Nature has a disheartening article out published this last week on the success of different projects attempting to encourage data sharing among academics.  Unfortunately, my experience has been entirely too in-line with what the authors found that data sharing is an entirely discipline-specific beast.  Within Management, probably the discipline of study most associated with entrepreneurship scholarship (with Economics a close second), data sharing is not common.  In fact, the discipline encourages, for the most part, studies which are based on proprietary data and that can never be replicated or accessed.  It is so incredibly frustrating.  In Economics, I would assess things as slightly better but not by much.  

I have had numerous conversations with people over the years who are interested in changing these discipline specific norms.  Unfortunately, these conversations often don't go very far.  Personally, I think the only hope of creating holistic change needs to start at the discipline level and would need to come from the top down vs. the bottom up.  If a coalition of the top journals in a given discipline were to come together and adopt new rules on data disclosure and sharing that were standard and implemented uniformly, every could change.  As it stands, I have never seen something like that happen.  Within Economics, many of the top journals in theory require data accessibility for publication but the actual implementation of these rules is spotty and hasn't spread to all publications.

With such a downtrodden take on the subject I should highlight a couple of cases that are the exceptions to the rule:

• We have a major innovation survey hitting the field at some point in the spring through Duke and Georgia Tech.  The principals on that project, with a little prodding, have created a user research consortium including some emerging scholars, who will use NORC's Data Enclave tool to allow for a geographically diverse community of scholars to leverage the data collected.  
• Rob Wiltbank and Rob Fairlie have both been very generous in making data they created for different Kauffman projects available.  The Angel Investor Performance Project and the Kauffman Index of Entrepreneurial Activity both allow for micro-data-based research.

I am not including here a discussion of public-use data sets only because such data sets have an added layer of complexity although many of the issues identified here and in the Nature article are also applicable to on public-use data files. 

Are you passionate on this topic or have an idea?  Let me know.