Sign in or register
for additional privileges

Using NVivo: An Unofficial and Unauthorized Primer

Shalin Hai-Jew, Author

You appear to be using an older verion of Internet Explorer. For the best experience please upgrade your IE version or switch to a another web browser.

Conducting Data Queries... (Part 2 of 2)

Some Types of Data Queries

So what are some of the data queries that may be conducted in NVivo?  In the NVivo ribbon, go to the Query tab. Click it to see some of the various tools that may be used to query the data inside the project.

Queries are used both for data exploration (and discovery) and for hypothesis testing.  They are used for straight-up data analytics. 

Advanced Find 

“Advanced Find” is a data query capability that enables a user to set various conditions and filters for finding particular information. This requires researcher intimacy with the data (which is generally advisable anyway for quality research), and it enables the calling up of selected resources in the List View of the project. 

Query Wizard

The “Query Wizard” enables the major text queries albeit in a step-by-step process and without the typical verbiage.  The selections read: 

  • "See where particular terms occur in context (word search and word tree)
  • Identify frequently occurring terms in content (word frequency count) 
  • Search for content based on how it is coded (advanced search) 
  • Cross-tabulate how content is coded (matrix query)"   

This wizard will take a user through each of the necessary steps in defining the parameters of the particular data extraction.  Once the sequences are clear, it is sufficiently simple to walk through the steps without the Query Wizard. (To do this, users would just go to the direct "Text Search," "Word Frequency," "Coding," and "Matrix Coding" buttons in the Create area of the Query tab in the ribbon.)  

Macros / Sequences of Data Queries and Data Processing

Any of the data queries may be saved as "macros." These are sequences of parameterized data queries that may be re-run again and again as the research proceeds, and more data is ingested.  Data queries may be run at any time in the research sequence for researcher awareness and data acquisition.  The results of the data queries may be saved separate from the macros (the computer-based directions for the data extractions).  What follows are some more direct queries.  

Direct Data Queries 

The following section includes a brief summary of the various types of data queries that may be conducted in NVivo.  Linked to this page are additional pages that show "how" to conduct the various listed data queries.  

Text Search:  

This feature enables users to locate particular words, phrases, equations, and concepts (data "strings") within any of the contents in the NVivo project.  

Word Frequency: 

This feature enables a machine-based "summary" of the main ideas (albeit without sentiment or direction) of an NVivo project (and any of its subsets of folders, nodes, text corpuses, and datasets, etc.) by the culling of popularly used (mostly semantic) words.  


This feature enables the identification of intersecting coded information, such as overlaps between particular nodes and concepts, and intersections of contents coded to particular nodes. This may also enable the culling of subsets of data based on particular attribute values. For example, this would enable the collecting of responses based on respondent characteristics, such as all (survey, interview, focus group, Delphi study, or other aspect) respondents who fit within certain subsets (gender, age, socio-economic status / SES, or other categories or descriptors).  

Matrix Coding: 

Matrix coding enables the search for shared occurrences of data or concepts across node-based variables, folders, sources, or other objects.  

Coding Comparison:  

A coding comparison enables those in a research team to compare how multiple coders or multiple teams of coders coded to a particular node.  This may be used to help in “norming” coding (raising inter-rater reliability), promoting discussions of coding among the team, and / or developing or evolving a shared codebook (and shared understandings around coding with a codebook).  


A compound query enables the identification of certain terms that are in relationship to other terms, with relationships such as the following:  "AND," "OR," "AND NOT," "NEAR Content," "PRECEDING CONTENT," and "SURROUNDING Content".  These relational connectors enable the finding of targeted and precise contents.  This is an advanced type of query.  The text searches may be done across types of contents (whether documents and codes or others). This query then enables fine-grained queries for particular data by a researcher who is quite familiar with his / her / their dataset.  


The group data query enables users to find items associated in defined / particular ways with other items.  The associational definitions may include “coding, attribute value, relationships,” and others.  (Some of this functionality may be viewed visually in the links or models functions.  Many such groupings may remain "invisible" or "latent" to researchers until these are extracted.  

Readers may follow the path below in order to get the specifics on the various ways to conduct the data queries.  Or they may continue along the sequential book path. 

Matrix Queries in NVivo

To gain a sense of some of the matrix queries in NVivo, the downloadable slideshow "Matrix Queries in NVivo 10" may be helpful. 

Storage of Saved Queries (Macros)

To access queries that were saved, in the Navigation View (bottom left), go to Queries. Above that section, go to the proper folder (Queries or Results), and double click.  Select the desired results from the List View, and double click. 

Any matrix coding results will be available in either a matrix format or a chart (data visualization) format (in the Detail View area).  

The idea behind a macro is that complex scripts that will be re-used do not have to be rewritten every time.  Rather, it is possible to just call up the macro and apply it to the new data or to the original data set and additional collected data. 
Comment on this page

Discussion of "Conducting Data Queries... (Part 2 of 2)"

Add your voice to this discussion.

Checking your signed in status ...