  This research investigates User Experience (UX) issues in dataset search,
targeting Google Dataset Search and data.europa.eu. It focuses on 6 areas
within UX: Initial Interaction, Search Process, Dataset Exploration, Filtering
and Sorting, Dataset Actions, and Assistance and Feedback. The evaluation
method combines 'The Pandemic Puzzle' user task, think-aloud methods, and
demographic and post-task questionnaires. 29 strengths and 63 weaknesses were
collected from 19 participants involved in roles within technology firm or
academia. While certain insights are specific to particular platforms, most are
derived from features commonly observed in dataset search platforms across a
variety of fields, implying that our findings are broadly applicable.
Observations from commonly found features in dataset search platforms across
various fields have led to the development of 10 new design prototypes. Unlike
literature retrieval, dataset retrieval involves a significant focus on
metadata accessibility and quality, each element of which can impact
decision-making. To address issues like reading fatigue from metadata
presentation, inefficient methods for results searching, filtering, and
selection, along with other unresolved user-centric issues on current
platforms. These prototypes concentrate on enhancing metadata-related features.
They include a redesigned homepage, an improved search bar, better sorting
options, an enhanced search result display, a metadata comparison tool, and a
navigation guide. Our aim is to improve usability for a wide range of users,
including both developers and researchers.
