Call for Resource Papers

Resources and datasets are crucial for the advancement of Information Retrieval and related fields. High-quality resources, including training and evaluation datasets and software tools, are essential for enabling, supporting, and accelerating top-level research.

To highlight and encourage the creation and sharing of different types of resources, ECIR 2027 features a dedicated Resource Track. This track welcomes papers that introduce novel resources, improve the quality or usability of existing resources, or provide tools that facilitate experimentation, benchmarking, and reproducibility in Information Retrieval, Information Access, Recommendation Systems and related areas.

Topics of Interest

We welcome submissions on any topic relevant to the general field of Information Retrieval, including those mentioned in the Call for Full Papers for ECIR 2027.

Resource paper topics may include, but are not limited to:

• Novel training datasets and test collections, or extensions of existing collections with additional labeled annotations
• Software tools and frameworks that support experimentation, evaluation, visualization, benchmarking, reproducibility, or resource management
• Repositories of data or code, including extensions or integrations with existing platforms, to support benchmarking and analysis
• Novel protocols, annotation guidelines, or documentation that facilitate resource creation, sharing, and use

Submissions should clearly describe the motivation, design, development, and intended use of the resource. Authors are encouraged to discuss availability, licensing, maintenance plans, and potential limitations to ensure transparency and foster reuse by the community.

Review Criteria

All resource-track papers will be evaluated along the following criteria (when applicable):

Novelty

• Does the resource represent a contribution to the community?
• Does the resource address limitations of existing resources (e.g., size, coverage, quality, bias, domain specificity)?
• Does the resource enable new types of experiments, tasks, or evaluation methodologies that were not possible before?

Availability

• Is the resource available to the reviewers at the time of review?
• Is the resource released in a permanent repository for easy access by researchers?
• Are the licensing and terms of use sufficiently open to allow most academic and industry researchers to access and use the resource?

Reliability and Utility

• Is the resource well documented, with all the details required for other researchers to use and understand the resource?
• Are tutorials, examples, or demonstrations provided, and do they reflect realistic usage scenarios?
• Are there discrepancies between what is described in the paper and what is actually available?
• If the resource is data, are appropriate tools provided for loading and processing the data?
• If the resource is data, are the preparation stages (e.g., source, preprocessing, cleaning, aggregation) clearly documented?
• If the resource is data collected from people, have appropriate human subjects/ethics procedures been followed and documented?

Impact

• What research activities are enabled or significantly advanced by the availability of this resource?
• Does the resource support a well-established area of IR research, or does it open opportunities in a new direction?
• Is the resource expected to remain useful over time? If updates or curation are required, is there a plan for maintenance?
• How large is the anticipated research user community?

Submission Guidelines

• Resource papers can be up to 12 pages in length plus additional pages for references. Appendices count toward the page limit.
• Resource papers will be refereed through single-blind peer review (submissions are not anonymous) so that reviewers can access and evaluate shared resources that cannot be anonymized.
• Authors are strongly encouraged to: (1) provide a permanent URL or repository where the resource can be accessed, (2) make accompanying code or tools freely available whenever possible, and (3) include documentation, tutorials, or usage examples to facilitate adoption by the community.
• Authors are strongly encouraged to address fairness considerations, including potential biases in data, annotations, or tool behavior, and describe mitigation strategies where relevant.

Authors should consult Springer's author guidelines and use their proceedings templates, either for LaTeX or Word for the preparation of their papers. The templates are available at https://bit.ly/springer-guidelines. Springer encourages authors to include ORCIDs in their papers (https://www.springer.com/gp/authors-editors/orcid).

All submissions must be written in English. All papers should be submitted electronically through the EasyChair submission system: here.

In addition, the corresponding author of each accepted paper, acting on behalf of all of the authors of that paper, must complete and sign a Consent-to-Publish form. The corresponding author signing the copyright form should match the corresponding author marked on the paper. Once the paper has been submitted, changes relating to its authorship cannot be made.

Accepted papers will be published in the conference proceedings in the Springer Lecture Notes in Computer Science series. The proceedings will be distributed to all delegates at the conference. Accepted papers will have to be presented at the conference by one of the authors in person, and at least one author for each accepted contribution will be required to register and attend.

Dual Submission Policy

Papers submitted to ECIR 2027 should be substantially different from papers that have been previously published, or accepted for publication, or that are under review at other venues. Exceptions to this rule are:

• Submission is permitted for papers presented or to be presented at conferences or workshops without proceedings.
• Submission is permitted for papers that have previously been made available as a technical report (e.g., in institutional archives or preprint archives like arXiv).