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Data and code from: Variability in academic research data management practices: implications for data services development from a faculty survey

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https://ir.library.oregonstate.edu/concern/datasets/qz20sx53f

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Abstract
  • This dataset includes comma-separated text files with tabular data from survey responses and the R code used to visualize them. The following abstract describes the research study. See the README file for a more thorough description of the data. Purpose: The purpose of this case study is to demonstrate how knowledge of local research data management (RDM) practices critically informs the progressive development of data services (RDS) after basic services have already been established. Design/methodology/approach: An online survey was distributed via email to all university faculty in the fall of 2013, and was left open for just over one month. We sent two reminder emails before closing the survey. Survey data were downloaded from Qualtrics survey software and analyzed in R. Findings: In this paper, we reviewed a subset of survey findings that included data types, volume, and storage locations, RDM roles and responsibilities, and metadata practices. We found that OSU researchers are generating a wide variety of data types, and that practices vary between colleges. We discovered that faculty are not utilizing campus-wide storage infrastructure, and are maintaining their own storage servers in surprising numbers. Faculty-level research assistants perform the majority of data-related tasks at OSU, with the exception of data sharing, which is primarily handled by the professorial ranks. We found that many faculty on campus are creating metadata, but that there is a need to provide support in how to discover and create standardized metadata. Originality/value: This paper presents a novel example of how to efficiently move from establishing basic RDM services to providing more focused services that meet specific local needs. It provides an approach for others to follow when tackling the difficult question of, “What next?” with regard to providing academic research data services.
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  • Whitmire, Amanda L. (2015): Data and code from: Variability in academic research data management practices: implications for data services development from a faculty survey. Oregon State University. Dataset. http://dx.doi.org/10.7267/N9J1012R
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  • description.provenance : Approved for entry into archive by Amanda Whitmire(amanda.whitmire@oregonstate.edu) on 2015-04-10T23:16:58Z (GMT) No. of bitstreams: 3license_rdf: 1089 bytes, checksum: 0a703d871bf062c5fdc7850b1496693b (MD5)DataFiles.zip: 8124 bytes, checksum: 947e6378f5e12dd58b018a282054e23d (MD5)RCode.zip: 6568 bytes, checksum: 5e4fb17f3b9ba0ef87ad6d0b0abf0a11 (MD5)
  • description.provenance : Made available in DSpace on 2015-04-10T23:16:58Z (GMT). No. of bitstreams: 3license_rdf: 1089 bytes, checksum: 0a703d871bf062c5fdc7850b1496693b (MD5)DataFiles.zip: 8124 bytes, checksum: 947e6378f5e12dd58b018a282054e23d (MD5)RCode.zip: 6568 bytes, checksum: 5e4fb17f3b9ba0ef87ad6d0b0abf0a11 (MD5)
  • There are two zip folders associated with this dataset, DataFiles.zip and RCode.zip. The file list for each folder is given in the README file. The data files are comma-separated text files containing data that has been exported from Qualtrics survey software and extracted from the larger dataset. These data support a manuscript published in the journal Program, titled, “Variability in academic research data management practices: implications for data services development from a faculty survey”.
  • description.provenance : Submitted by Amanda Whitmire (amanda.whitmire@oregonstate.edu) on 2015-04-10T23:16:15ZNo. of bitstreams: 3license_rdf: 1089 bytes, checksum: 0a703d871bf062c5fdc7850b1496693b (MD5)DataFiles.zip: 8124 bytes, checksum: 947e6378f5e12dd58b018a282054e23d (MD5)RCode.zip: 6568 bytes, checksum: 5e4fb17f3b9ba0ef87ad6d0b0abf0a11 (MD5)
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Thumbnail Title Date Uploaded Visibility Actions
file details RCode.zip 10/10/2017 Public
file details DataFiles.zip 10/10/2017 Public
file details README_Whitmire_Program_dataset.docx 10/10/2017 Public