Presubmission inquiry for cardsort #101
Description
Submitting Author: Name (@katoss)
Package Name: cardsort
One-Line Description of Package: A python package to analyse data from open card sorting tasks
Repository Link (if existing): https://github.com/katoss/cardsort
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Description
- Include a brief paragraph describing what your package does:
Card sorting is a standard research method in the human computer interaction field to design information architectures. The cardsort package analyzes and visualizes data from open card sorting tasks. Using csv data in the format returned by the kardsort tool (or any other tool outputting the same columns), it outputs a dendrogram based on hierarchical cluster analysis and pairwise similarity scores. It can also return category labels to learn which labels study participants gave to combinations of cards from emerging clusters.
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Scope
- Please indicate which category or categories this package falls under:
Scope
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Please indicate which category or categories.
Check out our package scope page to learn more about our
scope. (If you are unsure of which category you fit, we suggest you make a pre-submission inquiry):- Data retrieval
- Data extraction
- Data processing/munging
- Data deposition
- Data validation and testing
- Data visualization
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- Citation management and bibliometrics
- Scientific software wrappers
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Domain Specific & Community Partnerships
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Explain how and why the package falls under these categories (briefly, 1-2 sentences). Please note any areas you are unsure of:
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Who is the target audience and what are the scientific applications of this package?
The target audience are researchers or practitioners in human computer interaction and user experience. Open card sorting is a popular user research method used to understand how people order and conceptualize information, in order to design information architectures. In order to make sense of the data, clusters are often visualized in form of a dendrogram. To do so, pairwise similarity scores need to be calculated for all cards, followed by a hierarchical cluster analysis. This functionality is provided by the cardsort package. It also offers functionality to return category labels, in order to learn which labels study participants gave to combinations of cards in the emerging clusters.
- Are there other Python packages that accomplish similar things? If so, how does yours differ?
I did not find any python packages, nor other open source tools, that accomplish this, which was my motivation to make this package, when I was running a card sorting study in the course of my PhD. While research articles describe the steps of this analysis (i.e. pairwise similarity scores --> hierarchical cluster analysis --> dendrogram, see articles linked in question above), I did not find any open source tools that help to do this analysis. I used the widely used kardsort.com tool to collect the data, which refers to rather dated, closed source Windows software for analysis, which underpins my assumption of a lack of open source tools. The approach is rather simple, making use of scipy for hierarchical cluster analysis and dendrogram, adding a custom function to create the similarity scores, and putting everything in an easy-to-use pipeline. Nevertheless, in doing so, I think the cardsort package can help remove barriers for the application of this user research method (easy to use even for python beginners, no need to use closed source software that only runs on windows or expensive subscription tools). In any case I would have liked to have this package when I started my study :)
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