Surveys and datasets

The table below displays an example of a dataset containing survey responses. Each row represents a single survey respondent. The columns contain responses to closed-ended questions (demographics about the respondent) and open-ended questions (codable content).

The table below displays a simplified example of a dataset containing Facebook data imported from an NCapture file. Each row represents a single post or comment. The structure and columns are automatically defined.

When you autocode datasets containing social media data like this one, there are extra options, that make it easy to autocode the content based on the predetermined fields—for example, you could code this Facebook content by Username or Conversation.

And, when you autocode by Username, cases are created and biographical information about the Facebook user is stored as attribute values on the case (you do not need to use the Classify Cases from Dataset Wizard for this).

You cannot change the analysis type (codable or classifying) of a column after import, so you should decide how you want to use your data before you import a dataset.

Open-ended questions that contain data you want to analyze are created and coded to codes (codable)—for example, responses to open-ended survey questions such as How do you think we can reduce our carbon emissions?

Close-ended questions that describe your data (metadata) are created as attributes (classifying)—for example, the ID number, Age and Annual Income of your survey respondents. Values in classifying fields:

• Can be used to sort and filter the records in your dataset.
• Provide context when you view coded dataset content in a code.
• Can be used to build case structures that group your codable content—for example, by Age or Sex.
• Can be used to create and classify cases that represent the subjects of your research. For example, if you create a 'person' case for a survey respondent, you can use the classifying field values Age or Sex as attribute values on the case.

Surveys must contain a unique identifier that identifies the responses of each individual. A unique identifier could be the respondent's name, however, in a large survey, names may not be unique. For uniqueness and to protect the identity of your respondents, you may prefer to manually assign each respondent a unique ID number. You can then gather all responses of an individual respondent to a single code.

You cannot add additional rows or columns to a dataset after import, so it is important to gather your data before you start the import operation.

For each dataset that you want to create, your data must be gathered into one of the following:

• Microsoft Excel spreadsheet (.xlsx or .xls)
• Tab or comma delimited text file (.txt or .csv)

Text files must be organized as a tab or comma-delimited field values, so that the Survey Import Wizard can divide the contents into rows and columns. Each record must be on a separate line, and each field must be separated by the delimiter. The following is an example of a comma-delimited text file:

You cannot select multiple worksheets (within a spreadsheet), so the data you want to import must be gathered into a single worksheet.

The maximum amount of data that can be imported into a single dataset is 256 fields (columns) and 1,048,576 records (rows).

1. Open the spreadsheet file that contains your data in Microsoft Excel.
2. Ensure that the data is gathered into a single worksheet.
3. Review your data as described below:

   Element	Description
   Unsupported characters	If the cells contain any of the following characters, you should remove these characters before importing: & @ * $ | % ~ - + / \
   Blank rows	Remove any blank rows within the data.
   Extraneous content	Your file should contain only the rows you want to import, and (optionally) a 1st row containing field labels. Any other content should be removed.
   Data types	Make sure every value in a field contains the same type of data. During the import operation, NVivo scans the first 25 rows of your file to determine what data types are appropriate for each field. If you choose to import a field using the date, time, date/time, Boolean, integer or decimal data types, all the rows in your text file must contain valid data for that data type. If a row after the 25th line, contains invalid data, the import operation will terminate with errors.
   Merged cells	Merged cells can cause errors during the import operation. We recommend that you do not import spreadsheets containing merged cells.
   Calculated values	If a cell displays a calculated value, the displayed value (not the formula) is imported into the dataset.
   Error values	If any of the cells in your worksheet display error values such as #NUM or #DIV, you should correct them before you start the import operation. Columns containing error values can only be imported as text fields.
   Buttons and checkboxes	If any cells contain controls such as buttons or checkboxes the spreadsheet cannot be imported. You should remove these controls before import.

4. Close the spreadsheet. Keeping the file open may cause errors during the import operation.

Open the file that contains your data in a text editor, such as Notepad, then review your data as described below:

The Survey Import Wizard examines the data you are importing and helps you to ensure that the data is imported the way that you want.

1. On the Import tab, in the Survey group, click either Excel or Text File.
2. Click the Browse button, and then locate and select the file you want to import.
3. Click Open.
4. Follow the instructions in the Survey Import Wizard.

   Wizard step	Description
   Introduction	Understand the outcomes of the survey import. NVivo will import your data as a dataset, as well as create cases, codes and attributes in your project.
   Check your data format	For Spreadsheets Specify how many rows are used for your column headers. If your data contains dates, select the format the dates are in. If your spreadsheet contains multiple worksheets, select the worksheet that contains the data you want to import.   For text files Select the file encoding that is used in the text file. NVivo tries to detect the file encoding used in the file—if the Data Preview area is blank or displays strange characters, try a different file encoding. Select the character that separates the values in your text file (tab or comma). Select the character (single or double quotation marks) that encloses text values in your text file. All text enclosed within text qualifiers is imported as one value, even if the text contains a delimiter character. For example, if the delimiter is a comma (,) and the text qualifier is a double quotation mark ("), "Dallas, Texas" is imported as one field value. If no text qualifier is selected, it is imported as two separate values. Specify how many rows are used for your column headers. If your data contains dates, select the format the dates are in. Check the Data Preview to make sure the settings are right for your data.
   Manage your survey respondents	Specify a location to store the cases resulting from the survey import. Select a question from your survey to uniquely identify your survey respondents, for example a name or ID. Specify a classification for the cases that will be created for your survey respondents.
   Identify open-ended and closed-ended questions	A preview of the first response in your survey is presented in a grid. On this screen you choose which fields contain open-ended values that you want to code (codable fields) and which fields contain closed-ended values that describe your respondents (classifying fields). Press the arrow buttons to preview responses from the first 25 respondents in the survey. Select the Closed Ended, Open Ended or Don't Import option to specify the questions you want to import and identify their data type. An open-ended question is generally a free response that you want to analyze for themes or ideas that arise. Close-ended questions are useful to describe respondents and ask questions of your open-ended questions. NOTE  You can change the question name—for example, to make it shorter or more meaningful. Click on the question and edit it. Press ENTER or TAB to save your changes.
   Autocode themes and sentiment	You can choose to automatically detect and code themes and sentiment in open-ended survey responses (available for NVivo installations with coding enhancements enabled).

5. Click Close when the Wizard is finished. A dataset file is created.

If you coded for themes and sentiment, NVivo presents the results visually in a results matrix and hierarchy chart.

NOTE  It can take some time to import and process surveys. This depends on the number of questions, the number of responses, and the amount of text in the responses. The larger your survey, the longer it will take to import.

• You cannot edit dataset content inside NVivo, so it is important to check and prepare your data before you bring it into NVivo. For example, you might want to check spelling or hide the identify of people or organizations mentioned in survey responses.
• You cannot change the analysis type and data type of fields (columns) after import, so you should consider how you want to use the fields, before importing the data.

You can double-click a dataset in List View to open it in Detail View.

When you open a dataset, it opens in Table View (below)—the records and fields are displayed in a grid:

Form View (below) shows only one record at a time, laid out as a form:

1 Classifying fields—contain information about your data—for example, the age and sex of survey respondents. Classifying fields have a gray background.

2Codable fields—contain the information you want to analyze—for example, responses to open-ended survey questions. Codable fields have a white background.

3Table and Form View tabs—use these tabs to switch between Table View and Form View. You may have additional tabs if your dataset was created by importing NCapture files containing social media data. For example, you may have a Chart tab or a Cluster Analysis tab.

When the dataset is open in Detail View, you can switch between Table View (view all records) and Form View (view one record at a time).

Each row in a dataset has a unique record ID, based on the order in which it is imported. The ID is the first column in Table View, and the first field in Form View. If you sort the dataset by the values in the ID column, the dataset is displayed in the order that the records were imported into NVivo.

You can navigate from record to record on Table or Form View by using the navigation buttons—you can move to the first, previous, next or last record.

Hidden records are not counted—the Status bar indicates if any records are hidden (filtered) or if all records are visible (the dataset is unfiltered). The record number does not correspond to the ID value or any other field value.

You can also:

• Use scroll bars to move up and down, or left and right
• Use 'Go To' to quickly jump to a dataset record ID, see-also link, or annotation If you try to jump to a record that is hidden, you will go to the next visible record.

When working in a dataset file you can:

• Sort or filter the dataset based on the values in classifying columns
• Annotate the text in codable columns
• Create see-also links on the text in codable columns
• Code or query the text in codable columns (you can also code file shortcuts)
• Autocode to organize the data—for example, you could gather the survey responses for each participant in a case
• Organize demographic attributes for your cases using the classifying information in the dataset (for example, age or gender)

After importing a dataset, a code is created for each open-ended survey question—a useful starting point for further exploration.

A case is created for each respondent which gathers all of a respondent's answers together. Descriptive data is created for the cases using the closed-ended (classifying) information in the dataset—this allows you to compare respondent attitudes based on attributes like age or education.

You can use a number of techniques to analyze the data—for example, you could:

• Code the content—select the text in a codable field and code to new or existing codes.
• Run a Word Frequency query to get a feel for what respondents are saying.
• Create charts to visualize the data—for example if you set up demographic data, you could create a chart to see how many cases are male and aged 50 to 59.

When you import data from surveys, spreadsheets or text files, you choose identify closed-ended and open-ended questions. NVivo uses this information to identify the responses as 'codable' or 'classifying'.

You cannot change the analysis type (codable or classifying) of a response after import, so you should decide how you want to use your data before you import a dataset.

Open-ended questions that contain data you want to analyze are created and coded to codes (codable)—for example, responses to open-ended survey questions such as How do you think we can reduce our carbon emissions?

Close-ended questions that describe your data (metadata) are created as attributes (classifying)—for example, the ID number, Age, Gender and Annual Income of your survey respondents. Values in classifying fields:

• Can be used to sort and filter the records in your dataset.
• Provide context when you view coded dataset content in a code.
• Can be used to build case structures that group your codable content—for example, by Age or Sex