Post-processing T-patterns Using External Tools From a Mixed Method Perspective

摘要

Researchers of behavioral science often work with time-aligned annotation data based on video and/or audio recordings. Various platforms are available to process these data, offering various kinds and ways of data analysis. It often happens that one would wish to use one platform for a certain kind of analysis, and another platform for another kind. It may also happen that one would keep the results of the first analysis and continue processing the data using another platform—all as a chain of analyses on the way to discovery. When it comes to T-pattern analysis, the task of further analyzing already identified patterns across platforms requires a general framework within which virtually any kind of data can be processed in a cross platform environment: that of a database. Data (including patterns) from one platform are then imported into this database, where these patterns are further processed to uncover further properties, then the patterns can be exported to another platform, including the one the data originated from. This contribution aims at introducing a new methodology and a tool implemented as a web-based service for these purposes.