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In this article, we analyze how the processes of sharing, archiving, and citing derived astronomical data is {\it presently} accomplished. Our research is based upon a quantitative link structure analysis and a qualitative study, composed of interviews and a survey. The results of this article are divided in two sections, accordingly.   In the first part of the results, we report on a link analysis performed on all articles published in the Astronomy journals published by the American Astronomical Society between 1997 and 2008. To carry out this analysis, we collaborated with the leaders of the ``Astrophysics Data System," which has functioned for the past 20 years as the world's (first and) only compreshensive astronomical literature service \cite{http://adsabs.harvard.edu/cgi-bin/bib_query?arXiv:0909.4786}. \citet{http://adsabs.harvard.edu/cgi-bin/bib_query?arXiv:0909.4786}.  We explore all these articles for outgoing links. If links are present in an article, are those links pointing to data? Are the links still valid and reachable? We find that 1) astronomers have increasingly used links in papers to provide pointers to derived data, and 2) the availability of these data deteriorates with time (broken links) especially when derived data are hosted on personal websites. In the second part of the results section, we report findings from a personal interview study conducted with a dozen astronomers at the Harvard-Smithsonian Center for Astrophysics and a follow-up survey conducted at the same institution (173 respondents). The Center for Astrophysics is the largest astrophysics instutition in the United States with roughly 1000 employees, 300 of whom are PhD researchers from around the globe. The purpose of this dual qualitative study was to document the data sharing practices of an astronomical community in a semi-structured format. We found that 1) astronomers produce derived data in standard astronomical formats, 2) they are overwhelmingly willing to share their data with their peers and the public, 3) they are normally unaware of mechanisms for archiving and citing derived data, and 4) they rely upon non-automated, non-standard methods to acquire and provide derived data (e.g., they put derived data on their website and link to it, they contact paper authors to obtain data).