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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig4 Zehl FrontInNeuro2016 10.jpg|240px]]</div>
'''"[[Journal:Rethinking data sharing and human participant protection in social science research: Applications from the qualitative realm|Rethinking data sharing and human participant protection in social science research: Applications from the qualitative realm]]"'''
'''"[[Journal:Handling metadata in a neurophysiology laboratory|Handling metadata in a neurophysiology laboratory]]"'''


To date, non-reproducibility of neurophysiological research is a matter of intense discussion in the scientific community. A crucial component to enhance reproducibility is to comprehensively collect and store metadata, that is, all information about the experiment, the data, and the applied preprocessing steps on the data, such that they can be accessed and shared in a consistent and simple manner. However, the complexity of experiments, the highly specialized analysis workflows, and a lack of knowledge on how to make use of supporting software tools often overburden researchers to perform such a detailed documentation. For this reason, the collected metadata are often incomplete, incomprehensible for outsiders, or ambiguous. Based on our research experience in dealing with diverse datasets, we here provide conceptual and technical guidance to overcome the challenges associated with the collection, organization, and storage of metadata in a neurophysiology [[laboratory]]. ('''[[Journal:Handling metadata in a neurophysiology laboratory|Full article...]]''')<br />
While data sharing is becoming increasingly common in quantitative social inquiry, qualitative data are rarely shared. One factor inhibiting data sharing is a concern about human participant protections and privacy. Protecting the confidentiality and safety of research participants is a concern for both quantitative and qualitative researchers, but it raises specific concerns within the epistemic context of qualitative research. Thus, the applicability of emerging protection models from the quantitative realm must be carefully evaluated for application to the qualitative realm. At the same time, qualitative scholars already employ a variety of strategies for human-participant protection implicitly or informally during the research process. In this practice paper, we assess available strategies for protecting human participants and how they can be deployed. We describe a spectrum of possible data management options, such as de-identification and applying access controls, including some already employed by the Qualitative Data Repository (QDR) in tandem with its pilot depositors. ('''[[Journal:Rethinking data sharing and human participant protection in social science research: Applications from the qualitative realm|Full article...]]''')<br />
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Revision as of 17:00, 19 February 2018

"Rethinking data sharing and human participant protection in social science research: Applications from the qualitative realm"

While data sharing is becoming increasingly common in quantitative social inquiry, qualitative data are rarely shared. One factor inhibiting data sharing is a concern about human participant protections and privacy. Protecting the confidentiality and safety of research participants is a concern for both quantitative and qualitative researchers, but it raises specific concerns within the epistemic context of qualitative research. Thus, the applicability of emerging protection models from the quantitative realm must be carefully evaluated for application to the qualitative realm. At the same time, qualitative scholars already employ a variety of strategies for human-participant protection implicitly or informally during the research process. In this practice paper, we assess available strategies for protecting human participants and how they can be deployed. We describe a spectrum of possible data management options, such as de-identification and applying access controls, including some already employed by the Qualitative Data Repository (QDR) in tandem with its pilot depositors. (Full article...)

Recently featured:

Handling metadata in a neurophysiology laboratory
ISO 15189 accreditation: Navigation between quality management and patient safety
Compliance culture or culture change? The role of funders in improving data management and sharing practice amongst researchers