
Identifying key timesteps in spatio-temporal datasets is essential for shaping the story that a simulation tells. The selected timesteps act as anchors for visualization, guiding parameter choices for rendering, animation, and analysis. While many sophisticated selection methods have been proposed, we show that the field has often leaned toward unnecessary complexity. In this work, we provide a survey of existing timestep selection strategies, illustrating their limited ability to balance quality and efficiency. Building on these insights, we introduce a deliberately simple approach based on greedy local search. Starting from uniformly spaced candidates, we iteratively shift selections to minimize reconstruction error under interpolation. Despite its simplicity, this method consistently yields high-quality subsets, enabling effective parameter tuning and exploratory visualization while achieving significantly lower computational cost than more elaborate techniques. Through quantitative comparisons across datasets and error metrics, we demonstrate that this purposeful simplicity can provide a better trade-off between quality and runtime than existing, more complex alternatives.

This paper presents the methodologies to extract the headline and illustrations from a historical newspaper for storytelling to support digital scholarship. It explored the ways in which new digital tools can facilitate the understanding of the newspaper content in the setting of time and space, "The Hongkong News" was selected from Hong Kong Early Tabloid Newspaper for the case study owing to its uniqueness in historical value towards the scholars. The proposed methodologies were evaluated in OCR (Optical Character Recognition) with scraping and Deep Learning Object Detection models. Two visualization products were developed to showcase the feasibility of our proposed methods to serve the storytelling purpose.

Museums are digitizing their collections of 3D objects. Video games provide the technology to interact with these objects, but the educational goals of a museum are often at odds with the creative forces in a traditional game for entertainment. Efforts to bridge this gap have either settled on serious games with diminished entertainment value or have relied on historical fictions that blur the line between reality and fantasy. The Vessel project is a 3D game designed around puzzle mechanics that remains a game for entertainment while realizing the benefits of incorporating digitized artifacts from a museum. We explore how the critical thinking present in solving puzzles can still encourage engagement of the story the artifacts have to tell without creating an historical fiction. Preliminary results show a preference for our in-game digital interaction over a traditional gallery and a desire to learn more about the artifacts after playing.