Land-River Interface Management Semi-Structured Interview Data

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dc.contributor.authorGrabowski, Robert
dc.contributor.authorAzhoni, Azhoni
dc.date.accessioned2024-06-04T04:29:07Z
dc.date.available2024-06-04T04:29:07Z
dc.date.issued2022-12-07 13:58
dc.description.abstract<strong>About the data:</strong> The data contained in this archive are collected through semi-structured interviews from officials in key organizations involved in land-river interface management in India. The interviews were conducted through online video conferencing and recorded which were later transcribed verbatim for analyzing the key challenges of land-river interface management in India. The Garret ranking data was collected at the end of the interviews and marked in the form by the interviewer. The research was conducted as part of a collaborative NERC Towards a Sustainable Earth project (2019-2022), with direct funding from the Indian Department of Biotechnology. <strong>File names:</strong> Each interview transcript is in different files with the file name indicating the type organizations the interview respondents represent, viz; Academic Institutions (AI), Central Government Agencies (CGA), Central Government Ministries (CGI), Non-governmental organizations (NG), and State Government Departments (SG). This files are being archived for future reference and for providing transparency to the research data.
dc.description.sponsorshipIndian Department of Biotechnology (BT/IN/TaSE/69/AA/2018-19)
dc.identifier.citationGrabowski, Robert; Azhoni, Azhoni (2022). Land-River Interface Management Semi-Structured Interview Data. Cranfield Online Research Data (CORD). Dataset. https://doi.org/10.17862/cranfield.rd.21679898
dc.identifier.doi10.17862/cranfield.rd.21679898
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/21827
dc.publisherCranfield University
dc.rightsCC BY 4.0
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectInterview'
dc.subject'India'
dc.titleLand-River Interface Management Semi-Structured Interview Data
dc.typeDataset

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LRI Semi-Structured Questions.docx
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