Hi All,
I really like glueviz (in python) for qualitative linked-data browsing of
data. glueviz.org has some nice intro videos as well, explaining the concepts.
I'd love to hear if there are other likeminded solutions to this problem.
_ peter
On 03/15/2017 04:18 PM, Marianne Corvellec wrote:
> Hi Anelda,
>
> Thank you for bringing our attention to qualitative data analysis.
> Unfortunately, I'm not familiar with RQDA.
>
> So far my work with qualitative data has involved factor analysis,
> which has led me to this R package: http://factominer.free.fr/
>
> More generally, it has led me to join the Virtual Assessment Network
> started by Kari Jordan of Data Carpentry. In this context, I have
> started a project (https://github.com/mkcor/assmtrepr) with the
> following objectives:
> - introduce R (tidyverse approach for data analysis, as well as R packaging);
> - introduce assessment methodologies (teaching myself and learning from
> others);
> - and, of course, spark discussions and collaborations.
>
> Sorry I couldn't be more helpful!
>
> Best,
> Marianne
>
> On Wed, Mar 15, 2017 at 6:57 AM, Noam Ross <[email protected]> wrote:
>> We had a tutorial on RQDA at our users group meeting at Davis a couple of
>> years ago. Slides and video:
>> http://www.noamross.net/blog/2015/5/28/johnson-rqda.html
>>
>>
>> On Wed, Mar 15, 2017, 3:28 AM Anelda van der Walt <[email protected]>
>> wrote:
>>> Dear community,
>>>
>>> We are looking for a free alternative to AtlasTI for qualitative data
>>> analysis.
>>>
>>> I've come across RQDA (http://rqda.r-forge.r-project.org/). The benefit of
>>> teaching RQDA to novices, as I see it, is that it gives us an opportunity to
>>> also expose them to R and all the other great things you can do with R (not
>>> only qualitative). Obviously this also aligns nicely with our new
>>> partnership with the Carpentries and the type of workshops we are already
>>> planning.
>>>
>>> I am not familiar with either AtlasTI or RQDA though and was wondering if
>>> anyone might have an opinion about RQDA and whether this might be a sensible
>>> way forward or if there is anything else that might be more suitable?
>>>
>>> I'd appreciate any inputs, pointers to tutorials, etc.
>>>
>>> Thanks as always!
>>>
>>> Kind regards,
>>>
>>> Anelda
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>>
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