Understanding the process of data reuse: An extensive review

Abstract

Data reuse has recently become significant in academia and is providing new impetus for academic research. This prompts two questions: What precisely is the data reuse process? What is the connection between each participating element? To address these issues, 42 studies were reviewed to identify the stages and primary data reuse elements. A meta‐synthesis was used to locate and analyze the studies, and inductive coding was used to organize the analytical process. We identified three stages of data reuse—initiation, exploration and collection, and repurposing—and explored how they interact and form iterative characteristics. The results illuminated the data reuse at each stage, including issues of data trust, data sources, scaffolds, and barriers. The results indicated that multisource data and human scaffolds promote reuse behavior effectively. Further, two data and information search patterns were extracted: reticular centripetal patterns and decentralized centripetal patterns. Three paths with elements cooperating through flexible functions and motivated by different action items were identified: data centers, human scaffolds, and publications. This study supports improvements for data infrastructure construction, data reuse, and data reuse research by providing a new perspective on the effect of information behavior and clarifying the stages and contextual relationships between various elements.

Reuse‐oriented data publishing: How to make the shared research data friendlier for researchers

“…We divide them into the following aspects: data context (the state of the data itself), research context (the researcher's individual circumstances and research settings), and the context of reuse paths, which enables researchers to access, understand and use the data (Wang et al, 2021).…”

“…Comparison and analyses are everyday data repurposing needs in this context. In contrast to the independent data reuse of individual data sets, integrative data reuse based on the integration of multi-source data is widely favoured by researchers (Pasquetto et al, 2017;Wang et al, 2021), involving comparisons, disaggregations, aggregations and format transformations (Fu et al, 2020;Spreng, 2017;Whitmore, 2016), which consumes a significant amount of time. The provision of data repurposing services by data repositories can boost researchers' satisfaction, with a productive tactic being data enrichment.…”

“…Therefore, researchers often undergo an iterative reuse process that requires them to request external assistance to consult on how to discover, acquire, understand and reprocess the data. This requires researchers to come into contact with elements like data repositories, data and their metadata, repository standardization measures, data documentation, relevant peer-reviewed publications, data creators, administrators, and peers across a wide range of disciplines (Kim, 2021;Rolland & Lee, 2013;Wang et al, 2021;Yoon, 2017). Various elements are in place to solve the problems encountered here.…”

The data paper as a sociolinguistic epistemic object: A content analysis on the rhetorical moves used in data paper abstracts

“…Second, despite the different paper structures across journals, most require authors to detail methods used to produce the data object and the repository of the dataset (Kim, 2020). Detailed information about how the data object was collected, processed, and shared can support the discovery and evaluation of data papers by other researchers (Faniel et al, 2019; Wang et al, 2021).…”

Seeing oneself as a data reuser: How subjectification activates the drivers of data reuse in science

“…A distinct literature on data reuse has begun to emerge, including conceptual work on just what it comprises. Scholars have documented often iterative stages of data reuse, including search and retrieval [ 10 ], sensemaking [ 11 ], and reprocessing or repurposing [ 12 ]. Others have offered typologies of approaches to reuse, as with one framework of a continuum from (more common) comparative to (less common) integrative reuses [ 13 ].…”