HUMAN: Hierarchical Universal Modular ANnotator
This tool addresses the need for flexible and modular annotation workflows for researchers, but it is incremental as it builds on existing annotation tool concepts.
The paper tackles the problem of complex real-world phenomena requiring multiple interdependent annotation tasks and specialized tools, by introducing HUMAN, a web-based annotation tool that supports various tasks on text and image data and allows chaining tasks via a deterministic state machine, with an easy-to-use GUI.
A lot of real-world phenomena are complex and cannot be captured by single task annotations. This causes a need for subsequent annotations, with interdependent questions and answers describing the nature of the subject at hand. Even in the case a phenomenon is easily captured by a single task, the high specialisation of most annotation tools can result in having to switch to another tool if the task only slightly changes. We introduce HUMAN, a novel web-based annotation tool that addresses the above problems by a) covering a variety of annotation tasks on both textual and image data, and b) the usage of an internal deterministic state machine, allowing the researcher to chain different annotation tasks in an interdependent manner. Further, the modular nature of the tool makes it easy to define new annotation tasks and integrate machine learning algorithms e.g., for active learning. HUMAN comes with an easy-to-use graphical user interface that simplifies the annotation task and management.