I am back on track to get some writing done. Here is the first of a few papers I hope to get up as working papers in the coming weeks. This one deals with the propensity of school districts to consult with emergency management professionals.
Monday, January 10, 2011
Tuesday, January 4, 2011
It's been awhile - but I am back and will start with a tool recommendation
I have neglected my blog in large part due to my recent focus on some collaborative work. In my "quiet" period I have completed a couple of co-authored pieces that I was not comfortable posting on my personal blog (I will clear it with co-authors in the future), had a methods textbook proposal accepted, completed a textbook chapter for a homeland security textbook, and completed three NSF proposals -- one of which was apparently so bad it was rejected twice in one review cycle :).
I am back to writing some single authored pieces and will be posting working papers soon. Hopefully I will be able to better balance original research writing (for the blog) with my textbook writing and a couple of upcoming grant proposals.
In the mean time, I have a great tool to recommend. Google-Refine. I am working on a project for the local Ag extension office that includes 72000 referrals of case management clients to various organizations for services following Hurricane Ike. The data are fascinating. The dataset consists of referral level data that includes which specific clients were referred to which specific agencies by which specific case manager. The networking data potential is astounding. However, the data are PROFOUNDLY DIRTY. Google-refine is a great tool to help clean large datasets like this. Anyone interested in tools to facilitate cleaning datasets should give it a look.
The tool also helped me aggregate the data for quick analysis. In my case, I aggregated up from the referral-level data to case manager level data to compare referral strategies across case managers from different organizations. Given the nature of the data, this was not possible using STATA's "collapse" command or any other tool I could find. Google-refine's faceting tools made it simple. I recommend giving it a look.
Keep checking in. I expect to have an actual research working paper up within a week or so.
I am back to writing some single authored pieces and will be posting working papers soon. Hopefully I will be able to better balance original research writing (for the blog) with my textbook writing and a couple of upcoming grant proposals.
In the mean time, I have a great tool to recommend. Google-Refine. I am working on a project for the local Ag extension office that includes 72000 referrals of case management clients to various organizations for services following Hurricane Ike. The data are fascinating. The dataset consists of referral level data that includes which specific clients were referred to which specific agencies by which specific case manager. The networking data potential is astounding. However, the data are PROFOUNDLY DIRTY. Google-refine is a great tool to help clean large datasets like this. Anyone interested in tools to facilitate cleaning datasets should give it a look.
The tool also helped me aggregate the data for quick analysis. In my case, I aggregated up from the referral-level data to case manager level data to compare referral strategies across case managers from different organizations. Given the nature of the data, this was not possible using STATA's "collapse" command or any other tool I could find. Google-refine's faceting tools made it simple. I recommend giving it a look.
Keep checking in. I expect to have an actual research working paper up within a week or so.
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