Call for Resources (Data/Software)

JCDL 2026 invites submissions to a dedicated Resources Track, focused on publicly available datasets, software tools, benchmarks, and other research artifacts that advance the field of digital libraries. This track highlights the importance of open, reusable resources that contribute to transparent, reproducible, and impactful research.

Important Dates

All deadlines are Anywhere on Earth (AoE) time.

Scope and Topics

We welcome resource submissions that facilitate new research and advance the state-of-the-art in managing, accessing, analyzing, and curating digital collections. Suitable submissions include, but are not limited to:

• Novel datasets, corpora, test collections, or protocols, particularly those created using innovative annotation methods, crowdsourcing strategies, or new collection pipelines
• Open-source software, tools, APIs, and libraries that support computing, analysis, evaluation, visualization, or exploration in digital libraries, information retrieval, and data science
• Benchmarks and evaluation platforms that enable reproducible and comparative studies for core tasks such as search, classification, recommendation, or metadata enrichment
• Reusable research pipelines and workflows, including those for data cleaning, integration, or transformation
• Frameworks and services that support application development in areas such as machine learning, digital preservation, document understanding, or knowledge extraction
• Cross-disciplinary resources that bridge digital libraries with fields such as computational social science, digital humanities, AI4Science, etc.

All submissions must describe how the resource will be accessed and reused. Authors are encouraged to align their dataset submissions with the FAIR principles (Findable, Accessible, Interoperable, Reusable) [1], and where appropriate, provide structured documentation following the Datasheets for Datasets model [2].

Awards

Outstanding contributions will be considered for the Best Resource Award, announced during the closing session of the conference.

Submission Guidelines

Submissions should be 2–4 pages in length, excluding references, and must adhere to the following guidelines:

• All submissions must be written in English, submitted in PDF format, and prepared in the current ACM two-column conference format. Suitable LaTeX, Word, and Overleaf templates are available from the ACM Website: ACM Proceedings Template. Authors using LaTeX should use the sigconf proceedings template, while Word authors should use the Interim Template.

Review Model

This track uses a single-blind review process. Author names and affiliations should be included in the submitted manuscript. Reviewers will evaluate submissions based on their technical quality, clarity, accessibility, and potential impact on the community.

Public Availability

Submitted resources must be publicly accessible at the time of submission via a stable repository (e.g., GitHub, Zenodo, institutional repository), and must include appropriate open licensing and clear documentation. Resources must be accessible without requiring reviewers to identify themselves.

Content Requirements

Submissions should describe the motivation, design, structure, intended usage, target users, and impact of the resource. A usage example or integration scenario is encouraged.

Supplementary Materials

Authors are encouraged to include links to supplementary materials such as source code, datasets, demonstration videos, and documentation hosted on public platforms (e.g., GitHub, Zenodo). While reviewers are not required to review supplementary content, it may support evaluation.

Ethics

If the resource involves human participants or sensitive data, submissions must include details on ethics approvals (e.g., IRB) and comply with applicable ACM ethical standards.

Resource Review Criteria

Proceedings and Presentation

Accepted papers will be included in the official conference proceedings.

• Each accepted paper must be covered by a distinct conference registration by the deadline.
• Authors are required to present their work during their scheduled session.

Policies

ACM Publications Policy

By submitting an article to an ACM publication, authors acknowledge that they and their co-authors are subject to applicable ACM Publications Policies, including ACM’s Publications Policy on Research Involving Human Participants and Subjects.

Generative AI Policy

All submissions must comply with applicable ACM and conference policies regarding the use of generative AI tools. Any AI-assisted writing or AI-generated content should be disclosed in accordance with the final publication requirements of the venue.

Authorship Policy

JCDL 2026 follows the ACM Authorship Policy. Every listed author must have made a substantial contribution. The complete author list must be finalized by the submission deadline — no additions, removals, or reordering will be allowed after submission.

Desk Rejection Policy

Submissions failing to adhere to length or formatting requirements, or violating academic integrity standards, may be desk-rejected. Submissions that do not provide reviewers with access to the described resource (e.g., due to broken links or restricted access) will be desk-rejected without review. See the ACM Policy on Plagiarism, Misrepresentation, and Falsification.

ORCID Requirement

Please ensure that all authors obtain an ORCID ID so the publishing process can be completed for accepted submissions. For background, see ACM’s ORCID FAQs.

Ethics and Conduct

Research Ethics

Authors must comply with the ACM Code of Ethics and Professional Conduct. Submissions involving human participants must include a statement on ethics approval (e.g., IRB), informed consent, and relevant safeguards.

Conflict of Interest

All authors, reviewers, and committee members must adhere to the ACM Conflict of Interest Policy. Conflicts must be declared during submission and review.

Harassment Policy

All participants must adhere to the ACM Policy Against Harassment.

Resources Chairs

References

1. Wilkinson, M.D., et al. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 3, 160018.
2. Gebru, Timnit, et al. “Datasheets for datasets.” Communications of the ACM 64.12 (2021): 86–92.