Research Library

Preparing textual data for NVivo

Textual file formats supported by NVivo

  • .doc, .docx, .txt, .rtf, .pdf, .odt (Mac only)
  • Textual data is usually prepared as a Word document

The following features are supported:

  • All fonts and font sizes
  • All heading styles
  • All colours
  • Embedded images


General advice

  • We advise that you use pseudonyms instead of real names to protect privacy.
  • We will only apply Word Heading Style 1 to all the topic names. This can be done by using the Find and Replace tool in Word. There is no need to apply heading styles to the speaker – as you ‘Autocode by Speaker Name’ as explained later.


Things to avoid

  • Tables (when coded, text can be cut off at the end of a cell).
  • Putting key information in headers or footers - this will not be included when imported in NVivo. Instead put any description in the very first paragraph in the document.
  • Comment feature in Word - comments will not be included when imported in NVivo. You can comment in NVivo after importation using NVivo’s Annotation function.
  • Highlights will not import in NVivo.
  • Line numbering will not import in NVivo (and is not needed - an artefact of manual analysis methods).


Unstructured data

There is no special formatting needed for unstructured data.
Please follow the General Advice and Things to Avoid listed earlier.


Focus groups 

  • If possible, structure the focus group by speaker. Do this by placing the speaker name or speaker ID at the start of the line,or just above the line. An example is given below. There is no need to add any styles – keep it in normal style.
  • This means that you will be able to use the ‘Autocode by Speaker Name’ feature to automatically code each speaker in a focus group to so you have all the text of any given speaker in one place (a case). You will also be able to attach values to those cases (such as gender and so on).

SILVANA

I am going to ask you to tell me what your pseudonym is. And at the same time, if you can tell me what kind of an avatar you would choose to be if you wanted to represent yourself in some virtual world.

HOLLY

OK - so my pseudonym is Holly. Uhm, if I was an avatar I’d probably - if it’s like a personality thing - So I’m happy and friendly and I’d like to wear nice clothes - probably some jeans and some nice little shoes, probably black. And have like browny, red hair. But I want green eyes.
(Silvana: green eyes) Yeah.


OR:

SILVANA

So a happy, green-eyed red head with black shoes.
(Holly: yeah) And nice clothes - jeans. OK. Fine.

ROSE

My pseudonym is Rose. My avatar would be little. I’d be friendly but quite shy. Wear nice clothes, have blue eyes - brownish hair.


Structured documents – for highly structured interviews (Windows only)

Structured by topic areas or questions

If you have highly structured interviews, you can structure transcripts in a way that allows for auto-coding of these broad themes.

For this to work in NVivo, transcripts should have a unique identifier for EACH topic area that is the same for ALL  transcripts. The same wording for each transcript should be used, and you can also use numbers along with the topic if you wish. e.g. 01: Connection to Down East, 02: Natural Environment, etc. It’s best to keep the identifiers short. If a topic is missed, just leave it out. This will enable you to use Autocode > Use the style or structure.

See example below:

01: Connection to Down East

HENRY

What is your connection to Down East, how did you come
to be here?

THOMAS

I am not a Down Easter by generation in any sense.

02: Natural Environment

HENRY

What appeals to you about the area?

THOMAS

The beauty of the area is the main attraction.

03: Community and Environmental Change

HENRY

Since moving here, what changes have you seen?

THOMAS

Since the late 90’s this area has really experienced a boom. 


PDF files

  • PDF files can be imported in all editions of NVivo for Windows and Mac.
  • There are two types of PDF files - images and readable text. If you would like to text search your PDF files in NVivo, it is best to convert them to readable text, which can easily be done in the full version of Adobe Acrobat. The Mac version allows you to convert image files to readable text by clicking on the ‘Recognise text’ button in NVivo after importation.