Search Pathways: Modeling GeoData Search Behavior to Support Usable Application Development

Recent technical advances have enabled development of new scientific data discovery systems. Metadata brokering, linked data, and other mechanisms allow users to discover scientific data of interes across growing volumes of heterogeneous content. Matching this complex content with existing discovery technologies, people looking for scientific data are presented with an ever-growing array of features to sort, filter, subset, and scan through search returns to help them find what they are looking for. This paper examines the applicability of available technologies in connecting searchers with the data of interest. What metrics can be used to track success given shifting baselines of content and technology? How well do existing technologies map to steps in user search patterns?

Taking a user-driven development approach, the team behind the Arctic Data Explorer interdisciplinary data discovery application invested heavily in usability testing and user search behavior analysis. Building on earlier library community search behavior work, models were developed to better define the diverse set of thought processes and steps users took to find data of interest, here called 'search pathways'. This research builds a deeper understanding of the user community that seeks to reuse scientific data. This approach ensures that development decisions are driven by clearly articulated user needs instead of ad hoc technology trends. Initial results from this research will be presented along with lessons learned for other discovery platform development and future directions for informatics research into search pathways.