ontologies, knowledge representation) may play in developing search and access systems? How will these capabilities change the way our communities develop interdisciplinary and diverse science applications? Are VOs (or an analog paradigm in fields where 'observatories' are not the usual construct) changing or ready to change the way our communities perform science on ever increasing amounts and diversity of data? How can educators make use of VOs and DDSs that were designed for experts to use? How will knowledge representation technology help educators?
Finally, Are VOs ready to significantly aid scientists in integrating science data from diverse and heterogeneous sources, extract useful knowledge from vast virtual data repositories? and What are the best practices emerging from VO efforts?