![]() ![]() NOTE: There are few advantages in using the predefined classifications in this case 12.3.2. Usually one will do and you can just have as many attributes underneath it as you might require to organise all the different data. TIP: you only need more than one classification if you really have different data for which VERY different attributes are needed. MAKE A NODE CLASSIFICATIONīe in the Classsifications function (see Navigation bar) Create/Node Classification see Figure 12.2. Items can be added to or removed from folders and setsd at any stage of your work.įor reminders on how to create Folders go to 5.3.7įor reminders on how to create Sets go to 9.2.4Ģ.Create one or two attributes under the classification (just to try it out)ģ.Make a folder for the new structural nodes (case or respondent type nodes) Remember that Folders contain the actual items, whereas Sets contain short-cuts to Nodes and Sources - So an item like a source document should only belong in one Folder but the same item can belong in multiple Sets. This is enabled via nodes representing and applied to all the data for each e.g. to each Node but via its link the Node Classification. The Node Classification enables any number of attributes to be created below it…and that is how socio demographics are assigned i.e. ![]() for each respondent to a Node Classification (usually only one, but depends on the spread of data and different elements of the research project). ABOVE, more difficult to grasp but more efficient: Link the (structural) nodes e.g. Use another entity the Node Classification = most efficient and INSTEAD OF POINT B. All your queries will use combinations of nodes codes rather than any other entities of organisation (or combined with folders)Ĭ. use this rather than the below option only if you really do not understand option C. You can combine/copy/merge those case type nodes into another node based on a socio demographic characteristic (and so on with other socio demographic values) female, male, OR female of 20-29yrs old etc. Where a file consists of more than one case you can use the code/node applied to each case to view just that case (say one speaker from a focus group)ī. Once you have done this (however you do it see below at section 12.2) It enables several possibilities for you straightaway.Ī. Sometimes nodes will be needed to represent observations, field notes, or material about studies or places. If the answer to the second question above was YES and you do have a complex dataset with many socio-demographic or other information to keep in mind about your respondents/cases then you need to create Nodes which act as structural nodes representing for your individual respondents or the other units of analysis you are dealing with. 12.1.2 MORE COMPLEX METHODS OF ORGANISATIONĬreating nodes to represent and code respondents/cases/other units of analysis (Though you can do separate queries to build up a sense of comparison). to produce an easy cross tabulation matrix style output in one query. Multiple folders cannot be searched ‘across’ - i.e. They can’t be combined to create more complex scoping for a query. You may already have organised you source files in folders – these can act as a filtering device when doing later Queries ‘Items in Selected Folder’ using the query tool – similarly Sets (if you have sources there) can acts as an ‘Selected item’ to filter to. If the answer is YES, y ou probably need to make a choice from the more complex methods of data organisation 12.1.1. complex facts, features and information to keep in your head when it will come to interrogating and comparing across and within different files and cases? If the answer is YES you can ignore the more complex options for data organisation and possibly focus on the simpler options.Ģ.Do you have too much information i.e. We strongly advise you to follow the logic of all the advice below in sequence.ġ.Do you have a very homogenous data set with not many differences in respondent type or socio demographic characteristics are not relevant? Some of the methods you may already be using. We all the methods (and state their shortcomings if there are any, so that you can make the right choice for your data). Organizing data using NVivo’s most efficient method for doing so is not the easiest process to absorb and get right. This section only deals with the organisation of primary data – see a short section at the end which discusses the organisation of e.g. ![]()
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