Evaluating the user experience and annotation framework of 'Interwoven': enhancing digital storytelling and engagement with cultural heritage
'Interwoven' is a pioneering platform in South Asia that merges artificial intelligence and machine learning technologies to offer a unique narrative of global textile collections (https://interwoven.map-india.org/). The platform uncovers unseen connections between artworks from diverse cultures, presented visually and intuitively to inspire exploration and discovery. By critically evaluating the AI model's architecture and interface in ‘Interwoven,’ this session will explore how the architecture and interface of the 'Interwoven' platform can be optimised to enhance user engagement and interactivity, improve cultural heritage object annotation, and stimulate more effective storytelling experiences.
The research will base itself on:
1) A comprehensive literature review of existing knowledge in the field of digital humanities and digital heritage.
2) Interviews with designers and developers of 'Interwoven' to understand the platform's development process, underlying principles, and intended user experience.
3) Usability tests with the target audience, utilising heuristic principles of interactive design to evaluate the effectiveness of the platform's user interface.
Using a multi-pronged approach of enquiry, the larger objective of the presentation is to analyse the current annotation and its limitations to address the challenges in creating robust and consistent metadata for diverse cultural heritage objects; to explore the role of user vis-a-vis curators and annotators in such context; and finally, to investigate the extent to which the visualisation of cultural heritage in this platform enables a casual browser to transform into an enthusiastic and informed user through practical tools of storytelling.
