LibGuides: NVivo: Research Data Management

Research Data Management at VCC

Research Data Management refers to the storage, access and preservation of data produced from a given investigation. Data management practices cover the entire lifecycle of the data, from planning the investigation to conducting it, and from backing up data as it is created and used to long term preservation of data deliverables after the research investigation has concluded. 

Research around the world is moving to a model whereby researchers are expected to preserve data, rather than destroy it at the end of a study. Data sets are more often published independently or shared alongside publications. When data is preserved and made available to others to utilize, it increases research output in an efficient manner and provides opportunities to verify or extend findings. It is a lot of work to prepare data to be shared however, as it needs to go through a process of de-identification to protect the rights of participants, and also requires organizing and documenting so that it is discoverable and of use to others. NVivo has some built in features that support data documentation for this purpose.

"Data documentation is information about why and how data were created, prepared or digitized, what they mean, what their content and structure are an any alterations or coding that may have taken place. Good documentation is critical for understanding data in the short, medium and long term; and is vital for successful long-term data preservation" (Corti et al, 2019).

View the VCC Research Data Management guide for the VCC RDM Strategy and for information about planning, securing, organizing, and publishing data.

Resources

The Digital Resource Alliance of Canada offers a wealth of training materials on research data management.

Documenting Data in NVivo

Constructing documentation during analysis can support the analytic process and results in richer contextual information when data are shared.

Create classifications for persons, such as interviewees, data sources, etc.
Classifications can contain demographic information, dates/times of interviews, etc.
Classification sheets can be imported into NVivo12
Documentation files such as the description of the methodology, research plan, interview questions, consent form templates can be imported into the NVivo12 project file and stored in a "documentation" folder in the "Memos" folder
Descriptions can be added to all objects created in, or imported into the project file including data, documents, memos, nodes and classifications.
All textual documentation compiled during the project cycle can later be exported as spreadsheets to document preserved data collections.
Summary information about the project can be exported via project summary extract reports as text, MS Excel or XML file

Dataverse Guidance

Dataverse offers guidance on Curation and Metadata.

The Dataverse is an open source web application to share, preserve, cite, explore and analyze research data. Researchers, data authors, publishers, data distributors, and affiliated institutions all receive appropriate credit via a data citation with a persistent identifier (e.g., DOI, or handle).