Best Practice Article: Conducting teamwork during social distancing with ATLAS.ti Cloud
Written by: Dr. Neringa Kalpokaite & Ivana Radivojevic
The COVID-19 situation has brought about unprecedented challenges in continuing regular work, studies, and research. While technology has been essential for keeping us connected, adapting to social distancing can be a bumpy road for teams. In this best practice article, we share some tips for collaborative research projects in the hope of facilitating researchers’ work across the globe during these difficult times.
ATLAS.ti Cloud is the fully web-based version of the powerful qualitative data analysis software, and one of the greatest advantages of using ATLAS.ti Cloud is the possibility to collaborate with others in real time. You can create your research project and invite as many people as you would like. Each person can work on the project from their own ATLAS.ti Cloud account, and the project will be automatically saved and updated across everyone’s accounts. In other words, you never need to worry about missing anyone’s contributions or changes to the project. Getting access to ATLAS.ti Cloud is as simple as entering your email address, and everyone can use it for free while ATLAS.ti Cloud is in its beta version. This makes ATLAS.ti Cloud an ideal tool during these difficult times, for both teams and classes!
Setting up a project to collaborate in real time with others
Once you have created a project in ATLAS.ti Cloud, you can invite your teammates by clicking on the “Add new project member” button. You will find this option in the project settings page (see Figure 1), as well as at the top of any document you have opened (see Figure 2).
Figure 1. Inviting team members from the project settings page
Figure 2. Inviting team members from an opened document
Once you have sent invitations to others, you will be able to see the status of each invitation in the project settings page (see Figure 3). Thus, you can see who has accepted your invitation, whose invitation is still pending, and you can easily resend invitations (if someone cannot find their invitation email, it is worth checking the spam/junk inbox, just in case the email ends up there!).
Figure 3. Viewing the status of sent invitations for collaboration
Once a collaboration invitation has been accepted, that person will be able to see the project from the home page of their ATLAS.ti Cloud account. Now, two sections will appear, one with “Your projects” and another with “Shared with me”. Thus, anyone who has accepted a collaboration invitation will be able to access the project from the section “Shared with me” (see Figure 4). Once inside the project, they can see who is on their team in the settings of that project (see Figure 5).
Figure 4. Accessing the team’s project
Figure 5. Viewing team members and roles from the project settings page
As you add collaborators to your project, you may wonder, do we all have the same roles or rights in this project? Well, although each team member can work on analyzing the data, the role of the project creator remains clearly distinguished, and this is the only person who can delete the project or add additional collaborators. Even if a team member leaves the project, the work they did will remain in the project. Table 1 provides a summary of the roles and rights for teamwork in ATLAS.ti Cloud.
Table 1. Collaborates roles and rights in ATLAS.ti Cloud
|Roles||Data analysis tasks||Project management tasks|
|Project creator||Can engage in all analysis-related tasks: adding and editing documents, creating and coding quotations, writing comments, writing memos, creating groups, downloading reports||Can export (a copy of) the project, can invite additional collaborators, can remove current collaborators, can delete project|
|Team members||Can engage in all analysis-related tasks: adding documents, editing documents, creating and coding quotations, writing comments, writing memos, creating groups, downloading reports||Can export (a copy of) the project, can leave project|
Now that you have your project set up, how might you take advantage of ATLAS.ti Cloud to facilitate collaboration in these times of social distancing?
Communication is key
You can analyze your qualitative data in ATLAS.ti by highlighting segments of text and attaching codes. If you want to see more information on how to carry out analysis in ATLAS.ti Cloud, please feel free to explore our help center. ATLAS.ti Cloud keeps track of who did what – by hovering your mouse over any object, you will be able to see who created it (see Figure 6).
Figure 6. Viewing each person’s codings
While figuring out how to code data may be relatively straightforward, maintaining clear communication with your team can be challenging. How can team members exchange ideas and suggestions? We wish to highlight two (perhaps underestimated) features of ATLAS.ti projects: the comment spaces and memos.
Every individual object in ATLAS.ti has its own comment space. In other words, every single quotation, code, document, and memo has its own comment space. We can thus use comments to write additional information about any specific object. Table 2 provides some suggestions for what kind of information might be helpful to write in these comment spaces (but remember, the power of ATLAS.ti lies in its flexibility, so you can certainly make use of the comment spaces to jot down the kind of information that is going to be helpful for you and answering your research questions!).
Table 2. Some suggestions for what kind of information may be written in comment spaces
|Write the research question(s) and objective(s) for the project|
|Document comments||Write where/how the data was collected (e.g., in the case of interviews), or write the full reference (e.g., in the case of secondary data)|
|Code comments||Write the operational definition of each code (i.e., what exactly that code refers to and how this can be identified in the data)|
|Memo comments||Write the purpose or type of each memo (e.g., to distinguish between analytic memos, methodological memos, etc.)|
|Quotation comments||Write notes, ideas, and reflections regarding each specific data segment|
When you have multiple people working in the same project, these comment spaces can be incredibly helpful for organizing and exchanging ideas. On the one hand, describing the research question(s) and objective(s) is important to make sure everyone understands what the overarching goals of the project are. Moreover, establishing a clear operational definition for each code is essential to ensuring consistent coding; in other words, each team member should fully understand the meaning of each code and how to know when to attach a given code to a piece of data.
In addition to facilitating understanding of the different parts of the project, comment spaces can be used to organize and exchange ideas among team members. For example, you may want to note down who should be focusing on which document by writing team members’ names in document comments. You and your team may also agree to always write a brief reflection on each quotation (e.g., why did this segment of data capture your attention? Why did you attach the code(s)?), and if any doubts come up, the person can write their questions in the quotation comment so that the team can later talk about it (see Figure 7 for an example). You and your team may agree to write your initials to easily keep track of who is saying what when you have multiple people writing in the same comment space.
Figure 7. Exchanging ideas on specific data segments via quotation comments
While the comment spaces are great for describing the different parts of the project and jotting down ideas in the moment, memos provide a dedicated space for writing down more extensive notes and analyses. For example, you may create a memo for each main research objective or concept, and each person can continue adding their ideas, reflections, and analyses. Or, you may prefer to have each team member keep their own memo where they first write their analytic ideas, and you can later read through everyone’s memos and synthesize everyone’s insights. You can create as many memos as you want, so you can certainly take advantage of memos to facilitate deeper analyses of the data as well as already start elaborating rough drafts of the final write-up.
When it comes to working with others, you could even create a “bulletin board” memo where team members can leave messages for one another (see Figure 8 for an example). This kind of memo could also specify who is working on what as well as the deadlines for each part. Communication is key for coordinated teamwork, and memos can make exchanging messages and ideas especially easy for teams. As you start creating many memos (e.g., you have analytic memos and teamwork memos, or each team member is creating their own memos, etc.), it may be particularly helpful to organize the memos into groups (you can see our article on creating groups in ATLAS.ti Cloud for more detailed information).
Figure 8. Example of a “bulletin board” memo for exchanging messages among team members
Collaborating with others while at a physical distance can certainly be challenging. Fortunately, technology helps a great deal as we can still work with others as long as we have an internet connection. With this best practice article, we wanted to share some advice for how you and your team can take advantage of ATLAS.ti Cloud to continue conducting research with your team despite the challenges of working at a distance. With live collaboration that automatically save and updates everyone’s work, simultaneously analyzing qualitative data with others is easier than ever. These teamwork features of ATLAS.ti Cloud can be used for research groups analyzing data as well as students and teachers who are engaging in qualitative research. Teachers can create projects and invite their students to make learning about qualitative research more communal and interactive. We hope this article helps give some ideas for how you can take advantage of ATLAS.ti Cloud in creative ways to make your life as a researcher, professor, or student easier.
Kalpokaite, N., & Radivojevic, I. (2020). Best Practice Article: Conducting teamwork during social distancing with ATLAS.ti Cloud. Retrieved from https://atlasti.com/2020/05/12/best-practice-article-conducting-teamwork-during-social-distancing-with-atlas-ti-cloud/
About the authors:
Dr. Neringa Kalpokaite has dedicated her professional career to qualitative methodology. From her doctoral thesis for which she received the cum laude award in the Complutense University of Madrid to working as a visiting researcher at Harvard University, all of her research projects have been qualitative and carried out with ATLAS.ti. During her 15 years of professional work, she has published numerous articles in a variety of high-impact journals, she has given over 450 trainings, and she has helped over 8,500 people carry out qualitative research. In addition to leading the Europe Team of ATLAS.ti and being the CEO of NkQualitas, she is also a member of the Editorial Advisory Board of the Journal of New Approaches in Educational Research and a professor at the international IE University. Following students’ demand for more rigorous training in qualitative research, she pioneered and taught the qualitative research and ATLAS.ti course at IE University. She continually participates in international conferences to continue sharing knowledge, and she is part of a team of reviewers of articles from high-impact journals. She has repeatedly received awards for excellent teaching in qualitative research. She has also received several research grants from the Ministry of Foreign Affairs and International Cooperation, the Government of Lithuania, and Harvard University. Her latest publications include “Demystifying Qualitative Data Analysis for Novice Qualitative Researchers“, “Teaching qualitative data analysis software online: A comparison of face-to-face and e-learning ATLAS.ti courses“, and “Leading a successful transition to democracy: A qualitative analysis of political leadership in Spain and Lithuania“.
Ivana Radivojevic, a former student of Dr. Neringa Kalpokaite’s Qualitative Research course, is passionate about qualitative research and ATLAS.ti. After finishing her training, she was invited to join Neringa’s NkQualitas team and has been participating in numerous qualitative research projects since 2015, resulting in multiple publications in high-impact journals. She is currently the Project Coordinator of ATLAS.ti and is a Senior Professional Trainer. She has given numerous courses, including over 250 webinars, and she has helped over 3,000 people learn to use ATLAS.ti and conduct qualitative research. She continually participates in international conferences to learn and share knowledge with the scientific community. Her latest publications include “Demystifying Qualitative Data Analysis for Novice Qualitative Researchers“, “Teaching qualitative data analysis software online: A comparison of face-to-face and e-learning ATLAS.ti courses“, and “Leading a successful transition to democracy: A qualitative analysis of political leadership in Spain and Lithuania“.