Li, K.; Greenberg, J.; Dunic, J.: Data objects and documenting scientific processes : an analysis of data events in biodiversity data papers (2020)
0.03
0.027433997 = product of:
0.10973599 = sum of:
0.10973599 = weight(_text_:data in 5615) [ClassicSimilarity], result of:
0.10973599 = score(doc=5615,freq=36.0), product of:
0.14807065 = queryWeight, product of:
3.1620505 = idf(docFreq=5088, maxDocs=44218)
0.046827413 = queryNorm
0.7411056 = fieldWeight in 5615, product of:
6.0 = tf(freq=36.0), with freq of:
36.0 = termFreq=36.0
3.1620505 = idf(docFreq=5088, maxDocs=44218)
0.0390625 = fieldNorm(doc=5615)
0.25 = coord(1/4)
- Abstract
- The data paper, an emerging scholarly genre, describes research data sets and is intended to bridge the gap between the publication of research data and scientific articles. Research examining how data papers report data events, such as data transactions and manipulations, is limited. The research reported on in this article addresses this limitation and investigated how data events are inscribed in data papers. A content analysis was conducted examining the full texts of 82 data papers, drawn from the curated list of data papers connected to the Global Biodiversity Information Facility. Data events recorded for each paper were organized into a set of 17 categories. Many of these categories are described together in the same sentence, which indicates the messiness of data events in the laboratory space. The findings challenge the degrees to which data papers are a distinct genre compared to research articles and they describe data-centric research processes in a through way. This article also discusses how our results could inform a better data publication ecosystem in the future.
