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2017-07-18 Gregory, K. (Data Archiving and Networked Services) 10.17026/dans-zgu-qfpj
This study employed an extensive literature review to identify commonalities in the data retrieval practices of users of observational data. This dataset consists of a BibTeX file with the 146 bibliographic references examined in:
Gregory, K., Groth, P., Cousijn, H., Scharnhorst, A., & Wyatt, S. (2017). Searching Data: A Review of Observational Data Retrieval Practices. arxiv:1707.06937. [cs.DL]
The body of literature in the dataset was retrieved using different combinations of keyword searches, primarily in the Scopus database, across all fields. Keyword searches related to information retrieval (e.g. user behavior, information seeking, information retrieval) and data practices (e.g. research practices, community practices, data sharing, data reuse) were combined with keyword searches for research data. As the terms “data” and “search” are ubiquitous in academic literature, title searches also were employed and combined with the controlled vocabulary of the database to locate relevant information. Searches in Scopus included strings such as:
KEY ( user AND information ) AND TITLE-ABS-KEY ("research data" OR ( scien* W/1 data ) OR ( data W/1 ( repositor* OR archive* ) ) )
TITLE ( data W/0 ( search OR retriev* OR discover* OR access* OR sharing OR reus* ) )
AND ( LIMIT-TO ( EXACTKEYWORD , "Information Retrieval" ) OR LIMIT-TO ( EXACTKEYWORD , "Data Retrieval" ) OR LIMIT-TO ( EXACTKEYWORD , "Data Reuse" ) )
Bibliometric techniques such as citation chaining and related records were also applied. Pertinent journals and conference proceedings not indexed within Scopus (e.g. the International Journal of Digital Curation) were searched directly using similar keywords.
The approximately 400 retrieved documents were examined by close reading to identify articles referring to observational data for inclusion in the final dataset.
This work has funded by the NWO Grant 652.001.002 (programme Creative Industrie - Thematisch Onderzoek (CI-TO), Re-SEARCH: Contextual Search for Scientific Research Data)