An official website of the United States government
Researchers need to be able to find, access, and use data to participate in open science. To understand how users search for research data, we analyzed textual queries issued at a large social science data archive, the Inter-university Consortium for Political and Social Research (ICPSR). We collected unique user queries from 988,475 user search sessions over four years (2012-16). Overall, we found that only 30% of site visitors entered search terms into the ICPSR website. We analyzed search strategies within these sessions by extending existing dataset search taxonomies to classify a subset of the 1,554 most popular queries. We identified five categories of commonly-issued queries: keyword-based (e.g., date, place, topic); name (e.g., study, series); identifier (e.g., study, series); author (e.g., institutional, individual); and type (e.g., file, format). While the dominant search strategy used short keywords to explore topics, directed searches for known items using study and series names were also common. We further distinguished exploratory browsing from directed search queries based on their page views, refinements, search depth, duration, and length. Directed queries were longer (i.e., they had more words), while sessions with exploratory queries had more refinements and associated page views. By comparing search interactions at ICPSR to other natural language interactions in similar web search contexts, we conclude that dataset search at ICPSR is underutilized. We envision how alternative search paradigms, such as those enabled by recommender systems, can enhance dataset search.
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Transforming Data Discovery Through Behavior Modeling and Recommendation - Google Analytics Trace Data
This dataset contains trace data describing user interactions with the Inter-university Consortium for Political and Social Research website (ICPSR). We gathered site usage data from Google Analytics. We focused our analysis on user sessions, which are groups of interactions with resources (e.g., website pages) and events initiated by users. ICPSR tracks a subset of user interactions (i.e., other than page views) through event triggers. We analyzed sequences of interactions with resources, including the ICPSR data catalog, variable index, data citations collected in the ICPSR Bibliography of Data-related Literature, and topical information about project archives. As part of our analysis, we calculated the total number of unique sessions and page views in the study period. Data in our study period fell between September 1, 2012, and 2016. ICPSR's website was updated and relaunched in September 2012 with new search functionality, including a Social Science Variables Database (SSVD) tool. ICPSR then reorganized its website and changed its analytics collection procedures in 2016, marking this as the cutoff date for our analysis. Data are relevant for two reasons. First, updates to the ICPSR website during the study period focused only on front-end design rather than the website's search functionality. Second, the core features of the website over the period we examined (e.g., faceted and variable search, standardized metadata, the use of controlled vocabularies, and restricted data applications) are shared with other major data archives, making it likely that the trends in user behavior we report are generalizable.
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- Award ID(s):
- 2121789
- PAR ID:
- 10574919
- Publisher / Repository:
- ICPSR - Interuniversity Consortium for Political and Social Research
- Date Published:
- Subject(s) / Keyword(s):
- information retrival data archiving search web analytics
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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