The Landscape of Data Reuse in Interactive Information Retrieval: Motivations, Sources, and Evaluation of Reusability
Tianji Jiang, Wenqi Li, Jiqun Liu

TL;DR
This paper explores data reuse practices in Interactive Information Retrieval, revealing motivations, assessment strategies, and challenges faced by researchers to foster a sustainable data reuse culture.
Contribution
It provides empirical insights into IIR researchers' motivations, assessment methods, and concerns regarding data reuse, enriching understanding and promoting standards.
Findings
Researchers reuse data for efficiency and validation.
Assessment strategies include quality and relevance checks.
Challenges include data quality and accessibility issues.
Abstract
Sharing and reusing research data can effectively reduce redundant efforts in data collection and curation, especially for small labs and research teams conducting human-centered system research, and enhance the replicability of evaluation experiments. Building a sustainable data reuse process and culture relies on frameworks that encompass policies, standards, roles, and responsibilities, all of which must address the diverse needs of data providers, curators, and reusers. To advance the knowledge and accumulate empirical understandings on data reuse, this study investigated the data reuse practices of experienced researchers from the area of Interactive Information Retrieval (IIR) studies, where data reuse has been strongly advocated but still remains a challenge. To enhance the knowledge on data reuse behavior and reusability assessment strategies within IIR community, we conducted…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsData Quality and Management · Semantic Web and Ontologies · Research Data Management Practices
