Getting started with ATLAS.ti

Data and project management

Think of your ATLAS.ti project as an excursion into unknown territory. The data material is the terrain that you want to study; the chosen analytic approach is your pathway through it. The tools and functions provided by ATLAS.ti are your equipment to examine what there is to discover. The preparation of the data material is like choosing the right time for the journey. Rain and storm can complicate a planned excursion. This also applies to your project, if, for example, during the transcription, the peculiarities of a computer-aided analysis are not taken into consideration, or if the data file formats are not chosen optimally. A well-designed project set-up is like carefully planning your trip, so you do not make a wrong turn at the first intersection and end up in a dead end. In this article you learn about the various file types ATLAS.ti supports, how to prepare transcripts and how to set up your project. Regarding the latter, it helps to know some technical details. Don’t worry, it is not complicated. Knowing a few things about how ATLAS.ti handles documents will make it easier for you to manage your project(s).

Supported data file formats

Guidelines for preparing interview transcripts

When you prepare interview transcripts, mark all speakers unambiguously and enter an empty line between each speaker in turn. This increases readability and if you want to use the auto coding feature, this will allow you to code hits within a given speaker unit.

In the sample transcript above, the paragraph marker is visible, showing when the Enter button was pressed. The two speakers in the transcript are marked with unique identifiers:

INT: is used for the interviewer

AL: for Alexander, the interviewee.

Using ‘Interviewer’ or ‘Alexander’ as speaker IDs would be impractical as markers because those words might appear in the text itself. In addition, it is a lot to type and prone to typing errors. The character combinations INT: and AL: are not likely to be found anywhere else. This is essential for using the auto coding tool.

This way of organizing the transcript can be used for any documents that include structuring elements, like dates in historical documents, emails or letters. Although neglecting these best-practice rules will not have a negative effect initially, you may later regret not having used them from the beginning.

Guidelines for focus group transcripts

Everything I wrote above for interview transcripts also applies to focus group transcripts. If you want to compare the responses of individual speakers, each speaker unit needs to be coded. ATLAS.ti can recognize speakers with a unique ID like ‘Anne:’ or ‘@Anne:’. Based on these, ATLAS.ti finds all speaker units, and you can automatically code them with both speaker names and other attributes.

For further information see here.

Naming documents

I recommend that you name your documents in a way that is useful for the analysis. For instance, include criteria that you already know are important for your analysis like gender, age, profession, location or the date of the interview.

Naming your files in this way has the advantage that the documents are already sorted by these criteria. This helps creating documents groups in ATLAS.ti for analytic purposes (see below). In addition, a good analytic name gives valuable information when retrieving data and, overall, adds transparency to your project. If you create reports, the document name is displayed above each quotation.

If you have already created a project before reading this suggestions, you can rename each document in ATLAS.ti: Open the Document Manager, right-click on a document and select Rename.

Project management in ATLAS.ti

The aim of this section is to help you understand what is happening when you add documents to a project and to introduce you to a few technical issues that happen behind the scenes. Let’s assume that you have conducted an interview study and have 20 audio-recorded interviews. You transfer the audio files to your computer and begin to transcribe and save the resulting text files somewhere on the computer, using your own system for organizing and storing them. Next, you want to analyze the data with the help of ATLAS.ti. You open ATLAS.ti and begin to add data to your project.

When adding documents to a project, they are copied, converted and stamped with a unique ID and become internal ATLAS.ti files. This means ATLAS.ti no longer needs the original files. However, I recommend that you keep a backup copy of the original source files.

The unique ID consists of a combination of letters and numbers and looks something like this: 0e5418ea58a94fd28b7d5bd937f884a2.

It allows ATLAS.ti to recognize each document unambiguously as the name of a document, as not even a combination of name and size can ensure that the content of two documents are indeed the same. This is especially important for merging projects when working in a team. The way you ensure this is for one person to oversee setting up the project and adding documents. Everybody else who will be working on the project needs to wait for that person to share with them a project bundle file.

If you want to view or touch your project as a file, either to share it, to transfer it to another computer or to make a backup copy, you need to export it and save it project bundle file.

One last thing that you need to know is that libraries cannot be created or moved to a cloud sharing service like Dropbox, OneDrive and Google Drive. One purpose of cloud sharing services is that they synchronize data across different devices. This could quickly mess up an ATLAS.ti library and result in incoherent projects. To avoid this, ATLAS.ti prohibits creating or moving libraries to such locations. As ATLAS.ti may not catch all available cloud sharing services, you may be able to outsmart the program. This may, however, have dreadful consequences, as nothing is worse than losing an already coded data set and having to code it all over again. If you want to work in the cloud, use the ATLAS.ti Web version instead.

Setting up a project

Open ATLAS.ti and create a new project in Windows:

Open ATLAS.ti and create a new project in Mac:

All added or linked documents are numbered consecutively, starting with D1, D2, D3 and so on. The assignment of the numbers is determined by its position in the list of documents. The default sort order is by name, i.e. in alphabetical order for each batch of documents that you import.

Commenting on your data and keeping track of analytic thoughts

You can enter a comment for each document. This may not be necessary for all types of projects, but users often do not think of adding information they already have. My advice is to include all information in your ATLAS.ti project that is relevant for the analysis. When analyzing interview transcripts, researchers often write an interview protocol. But instead of adding it to their ATLAS.ti project, they store the protocols as Word files in another folder. I recommend copying and pasting the protocols into the comment field of the respective document, so you have all information in one place. The likelihood that you will look at the protocols again is much greater when they become part of your ATLAS.ti project.

When working with newspaper articles or reports, add information about the source, such as a description of the newspaper, its circulation, readership, and from where you retrieved the document. If the article or report is available online, you can also add the link to the original source. Each document with a comment shows a little yellow Post-it in the document icon.

To see the comment field in ATLAS.ti Windows, you must click on the burger menu on the right-hand side (see image below).

In the Mac version, the comment field is available in the inspector on the right-hand side.

After you have added and commented your documents, don’t forget to save the project.

Organizing project documents

When you start a project, you should first consider where and at what level the cases are in your data. Is each document a case that you want to compare to other cases? Or are several documents a case, such as female and male respondents? To ease the handling of the different types of data, they can be organized into document groups. Document groups allow quick access to subsets of your data. They can be used for analytic comparisons in later stages of the analysis. Examples of document groups are the classic socio-demographic variables of gender, age groups, material status, profession, location, etc. For an analysis of newspaper articles, you may want to group by country, circulation and type of newspaper.

Groups can also be useful for administrative purposes in team projects by, for instance, creating a group that holds all documents for coder 1, another group that holds the documents for coder 2 and so on.

It is possible to add each document to more than one group; it is not an exclusive either/or allocation. In a classical interview study, you may want to group a document into groups like gender: female, marital status: single and profession: high-school teacher.

In the following video you can see how to create groups in Windows:

In the following video you can see how to create groups in Mac:

Cases can also be embedded within documents – for example, the different speakers in focus groups. Depending on whether the case is at the document level or within the documents, you must handle it differently. If the cases are inside the documents, you must code them. For focus groups or other structured data, ATLAS.ti can do this for you automatically. See here for further detail.

Exporting projects for project transfer or backup

Computer hard disks can fail; laptops can be stolen. Therefore, storing a copy of your project elsewhere is best. You do this by exporting a project bundle file. I recommend keeping a copy of your project on a server, in the cloud, or on an external drive. Different from libraries, project bundle files can be stored in the cloud.

Project bundle files also need to be used to transfer projects between computers. Thus, you need to bundle files when working in a team or if you work on different computers.

To export your project to either save it as a backup or to use it for transferring it to a different computer:

In ATLAS.ti Windows:
Select File > Export.

In ATLAS.ti Mac:
From the main menu, select Project > Export > Project.

Select a name and location where you want to store the project and select Save.

You can rename bundle files. However, renaming the bundle does not automatically change the name of your project. Think of the project bundle file like a box that holds all documents that you added to a project + all your codes, codings, memos, groups, networks, etc. The latter information is stored in an internal project file. Putting a different label on the outside of the box does not change anything that is inside. The ATLAS.ti project file “lives” within the ATLAS.ti environment. You cannot extract it separately from the project bundle file.

Make it a habit to create a project bundle file after each work session and store it in a safe place. You may keep a few rolling copies of the project bundle and from time to time remove older versions.