qualSchema

qualSchema is a data modeling language designed for describing the structure and relationships of qualitative data. It aims to provide a standardized way to represent and organize unstructured or semi-structured information, often encountered in fields like social sciences, market research, and humanities. The core idea behind qualSchema is to allow researchers to define the types of qualitative data they are collecting, such as interview transcripts, focus group discussions, open-ended survey responses, or observational notes.

The language enables the specification of various data elements, their attributes, and how these elements can be linked together. This might include defining categories, themes, concepts, or entities within the qualitative data. For example, a researcher could define a "participant" entity with attributes like "age" and "gender," and then link it to "interview" data. Similarly, themes identified in the data can be explicitly modeled and related to specific passages or quotes.

qualSchema supports the creation of rich, interconnected qualitative datasets that can be more easily queried, analyzed, and shared. By imposing a schema, it facilitates consistency and comparability across different qualitative research projects. While not as widely adopted as some quantitative data standards, qualSchema represents an effort to bring more structure and rigor to the management and analysis of qualitative information, potentially improving the reproducibility and interpretability of qualitative findings.