Meeting the Challenges of Teamwork

A growing number of projects involve multiple researchers working collaboratively. While teams offer higher productivity and a richer perspective, they also present a number of management challenges. Early in a project it is important to determine the approach your team will take to:

Collecting and organizing data

Many large projects - including those spread over time or geographical location - need to manage an ever-growing volume of data. NVivo can help in the following ways:

In smaller projects, you may choose to share a single NVivo project file. In this scenario, it is still important that each researcher access the project using their unique user profile.

Only one user can access an NVivo project file at a time.

Creating and cataloguing themes and topics

Where coding consistency is important, you will need to negotiate and agree on a node structure early in the project. Have regular discussions about node definitions and how the node system is evolving. In NVivo you can:

While a common node structure is important for efficiency and reliability— it should remain flexible so that new insights and exciting ideas are not lost.

One method of retaining this flexibility is for each researcher to add a node to their project which is named just for them, e.g. 'Fiona'. Using this node as the parent (top level node), any new nodes they create can be stored under this parent node and coded to. When projects are merged together, even if two researchers have created child nodes with the same name, these nodes will stay separate and easily identifiable (because their hierarchical names are unique) so coding can be discussed and if required, the node(s) moved into the main node structure.

Coding the data

If multiple researchers are coding the same data set, you may be interested in the consistency of their coding. NVivo provides a number of ways to check consistency or coder reliability:

Remember that inconsistency in coding is not necessarily negative— it may prompt productive debate and deeper insights into the data.

Related Topics