Short Abstract

The panel critically examines promises/tensions of open science in anthropology, addresses ethical and political dilemmas in data management and open access, the role of AI in handling ethnographic data, and encourages reflection on how openness can enable more responsible knowledge practices.

Long Abstract

In times of growing social and political polarisation, calls from various quarters for open, transparent, and accessible research are growing louder. “Open Science” promises to share knowledge democratically, promote scientific collaboration, and make research results accessible to a wider audience. But what can “openness” mean in the context of anthropological research, which deals with sensitive data, relational knowledge, and asymmetrical power relations?

This panel invites critical reflections on the possibilities and tensions of open science within anthropology. We want to explore the ethical, epistemological, and political implications of open research practices: How can open access and research data management be balanced with obligations of confidentiality, anonymity, and accountability to research partners? Who can actually gain access? What role do colonial histories and knowledge regimes play in shaping the discussion of openness, and how could concepts such as the CARE Principles for Indigenous Data Governance (Collective Benefit, Authority to Control, Responsibility, Ethics) provide guidance here?

At the same time, new digital infrastructures and AI-based tools can change the way how ethnographic data, texts, and images are stored, analyzed, and shared. These technologies raise old questions about data sovereignty, bias, authorship, and consent in new ways.

We invite colleagues to contribute theoretical reflections, methodological discussions, or empirical case studies that shed light on the ambivalences, challenges, and potentials of open science from an anthropological perspective. The aim is to create a space for an reflexive dialogue on how openness can go beyond reproducing inequalities to foster more equitable and responsible forms of knowledge production—especially in a polarized world.

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