Software for Qualitative Data Analysis

I am on a half day course on software for Qualitative Data Analysis (QDA) to supervise research. Recommended as an overview of what software is available is the CAQDAS project at University of Surrey. It is decades since I worked with statistical analysis software (actually SAS) and then it was very quantitative (numbers). The workshop is concentrating on NVivo from QSR International. This could be useful for my studies in education and how to supervise research on-line. Rival produces are MAXQDA.

Of particular interest to me is Transana, a low cost product for analysis of video and audio:

Transana lets the user analyze and manage your data, transcribe it, identify analytically interesting clips, assign keywords to clips, arrange and rearrange clips, create complex collections of interrelated clips, explore relationships between applied keywords, and share your analysis with colleagues. The goal is to find a new way to focus on the data, and manage large collections of video and audio files and clips. ...

From: Transana,Wikipedia, 2012.

An interesting point was that whatever the software used, the researcher still needs to know what the software is doing and be able to show that what comes out is consistent with the data put in. At a technical level NVivo is developed using the Rational Unified Process (RUP).

It occurred to me that as QDA is mostly about labeling items and finding relationships between then]m, this might be used for the analysis and making of student assignments. This could not only look a what is in the assignments of one student but relationships between them and other works. This could look at how students have done group work (or if they have been plagiarizing).

The workshop got on to some often overlooked practical and ethical issues. Research data may contain information about people which needs to be protected. The software may contain encryption to help with this. Before storing the data in "The Cloud" work out where it is actually stored and if this is sufficiently secure (ANU is building its own ANU Cloud Storage). Removable storage devices can be a problem, particularly flash drives, which are easily lost (can be secured with a lanyard).

One point is that using software can assist with supervision. The supervisor can look at what the student has been doing and when they did it.

Editing Educational Video

Greetings from the video editing labs at the Australian National University, where Dr Judy-anne Osborn, Visiting Fellow, Centre for Mathematics and Its Applications, Mathematical Sciences Institute, is editing her educational mathematics video.

One of the first issues which came up is the very large size of the video files. This makes it difficult to copy them from computer to computer so that several people can work on the project at the same time. Another issue is which software to use. Simple applications like Apple iMovie may not have fine enough details.

Statistics and Mathematics Movie Making Information Session

A Statistics and Mathematics Movie Making Information Session will be held 1pm to 2pm, 23 February 2011, in room PM1012 of the PAP Moran Building, Austrlaian National Unviersity, Centre for Mathematics and Its Applications. The session is free and anyone interested in making educational videos for maths and stats is welcome to attend.

ANU-based award winning film-maker Bobby Cerini, as well as Statisticians, Mathematicians and students from the Mathematical Sciences Institute at ANU and elsewhere will be speaking. Everyone attending will be welcome to contribute ideas. Snacks and drinks will be provided.

Directions: To get to PM1012, enter the John Dedman Maths Building 27 near reception, go up one flight of stairs, across the glass walkway into the PAP Moran Building, walk along the corridor to where it turns left, turn left with the corridor and room PM1012 is the first door on the right.

More dtails are avialable from Dr Judy-anne Osborn, Visiting Fellow, Centre for Mathematics and Its Applications, Mathematical Sciences Institute, Australian National University.

RESTful Statistical Service Powered by R

Greetings from the SyPy: Sydney Python Users group meeting at Google Sydney. Richard Volpato is talking on "Making R restfully enterprising with Django". Richard works for the Copyright Agency Limited, which has a lot of statistical data to process and is important to Australia's authors. He created a RESTful 'statistical service' powered by the statistical language R. Richard pointed out that the open source R language could be used in a similar way to statistical packages SPSS and SAS. This could be more significant to the Austrlaian publishing industry than the government's Book Industry Strategy Group (BISG) inquiry.

To prevent the large statistical analyses overloading the server, they are queued (reminding me of old fashioned batch processing). The queuing is done using RabbitMQ. Then RESTful is used to interface to the clients (simpler than SOAP). The Django web framework was used with Python to tie all the components together.

I had difficulty understanding the technical details of Richard's explanation of how the system works, as not I am a Python user (I felt he was giving the equivalent of five conference talks at once). This reminded me a little of LaTex for typesetting, but applied to statistics.

However, the issue of having to carry out complex and very precise calculations on large amounts of data which effects large payments is familiar to me from work at the Commonwealth Schools Commission to calculate billions of dollars in payments to schools.

What was exciting was Richard's broad vision of how such systems could be used for corporate and public benefit. He mentioned Google's Content Identification and Management System which allows rights owners to "Choose, in advance, what they want to happen when those videos are found. Make money from them. Get stats on them. Or block them from YouTube altogether...".

One interesting comment was about how important the payments from the Copyright Agency were to Australian authors.

Richard then talked about how a Kanban Board is used for the software development.

Richard will be at John Maindonald's Statistical Learning and Data Mining using R course at ANU in Canberra 17 to 21 January 2011.