Review Assignments for DH2026 Have Been Sent

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We are pleased to announce that review assignments for the Digital Humanities Conference 2026 (DH2026) have been distributed to all reviewers.

Check Your Inbox

If you have registered as a reviewer, you should have received an email with details about your assigned submissions. Please check your inbox, including your spam or junk folder.

Didn’t receive an email? No worries! You can still access your review assignments by logging in to ConfTool directly:

🔗 Access Your Review Assignments

Review Deadline

Please complete all assigned reviews by January 20, 2026. Your timely completion is crucial for keeping the overall conference schedule on track.

Review Criteria and Assessment Categories

Reviews should be conducted in accordance with ADHO’s established review criteria, as outlined in the CFP and related ADHO documentation.

In the submission system, you will see five assessment categories:

• Evaluation (20%) – Does the submission provide a sufficient description of the current state of knowledge and best practices relevant to the work, supported by appropriate references?
• Significance (20%) – Does the work go beyond the current state of knowledge and best practices in its field(s), whether in method, approach, application domain, or findings?
• Methodology (20%) – Does the submission describe its approach or method with enough detail for readers to understand what was done and why, within the limits of the abstract format?
• Diversity (15%) – Does the submission contribute to diversity by expanding the range of topics, approaches, or perspectives represented at the conference, and/or by giving appropriate recognition to a broad range of relevant scholarly work?
• Readability (15%) – Is the submission well structured and clearly written in a way that supports reader comprehension?

Double-Anonymous Review

DH2026 follows the double-anonymous (blind) review principle. Authors’ and reviewers’ identities must not be disclosed, and submissions should be assessed solely on their scholarly merits. Please avoid speculation about authorship and flag any potential identifying information encountered in submissions.

Use of Large Language Models (LLMs)

To protect the confidentiality of the review process, please refrain from entering submission content into any large language model (LLM) or external AI tool. LLMs may be used only for light proofreading or language refinement of your own review texts, on the condition that no data are stored or used for training purposes.

Questions or Conflicts of Interest?

If you need to recuse yourself from any review, please select the “conflict of interest” option in ConfTool, and we will reassign it promptly. For any other questions, feel free to contact us.

Thank you for contributing your time and expertise to DH2026. Your careful and thoughtful reviews play a vital role in shaping a strong and inclusive conference program.

The Program Committee of DH2026 Daejeon

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