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Show and Tell Recap: OpenQDA – A Sustainable and Open Research Software for Collaborative Qualitative Data Analysis

Methods Lab

On November 18, 2024, Karsten Wolf and Florian Hohmann from the University of Bremen presented the software OpenQDA at WI. In this Show and Tell, they gave an overview of OpenQDA and its motivations, functions, and limitations.

In the first part of the Show and Tell, Karsten Wolf presented the development and purpose of the software. It is an open-source alternative to the commercial software MaxQDA, which is a popular tool for text annotation (i.e., coding) in qualitative research. The team at the University of Bremen had been working on OpenQDA for quite some time to not only deliver a free and customizable alternative to MaxQDA, but also allow for (simultaneous) collaboration on projects. In addition, OpenQDA has a plug-in framework that will be expanded over time. For example, atrain is already supported and can be used to transcribe audio files to text, and a plug-in that allows for implementing Python scripts is currently in the works. While OpenQDA is still under development and currently in early-access, the first official release is planned for the near future. It runs on servers at the Unversity of Bremen and can be used by anyone for free.

Florian Hohmann presents features and the GitHub repository of OpenQDA

In the second part of the Show and Tell, Florian Hohmann gave a practical introduction to the most recent version of the software. He showed participants how to create an account, set up a new project, and create a team to work on projects collaboratively. Text content can be added manually, from documents, audio files, and soon even remote sources. These texts can then be annotated/coded using separate, color-coded categories, and it is possible to set up sub-categories for further refinement. The results can be exported in CSV format. In addition, users can create a code portrait, which illustrates the distribution of categories across the text, and a word cloud for quick visual analysis.

At the end of the Show and Tell, participants provided feedback and suggestions for future implementation. For example, the automated conversion of scanned documents to plain text using OCR, and functions like counting and automatic coding, were discussed. Some participants were willing to stay and provide further feedback even after the main event ended. Finally, the team from Bremen, the Methods Lab, and the Weizenbaum Institute IT department discussed the installation of OpenQDA on the Institute’s servers in 2025 to provide a local instance to Weizenbaum Institute researchers.

The Methods Lab would like to thank the colleagues from Bremen for their work, and all participants for providing useful feedback!

Workshop Recap: Research in Practice – Attending to Algorithms in and Around Organizations

Katharina Berr, Jana Pannier

On November 26 2024, Maximilian Heimstädt, Professor of Digital Governance & Service Design at the Helmut Schmidt University in Hamburg, shared his experiences and expertise in applying qualitative methods to studying algorithms in organizations. This workshop was co-organized by the Methods Lab and the Research in Practice – PhD Network for Qualitative Research, coordinated by Katharina Berr and Jana Pannier.

The workshop focused on the complexities of studying algorithms from an interpretivist social science perspective; not only the potentials and risks people ascribe to them, but how they are made sense of, enacted, negotiated and integrated into everyday work settings. Drawing on joint research with Simon Egbert on predictive policing, Max shared how he gained access to public sector organizations, approached team-based multi-sited ethnographic fieldwork and learned to understand complex technologies developed and implemented across different empirical sites and over time.

Maximilian Heimstädt presents theoretical approaches to research algorithms in practice

Max introduced three central theoretical approaches from organization studies and critical data studies to research algorithms in practice: technology trajectories, biographies of algorithms,and data journeys that all afford different analytical lenses and offer more nuanced understandings of algorithmic systems. The approach of technology trajectories expands research of the design and use of technologies by integrating broader questions of power, ideology, and institutional change (Bailey & Barley, 2020). Approaching digitalization research from a biographies approach draws attention to the dynamic development of digital technologies, understood as ‘entangled, relational, emergent, and nested assemblages’ across different organizational contexts and time (Glaser, Pollock, & D’Adderio, 2021). Finally, the data journeys approach allows to ‘focus attention on the life of data as they move through space and time, through different sites and cultures of data practice’, and offers a perspective that is attentive to frictions of such data journeys (Bates, Lin, & Goodale, 2016). Based on an introduction of these approaches, the workshop participants explored how their own research has been (both implicitly and explicitly) informed by these approaches, and discussed their practical and epistemic potentials and limits.

The Idea Behind the ‘Research in Practice’ Workshop Series

Qualitative research often feels polished in academic publications, but the reality is that the process can be tedious at times, and full of twists and turns. We have created this workshop series to center the ‘backstage’ of qualitative research. The goal is to hear directly from scholars about how they conduct their work – the challenges, the unexpected discoveries and unplanned adaptations, the specific methods and digital tools used, and the strategies that help them arrive at interesting and valuable findings. With this workshop format and research network, we aim to create a space for qualitative researchers within and beyond the Weizenbaum Institute to connect, collaborate, and learn from one another.

What to Expect

Each workshop session in the series brings a new perspective on qualitative (digital) research. Invited scholars walk us through their research processes, focusing on how they have handled the challenges of their work. This includes designing studies, building rapport with research participants, analyzing different kinds of qualitative data, theorizing as method, and navigating ethical considerations. The sessions are interactive, offering opportunities to ask questions, share ideas, and discuss in depth. By opening up the processes behind qualitative research, we hope to demystify the work and facilitate conversations that help researchers at all levels.

If you would like to join our network and to be informed about upcoming events, reach out to Katharina Berr and Jana Pannier.

Spotlight: The Data Workers’ Inquiry 

Diana Ignatovich

AI applications are growing in popularity, everyday digital tasks are intuitively streamlined, and social media platforms are flooded with automated media that emulate the clarity of actual events. Naturally, this inspires discussions of future opportunities and concerns, such as the possibility of computers overtaking jobs that once relied upon humans. But amidst this consideration of AI into our routine behaviors, how much do we really know about the foundation of these tools? What are the invisible costs of this innovation, and who bears the consequences? The answer is revealed in this article, unsettling accounts behind the scenes of our usage are presented by the data workers’ inquiry.

This community-based initiative fights for fair working conditions and adequate recognition of data workers’ expertise. Since 2022, workers behind AI applications have been investigating their own workplaces to address labor conditions and build workplace power. Derived from the principles of 1880s Marxist thinking, workers conduct research tailored to their political and environmental concerns, with support from trained qualitative researchers. This team of researchers includes lead researcher Milagros Miceli with the Weizenbaum Institute, Adio Dinika, Krystal Kauffman, Camilla Salim Wagner, and Laurenz Sachenbacher. Without compromising the workers’ epistemic authority, they provide training in methods for data collection and analysis to create a methodology for workers to use within investigations. They also diligently monitor ethical and legal boundaries throughout the duration of projects. 

The inquiries take place across Venezuela, Kenya, Syria and Germany. Whether in essays, artwork or documentaries, data workers creatively share their perspective working under various AI industries. The striking truths are outlined in the inquiries below. Ultimately, this research will provide structure for collective action, establishing future ethical guidelines in regard to the treatment of data workers. 

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Tutorial: When and how to use the official TikTok API

Lion Wedel

This blog post discusses when and when not to use the official TikTokAPI. Additionally, this blog post provides step-by-step instructions for a typical research scenario to inform aspiring researchers about using the API.

When and when not to use it

While being the official way of data access, the official TikTok API is by no means the only way for collecting TikTok data in an automatized fashion. Depending on the research endeavour, one of the other ways might be the way to go:

  1. 4Cat + Zeeschumier: Sensible if you want to collect limited data on one or more actors, hashtags, or keywords and/or are not confident in programming for the subsequent analysis.
  2. An in-official TiKTok API (pyktok or the Unofficial TikTok API in Python): Both are great projects that provide significantly more data points than the official API. However, this comes with costs: stability and dependency on developers reacting to changes on TikTok’s site.

But why should you use the official TikTok API if those two options are available?

  • Reliability. In theory, the official API data access provides more stable access than other solutions.
  • Legality. Depending on your country or home institution, official data access might be a problem for legal reasons. However, you are on the safer side with official data access. Please consult your institution regarding data access.
  • User-level data. Other data collection methods are often superior in terms of data points on the video level (Ruz et al. 2023). However, the official TikTok API offers a set of user-level data (User info, liked videos, pinned videos, followers, following, reposted videos), which is not as conveniently available through other data collection methods.

One fundamental limitation still needs to be kept in mind. One can make only 1,000 daily requests, each containing 100 records (e.g., videos, comments) at most. This means that if one can exploit the complete 100 records per request (rarely possible), one can retrieve a maximum of 100,000 records per day.

To start with the official TikTok research API, visit Research API. To gain access, you need to create a developer account and submit an application form. When doing so, please record your access request under DSA40 Data Access Tracker to contribute to an effort to track the data access platforms provided under DSA40.

The official documentation on research API usage is not intuitive, especially for newcomers (Documentation). Using the API within the typical programming language Python/R might still pose a challenge, especially for researchers who are working with an API for the first time. The currently scarce availability of API guidance motivates this blog post to provide such guidance without a paywall.

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Show and Tell: OpenQDA – A Sustainable and Open Research Software for Collaborative Qualitative Data Analysis

Methods Lab

The Methods Lab is eager to present the upcoming Show and Tell: OpenQDA—A Sustainable and Open Research Software for Collaborative Qualitative Data Analysis, scheduled for Monday, November 18th. This Show and Tell will be directed at the Weizenbaum Institute, but is also available to members joining online.

Florian Hohmann with the ZeMKI research unit at the University of Bremen, will be facilitating the event. This workshop provides a live demonstration and open discussion that introduces researchers to the structure of this web-based, collaborative, and open-source tool on qualitative data analysis. The ZeMKI team will present a thorough guide of instruction for using OpenQDA, as well as the idea’s goals and implications. Following this, all participants are encouraged to ask questions in the allotted Q&A period. The second segment of this workshop will invite on-site participants to engage in a research community session, for an exchange of knowledge that supports the future development of this application. To get a sense of prospective demands, we request that researchers bring the relevant data analysis formats of published works such as tables or visualizations.

To learn more, visit our program page. We are looking forward to your participation!

Special Issue: Open Research Infrastructures and Resources for Communication and Media Studies

Diana Ignatovich

Despite the advantages of accessible and reproducible research practices for scholars in media and communication research, few journals present opportunities to examine these resources. Therefore the journal of Media and Communication plans to publish a Special Issue on “Open Research Infrastructures and Resources for Communication and Media Studies” in 2026 to encourage an exchange of feedback between researchers on the implications of relevant resources and infrastructures. The Call for Papers on this issue invites papers to discuss and pursue resources that adhere to open science principles. The Methods Lab lead, Christian Strippel is a co-editor of this issue. 

In regards to submissions, open science principles emphasize non-commercial tools that may apply to both quantitative and qualitative methods. Articles that present datasets, evaluate research software or compare instruments involved in data analysis are encouraged. The scope also extends to papers discussing developments or challenges to the operation of open research infrastructure, and investigates the potential areas for improvement. Notably, this publication considers implications for researchers of different socioeconomic and cultural backgrounds to address research inequalities and promote sustainability. Thus, papers are encouraged to reflect this dimension of diversity. In conclusion, contributions to this publication equip researchers with greater access and ease of operation to these valuable resources, ultimately advancing and promoting inclusivity within open research practices. 

Submission of Abstracts: 1-15 September 2025

Submission of Full Papers: 15-31 January 2026

Publication of the Issue: July/December 2026

Workshop: Research in Practice – Attending to Algorithms in and around Organizations (November 26, 2024)

Methods Lab

We’re excited to announce our upcoming workshop Research in Practice – Attending to Algorithms in and around Organizations, which will take place on Tuesday, November 26. This workshop will be conducted at the Weizenbaum Institute and is open to Weizenbaum Institute members.

Led by Maximilian Heimstädt, Professor of Digital Governance & Service Design at the Helmut Schmidt University in Hamburg, this workshop sheds light on how to research the role of algorithms for work and workers in and around organizations. As the anthropologist Nick Seaver has aptly put it: “Just as critical scholars picked them up, algorithms seemed to break apart.” The aim of the workshop is to understand the breaking apart of algorithms as an opportunity for creative research questions, designs and methods. In the first part of the workshop, Maximilian presents different ways in which algorithms in organizations lend themselves to study. In the second part, participants are invited to present their own research projects and ideas, and to discuss methodological challenges with the group.

The workshop is co-organized by the Methods Lab and the Research in Practice – PhD Network for Qualitative Research, coordinated by Katharina Berr and Jana Pannier.

For further details, visit our program page. We are looking forward to your participation!

New preprint article: Extracting smartphone use from Android event log data

Diana Ignatovich

With smartphones now more prevalent in everyday life than ever before, understanding their use and its implications becomes increasingly necessary. While self-reporting in surveys is the method typically used to assess smartphone use, it is affected by various problems such as distorted retrospection, social desirability bias, and high aggregation. More advanced methods include the Experience Sampling Method (ESM), which presents multiple short surveys per day to limit the degree of retrospection, and logging (Android only), which accesses an internal log on the device itself that documents each user activity in extremely high resolution. Although the latter is the most precise and objective method available for assessing smartphone use, the raw data received from the log file requires extensive transformation to extract actual human behavior rather than technical artifacts. Still, this transformation was never documented systematically and researchers working with this input implemented arbitrary steps to extract the data they required. 

The preprint article Extracting Meaningful Measures of Smartphone Usage from Android Event Log Data: A Methodological Primer, authored by former Methods Lab fellow Douglas Parry and Methods Lab member Roland Toth, aims to provide a detailed step-by-step guide to extracting different levels of smartphone use from Android log data. Specifically, the guide helps identify glances (short checks without unlocking the device), sessions (uses from unlocking to locking), and episodes (single app uses) from such log files, allowing for further investigation. All steps are presented as pseudo-code as well as described in text. In addition, the Online Supplementary Material (OSM) contains the full pseudo-code, a rendition in the R programming language, a sample data set containing raw log data, and more helpful material.

This guide ultimately enhances our understanding of how humans interact with these versatile devices, particularly beneficial for projects within the social sciences and neighboring disciplines. While survey methods are recognized for their economical advantages and ease of administration, access to objective high-resolution data contributes a more refined perspective. We hope this article helps researchers identify valuable measures from raw android event log data, thereby making this rich data source more accessible and manageable than it has previously been. 

Workshop Recap: Open Research – Principles, Practices, and Implementation

Roland Toth

On September 3 2024, Tobias Dienlin from the University of Vienna held the workshop Open Research – Principles, Practices, and Implementation at WI. In this workshop, he gave an overview of Open Research and its motivations, relevance, and formal and technical implementation.

In the first part of the workshop, Tobias argued that certain problems and values in science are the main reasons why researchers should practice Open Research. The problems included the replication crisis (a lack of or low quality of replication studies, especially in the social sciences), questionable research practices (p-hacking, HARKing, errors), and publication bias (journals prefer exciting, expected, and significant results). The values in question included openness as a foundation of science itself and the dedication to scientific advancement instead of emphasizing individuals that achieve it.

Tobias welcomes the participants to the workshop

In the second part, the formal practices of Open Research were discussed. Tobias first clarified the differences between the terms Open Science, Open Research, and Open Scholarship. To achieve a culture of Open Research, he suggested aiming for open access, pre-/post-printing, open reviews, author contribution statements, open teaching, and citizen science. While these practices ususally require additional work, the burden can be lowered by already considering and preparing them in the initial stages of a research project. For instance, by implementing two of the most important Open Research practices: Preregistrations and registered reports.

  • In a preregistration, any details of a study that are already fixed (e.g., theoretical foundation, research questions, hypotheses, analysis methods, …) are published before conducting the study itself. After conducting the study, the preregistration is referred to in the manuscript, and possible deviations from it are explained. This procedure reduces the possibility and risk of p-hacking and HARKing, and under specific circumstances a preregistration can even take place after the data have already been collected.
  • A registered report is a more elaborate version of a preregistration. It consists of all parts of a submission that do not involve the analysis and the results. The submission can therefore be reviewed before the data and results even exist. This way, reviewers are not influenced by results and publication bias can be avoided. While a preregistration can be published anywhere, the registered report format needs to be offered by the journal itself.
Participation was enable in-person as well as online

In the last part of the workshop, the focus was on tools and software that help implement Open Research practices. For example, the free-to-use repository OSF can be used for pre-/post-prints, preregistrations, and online supplementary materials such as data, analysis code, or questionnaires. As an exercise, Tobias gave participants the opportunity to implement a basic preregistration or registered report on OSF for a research project they were working on already and try different features, such as linking it to a repository on GitHub. After summarizing the insights of the workshop, Tobias concluded by showing a fitting statement:

Open Science: Just Science Done Right.

During the workshop, participants had plenty of space to ask questions, discuss with everyone or in separate breakout rooms, and interact in various ways. We would like to thank Tobias for this insightful workshop and strongly encourage the implementation of Open Research.

Workshop: Open Research – Principles, Practices, and Implementation (September 3, 2024)

Methods Lab

We’re excited to announce our upcoming workshop Open Research – Principles, Practices, and Implementation, which will take place on Tuesday, September 3. This workshop will be conducted both at the Weizenbaum Institute and online, and is open to Weizenbaum Institute members as well as external participants (and the QPD).

Led by Tobias Dienlin, Assistant Professor of Interactive Communication at the University of Vienna, this workshop will equip participants with skills in open research by covering principles of transparency, reproducibility, the replication crisis, and practical sessions on sharing research materials, data, and analyses. It will also include preregistrations, registered reports, preprints, postprints, TOP Guidelines, and initiatives like DORA, CORA, and RESQUE. Participants will engage in drafting preregistration plans and discussing the incentives and challenges of open research, aiming to integrate these practices into their work for a more transparent and robust research community.

For further details, visit our program page. We are looking forward to your participation!