{"id":13685,"date":"2026-07-30T09:03:44","date_gmt":"2026-07-30T07:03:44","guid":{"rendered":"https:\/\/www.uni.lu\/c2dh-en\/?post_type=news&p=13685"},"modified":"2026-07-30T09:04:23","modified_gmt":"2026-07-30T07:04:23","slug":"cfp-revisiting-metadata","status":"publish","type":"news","link":"https:\/\/www.uni.lu\/c2dh-en\/news\/cfp-revisiting-metadata\/","title":{"rendered":"CfP: Revisiting Metadata. Standardisation, Trust and Power"},"content":{"rendered":"\n
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\nConference on 27-29 January 2027 at the 8xav福利导航 Of Luxembourg, Belval Campus<\/h3>\n\n\n\n

This conference presents the way we design, govern, and disclose metadata as directly entangled with questions of public trust, pluralism, authority and the possibility of informed democratic deliberation. We debate how rich and transparent metadata about provenance, verification status, editorial interventions, and funding can support more diversified databases as well as democratic resilience by enabling the accountability and traceability of information flows. The Call for Papers invites contributions that examine, contest, or re\u2011imagine metadata practices in light of tensions between standardization, trust and power.<\/p>\n\n\n\n

Metadata:<\/strong> Metadata is the structured information that turns raw files and data into manageable, searchable, and sharable resources within digital workflows. It drives automation and decision\u2011making at the stages of creation, ingestion, processing, discovery, access control, and long\u2011term preservation. By encoding context, relationships, and rights, metadata enables interoperability between systems and ensures that digital materials can be reliably found, interpreted, and reused over time. Metadata is a human, interpretive activity imposing standards on data that inevitably encode particular worldviews, power relations, and assumptions about what counts.<\/p>\n\n\n\n

Metadata standards emerged as libraries, archives, and information scientists sought shared schemas (such as MARC in the 1960s and Dublin Core in the mid\u20111990s) to describe resources consistently across institutions and, later, across the web. Over time, these core schemas were joined by a proliferation of domain\u2011specific standards and application profiles (for audiovisual media, research data, cultural heritage, etc.), reflecting both technological change and the growing need for interoperability between heterogeneous digital systems.<\/p>\n\n\n\n

Feminist, Decolonial and Indigenous Perspectives: <\/strong>Established metadata standards have been critiqued from feminist, decolonial and Indigenous perspectives for their embedded assumptions about people, place, and authority. It has been argued that standard vocabularies and structures often cannot express local epistemologies, relational concepts of land, kinship, trauma, or testimony. The tension is that FAIR principles prioritise making data maximally open and reusable for technical and scientific efficiency, while CARE foregrounds community rights, control, and ethical use, which sometimes requires limits on access and reuse that directly constrain FAIR-style openness. Many (oral) history and community archive projects have developed project\u2011 or community\u2011specific extensions and application profiles\u2014adding new fields, vocabularies, and ethical metadata to articulate e.g., the harms of war and displacement more adequately. Other initiatives offer alternative cataloguing traditions in their own right, e.g., stressing Indigenous data sovereignty.<\/p>\n\n\n\n

\u201cSoft Censorship\u201d and Agenda-Setting: <\/strong>Most recently, metadata has become a key battleground in contemporary wars as well as political threats to democracy because metadata can be deliberately manipulated, for example through mislabeling. As a result, it can help disinformation appear more credible than verified information. Platform\u2011controlled relevance signals and opaque taxonomies can effectively turn metadata into an instrument of \u201csoft censorship\u201d and agenda\u2011setting, where some voices and narratives are amplified while others are quietly buried. The way metadata is defined, governed, and exposed is also a central element of concern as Artificial Intelligence is increasingly integrated in professional practices. Machine-automated metadata standardization risks misclassifying content and the reproduction of inequalities included in classification languages of the past. This is increasingly important to highlight, given that the training data on which models are built can further entrench metadata biases and soft power through labels and classifications that are applied automatically and, at times, uncritically. This also raises pressing legal and regulatory questions, from GDPR and the EU AI Act’s data-governance requirements to the copyright and IP status of the training data and metadata themselves.<\/p>\n\n\n\n

\nThematic Scope and Invited Submissions<\/h4>\n\n\n\n

<\/strong>Papers may address empirical case-studies or critical evaluations of the underlying visions, practices and contemporary use, adaptation or refusal of metadata standards from the perspective of:<\/p>\n\n\n\n