{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T19:00:20Z","timestamp":1772564420762,"version":"3.50.1"},"reference-count":57,"publisher":"SAGE Publications","issue":"3","license":[{"start":{"date-parts":[[2022,5,7]],"date-time":"2022-05-07T00:00:00Z","timestamp":1651881600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Librarianship and Information Science"],"published-print":{"date-parts":[[2023,9]]},"abstract":"<jats:p>\n                    Without sufficient information about research data practices occurring in a particular research organisation, there is a risk of mismatching research data service efforts with the needs of its researchers. This study describes how data acquiring and data sharing occurring within a particular research organisation can be investigated by using current research information system publication data. The case study organisation\u2019s current research information system was used to identify the sample of investigated articles. A sample of 193 journal articles published by researchers in the computer science department of the case study\u2019s university during 2019 were extracted for scrutiny from the current research information system. For these 193 articles, a classification of the main study types was developed to accommodate the multidisciplinary nature of the case department\u2019s research agenda. Furthermore, a coding framework was developed to capture the key elements of data acquiring and data sharing. The articles representing life sciences and computational research relatively frequently reused open data, whereas data acquisition of experimental research, human interaction studies and human intervention studies often relied on collecting original data. Data sharing also differed between the computationally intensive study types of life sciences and computational research and the study types relying on collection of original data. Research data were not available for reuse in only a minority of life science (\n                    <jats:italic toggle=\"yes\">n<\/jats:italic>\n                    \u2009=\u20092; 7%) and computational research (\n                    <jats:italic toggle=\"yes\">n<\/jats:italic>\n                    \u2009=\u200915; 14%) studies. The study types of experimental research, human interaction studies and human intervention studies less frequently made their data available for reuse. The findings suggest that research organisations representing computer sciences may include different subfields that have their own cultures of data sharing. This study demonstrates that analyses of publications listed in current research information systems provide detailed descriptions how the affiliated researchers acquire and share research data.\n                  <\/jats:p>","DOI":"10.1177\/09610006221093049","type":"journal-article","created":{"date-parts":[[2022,5,7]],"date-time":"2022-05-07T11:11:33Z","timestamp":1651921893000},"page":"596-608","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":12,"title":["Using current research information systems to investigate data acquisition and data sharing practices of computer scientists"],"prefix":"10.1177","volume":"55","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4184-7035","authenticated-orcid":false,"given":"Antti Mikael","family":"Rousi","sequence":"first","affiliation":[{"name":"Aalto University, Finland"}]}],"member":"179","published-online":{"date-parts":[[2022,5,7]]},"reference":[{"key":"e_1_3_4_2_1","doi-asserted-by":"publisher","DOI":"10.1108\/DLP-06-2020-0051"},{"key":"e_1_3_4_3_1","doi-asserted-by":"publisher","DOI":"10.1002\/meet.14505001041"},{"key":"e_1_3_4_4_1","unstructured":"Azeroual O Saake G Abuosba M et al (2018) Text data mining and data quality management for research information systems in the context of open data and open science. 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