The research of ancient written artefacts results in an ever-increasing amount of digital data in different forms, ranging from raw images of artefacts to automatically generated data from advanced acquisition techniques. The manual analysis of this data is typically time consuming and can be subject to human error and bias. Therefore, a set of Pattern Analysis Software Tools (PAST) has been developed for the automatic analysis of visual and tabular patterns in the research data from the study of ancient written artefacts. These software tools have been developed by Hussein Mohammed to facilitate a more efficient study of written artefacts and to help scholars benefit from the rapid advancements in the fields of pattern analysis and artificial intelligence. Furthermore, these tools can provide new insights which can only be derived from the statistical analysis of research data. Each tool in PAST is developed and tested in close collaboration with experts from relevant fields of research in order to ensure its usability and applicability to actual research questions.
Vega-Lite - a high-level grammar for statistical graphics. Vega-Lite provides a higher-level grammar for visual analysis, comparable to ggplot or Tableau, that generates complete Vega specifications. Vega-Lite specifications consist of simple mappings of variables in a data set to visual encoding channels such as x, y, color, and size. These mappings are then translated into detailed visualization specifications in the form of Vega specification language. Vega-Lite produces default values for visualization components (e.g., scales, axes, and legends) in the output Vega specification using a rule-based approach, but users can explicit specify these properties to override default values.