Understanding Perspectives on Sharing Neutron Data at Oak Ridge National Laboratory. (29th June 2017)

• Record Type: Journal Article
• Authors: Donaldson, Devan Ray; Martin, Shawn; Proffen, Thomas
• Is Part Of: Data science journal. Volume 16(2017)
• Publication Date: 2017-06-29
• Subjects: Scientific data reuse -- data sharing -- neutron data -- data consumers -- data managers -- data producers; Science -- Data processing -- Periodicals; Database management -- Periodicals; 502.85
• DOI: 10.5334/dsj-2017-035
• Languages: English
• ISSNs: 1683-1470

Abstract

Even though the importance of sharing data is frequently discussed, data sharing appears to be limited to a few fields, and practices within those fields are not well understood. This study examines perspectives on sharing neutron data collected at Oak Ridge National Laboratory's neutron sources. Operation at user facilities has traditionally focused on making data accessible to those who create them. The recent emphasis on open data is shifting the focus to ensure that the data produced are reusable by others. This mixed methods research study included a series of surveys and focus group interviews in which 13 data consumers, data managers, and data producers answered questions about their perspectives on sharing neutron data. Data consumers reported interest in reusing neutron data for comparison/verification of results against their own measurements and testing new theories using existing data. They also stressed the importance of establishing context for data, including how data are produced, how samples are prepared, units of measurement, and how temperatures are determined. Data managers expressed reservations about reusing others' data because they were not always sure if they could trust whether the people responsible for interpreting data did so correctly. Data producers described concerns about their data being misused, competing with other users, and over-reliance on data producers to understand data. We present the Consumers Managers Producers (CMP) Model for understanding the interplay of each group regarding data sharing. We conclude with policy and system recommendations and discuss directions for future research.