The image of ATLAS.ti as a knowledge workbench is more than just a lively analogy. Analytical work involves tangible elements: research material requires piecework, assembly, reworking, complex layouts, and some special tools. A well-stocked workbench provides you with the necessary instruments to thoroughly analyze and evaluate, search and query your data, to capture, visualize and share your findings.
To understand how ATLAS.ti handles data, visualize your entire project as an intelligent container that keeps track of all your data. This container is your ATLAS.ti project.
The project keeps track of the paths to your source data and stores the codes, code groups, networks, etc. that you develop during your work. Your source data files are copied and stored in a repository. The standard option is for ATLAS.ti to manage the documents for you in its internal database. If you work with larger audio or video files, they can be linked to your project to preserve disk space. All files that you assign to the project (except those externally linked) are copied, i.e., a duplicate is made for ATLAS.ti's exclusive use. Your original files remain intact and untouched in their original location.
Your source data can consist of text documents (such as interview or focus group transcripts, reports, observational notes); images (photos, screen shots, diagrams),audio recordings (interviews, broadcasts, music), video clips (audiovisual material),PDF files (papers, brochures, reports, articles or book chapters for a literature review), geo data (locative data using Open Street Map), and tweets from a twitter query.
Once your various documents are added or linked to an ATLAS.ti project, your real work can begin. Most commonly, early project stages involve coding different data sources.
Selecting interesting segments in your data and coding them is the basic activity you engage in when using ATLAS.ti, and it is the basis of everything else you will do. In practical terms, coding refers to the process of assigning codes to segments of information that are of interest to your research objectives. We have modeled this function to correspond with the time-honored practice of marking (underlining or highlighting) and annotating text passages in a book or other documents.
In its central conceptual underpinnings, ATLAS.ti has drawn deliberately from what might be called the paper and pencil paradigm. The user interface is designed accordingly, and many of its processes are based on - and thus can be better understood by - this analogy.
Because of this highly intuitive design principle, you will quickly come to appreciate the margin area as one of your most central and preferred work space - even though ATLAS.ti almost always offers a variety of ways to accomplish any given task.
The following sequence of steps is, of course, not mandatory, but describes a common script:
Create a project, an idea container, meant to enclose your data, all your findings, codes, memos, and structures under a single name. See Creating a New Project.
Next, add documents, text, graphic, audio and video files, or geo documents to your ATLAS.ti project. See Adding Documents.
Organize your documents. See Working With Groups.
Read and select text passages or identify areas in an image or select segments on the time line of an audio or video file that are of further interest, assign key words (codes), and write comments and memos that contain your thinking about the data. Build a coding system. See Working With Comments And Memos and Working With Codes.
Compare data segments based on the codes you have assigned; possibly add more data files to the project. See for example Retrieving Coded Data.
Query the data based on your research questions utilizing the different tools ATLAS.ti provides. The key words to look for are: simple retrieval, complex code retrievals using the Query Tool, simple or complex retrievals in combination with variables via the scope button, applying global filters, the Code Co-occurrence Tools (tree explorer and table), the Code Document Table, data export for further statistical analysis (see Querying Data and Data Export For Further Statistical Analysis.
Conceptualize your data further by building networks from the codes and other entities you have created. These networks, together with your codes and memos, form the framework for emerging theory. See Working With Networks.
Finally, compile a written report based on the memos you have written throughout the various phases of your project and the networks you have created. See Working With Comments And Memos and Exporting Networks.