Upcoming workshop presentation: ‘XVivo: The case for an open source QDAS’

I will be doing a presentation on the need for qualitative researchers to embrace open source software and my work on Pythia as part of the Urban Studies’ Monday workshops at the University of Glasgow on 26th November.


Qualitative data analysis software (QDAS) has the potential to revolutionise both the scale of qualitative research and the array of possible analysis techniques. Yet currently available software still imposes unnecessary limits that hinder and prevent this full potential from being realised. Additionally, it locks data and the analysis performed on it within proprietary file formats that makes the archiving and sharing of research difficult. Due to similar issues, open source solutions have seen increasing popularity in quantitative research, and it is perhaps time that qualitative researchers joined them. This presentation will therefore discuss both the issues of current proprietary QDAS as well as the potential of open source software for qualitative researchers. To do this, the myriad of issues experienced with NVivo by the Welfare Conditionality project will be used to exemplify the problems created by a reliance on expensive, slow, and poorly designed proprietary software. The second half of the presentation will focus on Pythia, an open source QDAS library written in Python I have been working on. Through covering the design philosophy, current progress, and long-term plans the potential of open source will be highlighted for being able to solve problems with current qualitative software, enable new creative analysis techniques, and allow researchers to reclaim control of their data.

The workshops, as far as I am aware, are open to Urban Studies’ staff and PhD students only. However, as usual I will upload a copy of my presentation slides after the event. Additionally, as part of the preparation for the presentation I will be aiming to write a few short blog posts on the design philosophy of Pythia, elaborate further on why there is a need for an open source QDAS, as well as write-ups and screenshots of progress. Unfortunately, development ground to an absolute halt during the eight months where all my spare time, energy, annual leave, mental health, hopes, dreams, and general will to live were sacrificed at the job hunting altar. I now have around 12 months before that hell begins again, so once I have taken care of the journal article writing backlog that also built up during that time the plan is to filter work on Pythia back into my weekly schedule.

A Qualitative Computing Revolution?

The challenges of data management and analysis on a large longitudinal qualitative research project

Computer aided qualitative data analysis has the potential to revolutionise both the scale of research and possible analysis techniques. Yet, the software itself still imposes limits that hinder and prevent this full potential from being realised. This post looks at the large and complex dataset created as part of the Welfare Conditionality research project, the analytical approach adopted, and the challenges QDAS faces.

The Welfare Conditionality project has two broad research questions in setting out to consider the issues surrounding sanctions, support, and behaviour change. Firstly, is conditionality ‘effective’ – and if so for whom, under what conditions, and by what definition of effective. And, secondly, whether welfare conditionality is ‘ethical’ – how do people justify or criticise its use and for what reasons. To answer these questions, we have undertaken the ambitious task of collecting a trove of qualitative data on conditional forms of welfare. Our work across nine policy areas, each of which has a dedicated ‘policy team’ that is responsible for the research. The policy areas are: unemployed people, Universal Credit claimants, lone parents, disabled people, social tenants, homeless people, individuals/families subject to antisocial behaviour orders or family intervention projects, (ex-)offenders, and migrants. Research has consisted of 45 interviews with policy stakeholders (MPs, civil servants, heads of charities), 27 focus groups with service providers, and three waves of repeat qualitative interviews with 481 welfare service users across 10 interview locations in England and Scotland.

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