Looking back and looking forward to qualitative analysis in 2017

  In the month named for Janus, it’s a good time to look back at the last year for Quirkos and qualitative analysis software and look forward to new developments for 2017.   It’s been a good year of growth for Quirkos, we now can boast of users in more than 100 universities across the world. But we can see how many more people are using Quirkos in these institutions as the word grows. There is no greater complement than

How Quirkos can change the way you look at your qualitative data

We always get a lot of inquiries in December from departments and projects who are thinking of spending some left-over money at the end of the financial year on a few Quirkos licences. A great early Christmas present for yourself the team! It’s also a good long term investment, since our licences don’t expire and can be used year after year. They are transferable to new computers, and we’ve committed to provide free updates

Snapshot data and longitudinal qualitative studies

In the last blog post, we looked at creating archives of qualitative data that can be used by other researchers (or yourself in the future) for secondary analysis. In that article I postulated that secondary data analysis could make collecting new data a rarer, and expensive event. However, some (including Dr Susanne Friese) pointed out that as the social world is always changing, there is a constant need to collect new data. I totally agree

Archiving qualitative data: will secondary analysis become the norm?

  Last month, Quirkos was invited to a one day workshop in New York on archiving qualitative data. The event was hosted by Syracuse University, and you can read a short summary of the event here. This links neatly into the KWALON led initiative to create a common standard for interchange of coded data between qualitative software packages. The eventual aim is to develop a standardised file format for qualitative data, which not only

Stepping back from coding software and reading qualitative data

There is a lot of concern that qualitative analysis software distances people from their data. Some say that it encourages reductive behaviour, prevents deep reading of the data, and leads to a very quantified type of qualitative analysis (eg Savin-Baden and Major 2013).   I generally don’t agree with these statements, and other qualitative bloggers such as Christina Silver and Kristi Jackson have written responses to critics of