With my thesis completed and the defense pending, I can get on with a much-deserved relaxing summer. This means, of course, that I have already begun to tug at the several inviting strands poking out of the tangled ball of string that occupies the cavity behind my eyes where my brain ought to be. 

One of those strands is what I guess I'll call "research management". Even when I started the MA program I knew this: the goal of a research-oriented MA degree is to demonstrate a rough ability to come up with a project and execute it. It's a bit like making it through nursing school or any professional program. You don't get out of a nursing program ready to work with patients. Having a nursing degree just tells employers you're slightly less likely to kill someone under your care than someone off the street. Similarly, for as much as I – and my hard-working peers – do our very best to come up with well-theorized research projects grounded in original and convincing data, the real goal of our theses is to show that we can do social science research without breaking any major laws, causing and personal or public harm, and, if it's not too much bother, even say something novel about the world. Assuming that I make it through the defense (not an assumption I take lightly), I will have the chance to do more research. Isn't that enough?

No, probably not. One of the things that bugged me throughout the MA was the difficult time I had corralling pieces of the project together. Trying to keep track of all the relevant (or possibly relevant) theoretical sources, scraps of qualitative and quantitative data, and optimizing time spent on field research was a bit like herding the proverbial family of very ornery cats. This is natural in any field, not just academic research – just look at the office of any attorney, private practice doctor, or school teacher. However, as I've always been a bit obsessed with organization, I consider it a personal goal to get better at managing the research process and the data generated from research.

How to proceed? A few years ago I read an article by David Allen, creator of the Get Things Done system of task management. (Okay, it's kind-of cheezy pop business lit, but give me a break.) He said one thing that stuck with me: the human mind is terrific at analyzing one thing, but terrible at keeping track of lots of different things. For instance, when I focused on particular problems within my field research, I could generate new ideas, make connections to related issues, and so on. But it was difficult to keep track of all the pieces of information that make up the whole research project, or even just remember the final conclusions from my last intense work session. In the first example, I could focus and think through a specific problem. In the second example, my brain had to keep track of dozens of files and ideas spread across documents, scraps of paper, my field notebook, maps in ArcGIS, and PDF's on both my Mac and Windows partitions. My brain wasn't so good at the second part. 

One thing that helped greatly was Scrivener. Scrivener is a piece of software that lets you keep all your different chapters, sections, and ideas together in one project while you work on smaller pieces at a time. For example, in one project titled "MA Thesis", I had all my conference papers, grant proposals, term papers, and concrete ideas together in one place. This made some parts of writing the thesis much easier. Word is the dominant writing software, though, so I regularly had to export it to Word for comments and edits, and finally to format it for the University. Word is not my friend, and while I did get a final draft out, it was too much hassle for my taste.

Scrivener, however, is writing oriented, not analysis oriented. (Not that I'm making a too narrow distinction between the two.) So when I needed to look at my original data I had it spread across tons of Excel spreadsheets, several versions of ArcGIS projects, exported maps, interview transcripts, and documents I obtained in the field. I should say that I am pretty well-organized, and I could usually get to the data pretty easily. But no matter how clearly and logically folders on my three hard drives were organized, I could never look at all my data in one place. Furthermore, I didn't have metadata that tied all this data together. You can only append Excel files with versions ("Statistical Analysis Spreadsheet v.7") so many times before it becomes completely meaningless. 

So here's the end of that matter. I'm surveying a number of software solutions to these problems. Here's the list of packages I'm exploring to help for the PhD.

Filemaker Pro 11 – I should have used this from the beginning to code documents instead of putting it into an Excel spreadsheet. Excel is great at statistics, but it's lousy at organizing and searching data. I think four times out of five, a database should be used instead of a spreadsheet. It's possible to create a database accessible by other researchers which can serve as a repository of raw data, field contacts, and research activity. There's also a mobile app call Filemaker Go which has some fieldwork possibilities, as well.

Nvivo – There's debate about the value of qualitative analysis software. Clearly the most important thing from a research perspective is to have a clear framework for your research. However, Nvivo appears to be a terrific solution for organizing research. In fact, I much prefer that Nvivo (like Atlas ti and Maxqda) be called "qualitative research organization software" than "qualitative analysis software". It doesn't actually analyze anything for you; you have to do that yourself.

Adobe InDesign – For producing a final draft of a long document, Adobe InDesign is superior. It give you much more control – and more predictable control – over the the layout, text, and graphics. I suppose if you don't have any graphics whatsoever InDesign is a waste. But then again, if you don't have pictures...that's just, well, boring. Apple Pages is actually my favorite because it handles graphics and text so well, but it lacks in some essential areas such as making a list of figures, charts, and chapters (it can only do one at a time, not all three). 

ArcGIS – I already used ArcGIS for some data analysis, but now that I've learned a bit more about databases in general through Filemaker Pro, I'm beginning to see some interesting and unconventional uses of ArcGIS to store and represent data. I need more time with this software.

All three of these (and others that I'm looking into) have a steeper learning curve than typical software. However, I think the payoff will be huge in terms of organizing and using data instead of spending time hunting for it and re-creating it every time I want to put it into a document. (I can't tell you how many times I re-made maps in ArcGIS because the PDF's I exported were just off slightly. I lost a year of my life from stress, I'm sure.) So that's it. I'm having fun exploring these software packages and I'll hopefully have a more professional workflow for my PhD research. 

I want to take the opportunity to offer a broad view of my academic interests. Yes, that sounds tremendously boring. But I haven't done it anywhere else, and if you're a fellow grad student you may actually find this interesting.

Primary Research Interest (How do I spend the majority of my research efforts?)
I am interested in how immigration enforcement functions in non-border spaces. It's that simple and that complicated. It's a broad topic that draws on social and political theory, legal history, and site-specific field research. This is the substance of my MA thesis, and likely the focus of my future PhD dissertation, as well. I will be the most vague here, since it is the topic of ongoing research.

Secondary Research Interests (What other research am I willing to selectively spend time on?)
Geography & Deaf Studies: There are relatively few geographers who have the experience and language proficiency to connect deaf studies and geography. I am fascinated by the potential connections and contributions that have gone unnoticed due to the relatively little research overlap between these two fields. You'll notice that I'm organizing two sessions at the AAG on this topic. I find this a rewarding way to balance my interest in this topic and more pressing demand of the primary research.

Mobility and Cycling: Like the deaf studies, this is an intersection of personal and professional interest. Through my own experience of cycling for transportation, I have become interested in how mobility is invested with political, cultural, and personal meaning. This actually shows up in my research on immigration, but only a piece of the larger puzzle. I also help to keep Bike OSU going. (See http://bikeosu.weebly.com)

Tertiary Interests (These are the threads in my sweater that I just pick at from time to time.)
Project Management in Academia: After interpreting an excellent two-day seminar on project management, I realized that project management skills were just what I had been trying to develop over the past few years of organizing Bike to Work Week and other programs. I have since tried to apply bits and pieces of project management to my own studies in order to get (and stay) on track with my research. I am now kicking around the idea of how project management (P.M.) might contribute to improved research experience and outcomes, and whether P.M. is not an absolutely crucial but heretofore untaught skill for graduate students and career academics. 

Productivity and Performance in Academia: This is related to my first tertiary interest. I hesitate to mention these together, because it may seem like I'm trying to simply import business concepts. Not the case. I'm genuinely interested in how goals are set, measured, and achieved in a variety of settings: personal life, career life, and social life. I take the position that people generally accomplish what they set out to do. And most of the time, we set out to fail in some way – we just don't realize it because we aren't used to thinking clearly or communicating specifically. This brings up tertiary topic 2.1: writing and communication. I want to have an efficient writing process and produce clear writing products. Like P.M. above, I can't help but see writing as a core skill for academics. And like P.M., the writing process is almost completely untaught; it's expected that students will pick it up as they go along. Some of you may think that's fine. But think of where we've come with research methods. No one used to take research methods classes, and now they are seen as core skills (and required courses) for graduate students.

Relevant Pedagogy in Higher Education: Let's face it. If you are going to work at a university, you will have to teach. And unless you're at a liberal arts college, teaching will always be second to research. So, why bother being a good teacher? Primarily because initial investment in being a good teacher means lots of time saved down the road. Hence more time available for research. But it's more than that. Higher education can be anywhere between enlightening and life-changing, to irrelevant and mis-managed. It's just my opinion, but as a social scientist, I'm supposed to know something about how society functions, no? Even better if I can make a contribution to society, developing much-needed perspective in our undergraduate future leaders. What does all that mean, and how do we do that? I don't know. But I'm watching. And taking notes.