Applied Data Science (ADS) Track: Call for Papers

February Cycle
August Cycle

KDD is the premier Data Science conference, hosting both a Research and an Applied Data Science Track. The conference will take place in Toronto, Canada, from Sunday, August 3, 2025 to Thursday, August 7, 2025. It hosts both a Research and an Applied Data Science Track. A paper should either be submitted to the Research Track or the Applied Data Science Track but not both.

KDD has multiple submission cycles per year. KDD 2025 has two cycles, one already complete with submissions due on August 1, 2024 and a second cycle underway with the following important dates.

Important Dates

Abstract Deadline: Feb 3, 2025
Paper Deadline: Feb 10, 2025
Author Rebuttal Period: Apr 4-18, 2025
Notification: May 16, 2024
Camera-ready: TBD

All deadlines are end-of-day in the Anywhere on Earth (AoE) time zone.

Submission Site

We will use OpenReview to manage the submissions and reviewing. Submissions will not be made public on OpenReview during the reviewing period.

All listed authors must have an up-to-date OpenReview profile. Here is information on how to create an OpenReview profile. Note OpenReview’s moderation policy for newly created profiles:

New profiles created without an institutional email will go through a moderation process that can take up to two weeks.
New profiles created with an institutional email will be activated automatically.

The OpenReview profile will be used to handle conflict of interest and paper matching. Incomplete OpenReview profile is sufficient ground for desk rejection.

To be considered complete, each author profile must be properly attributed with the following mandatory fields: current and past institutional affiliation (going back at least 5 years), homepage, DBLP (if there is prior publication), ORCID, Advisors and Recent Publications (if any). In addition, other fields such as Google Scholar, LinkedIn, Semantic Scholar, Advisees and Other Relations should be entered wherever applicable.

Abstracts and papers can be submitted through OpenReview.

Scope

The KDD’25 Applied Data Science (ADS) track solicits submissions of papers describing deployed applications of data mining, data analytics, data science, and applied machine learning. The emphasis is on papers that either solve or advance the understanding of issues related to deploying data science technologies in the real world.

Submissions must include a quantification of the post-launch performance of the described system or solution. Submissions that do not provide this quantification will be desk-rejected without review. This is a strict requirement. However, exceptions may be granted in the following cases:

1. Blocked Deployment Due to Real-World Challenges: Submissions describing systems designed to address real-world problems but blocked from deployment may qualify for an exception. In such cases, the primary contribution should focus on:

Detailed documentation of the deployment attempts.
Key challenges or barriers encountered.
Lessons learned from these failures that are broadly applicable and provide valuable insights for future systems in similar or related domains.

2. Unrealistic Deployment to Live Users: In rare scenarios, deployment to live users may be impractical due to external constraints. Examples include:

Regulatory Requirements: Applications in domains such as healthcare or air traffic management, where strict regulations prevent live deployments.
Infrastructure Limitations: Systems dependent on external factors, such as satellite deployments constrained by launch schedules.

For these cases, we are open to alternative definitions of deployment, such as controlled or limited-scale pilots that provide substantial learning.
These exceptions are intended for unique circumstances and should not be considered the norm. Authors seeking an exception must ensure that their submission highlights the broader implications and community benefits of their work, even in the absence of post-launch performance data.

The following classes of submissions do not meet the criteria for real-world deployment and will be desk-rejected:

Applications that are tested offline on real-world data, but have not been deployed live to users
Applications that are in principle available to users, for instance by deploying source code or executables to a repository, but which do not include a rich quantification of post-launch performance.

Papers should present the problem, its significance to the application domain, the decisions and tradeoffs made when making design choices for the solution, how any challenges in areas like data collection, modeling, and deployment in constrained environments were overcome, and the lessons learned from successes and failures. It is perfectly fine if the underlying machine learning approaches are not fundamentally groundbreaking. However, it must be clear how these machine learning approaches are applied to the problem domain, and deployed in a real-world system.
Papers should be aimed at a broad audience of applied data scientists.

Application areas include but are not limited to the following:

Advertising, Marketing, and E-commerce
Social and professional networks
News Feed, Search and Recommendations
Financial Applications (including fintech, banking, insurance)
Geospatial Applications (including smart cities, transportation, mapping)
Industrial Applications (including medical devices, robotics, sensors)
Scientific Applications (including computational biology, health, environmental science)
Trust and Responsible AI Applications (including policy enforcement, regulatory compliance, ethics, fairness, privacy, and fraud detection)
Resource Allocation Applications (including Cloud, intranet, and other large system allocation optimizations)
Applications of Generative AI (including text, code, and media)

Novelty for an ADS Track submission will not generally depend on novel research contributions, but may instead lie in the choice of application domain, engineering design, usability approach, or business use case.

Submission Guidelines

Deadlines. The submission deadlines are strict and no extensions, regardless of circumstances, will be allowed. Placeholder or dummy abstracts are forbidden.

Authorship. The ACM has an authorship policy stating who can be considered an author in a submission as well as the use of generative AI tools. Every person named as the author of a paper must have contributed substantially to the work described in the paper and/or to the writing of the paper and must take responsibility for the entire content of a paper. Any use of generative AI tools must be disclosed and elaborated in the submission form.

Maximum authorship. In the ADS track, the number of submissions allowed per author is limited to 5 (five) maximum. If more than 5 papers are submitted with the same person listed as an author, the additional papers submitted after the first 5 by submission ID will be desk-rejected.
Authorship changes. The full list of author names, including the ordering, must be finalized by submission deadline. There cannot be any addition, removal, or reordering of authors after the submission deadline. The only changes allowed are the correction of spelling mistakes or new affiliation.

Anonymity. Due to the nature of the Applied Data Science (ADS) track, the review process will be single-blind — author names and affiliations should be listed.

Formatting Requirements. Submissions must be in English, in double-column format, and must adhere to the ACM template and format (also available in Overleaf); Word users may use the Word Interim Template. The recommended setting for LaTeX is:

\documentclass[sigconf,review]{acmart}

Submissions must be a single PDF file: 8 (eight) content pages as main paper, followed by references and an optional Appendix that has no page limits. The Appendix can contain details on reproducibility, proofs, pseudo-code, etc. The first 8 pages should be self-contained, since reviewers are not required to read past that. Note that different limits will apply to camera-ready (see below).

Originality and Concurrent Submissions. Submissions must present original work—this means that papers under review at or published/accepted to any peer-reviewed conference/journal with published proceedings cannot be submitted. Submissions that have been previously presented orally, as posters or abstracts-only, or in non-archival venues with no formal proceedings, including workshops or PhD symposia without proceedings, are allowed. Authors may submit anonymized work that is already available as a preprint (e.g., on arXiv or SSRN) without citing it. The ACM has a strict policy against plagiarism, misrepresentation, and falsification that applies to all publications.

Resubmission Guidelines. A paper that receives a Resubmit decision during the Aug 2024 submission cycle may submit a revised version to the Feb 2025 deadline. A paper that was either rejected or withdrawn after receiving its reviews during the Aug 2024 deadline could not submit a revision, and could not be re-submitted as a fresh submission to the Feb 2025 deadline. Please also refer to the FAQ for Resubmission.

Resubmission must be indicated upon submission, along with the OpenReview forum id of the previous submission. The resubmission should also include a one-page summary of changes as the first page of the submitted PDF. While this summary page will not be counted in the limit of 8 content pages, exceeding the first page will be considered a violation.

The reviewers/AC/SAC will have visibility of the previous submission and reviews. We anticipate that Resubmit papers that address the previously noted concerns appropriately would have a higher acceptance rate than fresh submissions, owing to the former’s selectivity and potential improvements.

Correspondingly, some of the fresh submissions to the Feb 2025 deadline may receive a Resubmit decision for KDD 2026 first deadline.

Serving as Reviewer. To ensure that all papers receive a sufficient number of high quality reviewers, there is a requirement for authors to contribute to reviewing.

Every submission must nominate at least one author who is a qualified reviewer (i.e., authors with at least three papers in KDD or other related conferences). Only if no qualified reviewer exists in the author list, nominate the best-qualified author for consideration by the PC chairs.
Any author listed on 3 or more papers will be automatically signed up as a reviewer unless they are already serving as a reviewer, AC, or SAC.

Either case above constitutes an acceptance and a commitment to carry out the regular reviewing load responsibly. Failure to provide a qualified reviewer when one exists in the author list, or failure to carry out the assigned reviewing duty properly, is grounds for desk rejection.

Ethical Use of Data and Informed Consent. Authors are encouraged to include a section on the ethical use of data and/or informed consent of research subjects in their paper, when appropriate. You and your co-authors are subject to all ACM Publications Policies, including ACM’s Publications Policy on Research Involving Human Participants and Subjects (posted in 2021). Please ensure all authors are familiar with these policies.

Please consult the regulations of your institution(s) indicating when a review by an Institutional Ethics Review Board (IRB) is needed. Note that submitting your research for approval by such may not always be sufficient. Even if such research has been approved by your IRB, the program committee might raise additional concerns about the ethical implications of the work and include these concerns in its review.

Submissions that do not follow these guidelines or do not view or print properly, will be desk-rejected.

Reviewing Process

Reviewing. Each submission will receive at least three independent reviews, overseen by an Area Chair (AC). If any author of a submission, who is also a reviewer, does not carry out the reviewing task in a proper and timely manner, no author of that submission will see the reviews of that submission during the rebuttal stage.

Any use of generative AI tools during the reviewing process must be disclosed in the review form. In particular, verbatim uploading of any passage from the paper being reviewed to any generative AI tool is forbidden.

Rebuttal. Authors will have the chance to provide a response to each review during the rebuttal period. The ACs will consider the authors’ response to the points raised by the reviewers, as well as discussion among reviewers, to inform acceptance decisions.

Withdrawal. Authors may use the withdrawal button on OpenReview up until the end of the rebuttal period. Beyond that, any request to withdraw must be made to the PC Chairs in writing, and approval for late withdrawal is at the discretion of PC Chairs. If withdrawal is made after reviews have been revealed to authors, the paper will face a 12-month waiting period before it could be submitted to KDD again.

Decision. A range of factors including technical merit, originality, potential impact, quality of execution, quality of presentation, related work, reproducibility of results, and ethics, will be used by the ACs to make a recommendation. The PC Chairs will make the final decisions.

Transparency. By submitting paper(s) to KDD 2025, the authors agree that the original submission, reviews, meta-reviews, and discussions will be made public in OpenReview for all accepted papers.

Conflict of Interest (COI) Policy

All authors and reviewers must declare conflicts of interest in OpenReview. A domain conflict (entered in Education & Career History) must be declared for employment at the same institution or company, regardless of geography/location, currently or in the last 12 months. A personal conflict should be declared when the following associations exist:

candidate for employment at the same institution or company
co-author on book/paper or co-PI on a funded grant/research proposal in the last 24 months
active collaborator
family relationship or close personal relationship
graduate advisee/advisor relationship, regardless of time elapsed since graduation
deep personal animosity

In general, we expect authors, PC, the organizing committee, and other volunteers to adhere to ACM’s Conflict of Interest Policy as well as the ACM’s Code of Ethics and Professional Conduct. Any transgression that falls short of ethical standards will be investigated and may face disciplinary actions. Such transgressions include, but are not limited to, falsification, dual submission, collusion, pressuring any member of the program committee. Convicted misconduct may result in a 3-year ban from SIGKDD events for all the authors.

To assess and be able to exclude CFP violations, authors must give consent to the SIGKDD to process and share their submission and other relevant data pertaining to the submission such as authors’ names, affiliations, and email addresses to related conference organizations. Any and all data will be processed by only the respective Program Chairs and the Ethics Committee Members.

Publication and Presentation Policies

Publication. All accepted papers will be allowed the same maximum page length in the proceedings (12 pages, of which 9 are content pages), which will be published by ACM and will be accessible via the ACM Digital Library. That is, while we allow one more content page for accepted papers to incorporate reviewer feedback and enhance the quality of their papers, we limit the references and Appendix to only 3 pages. Accepted papers will require a further revision to meet the requirements of the camera-ready format required by ACM. Camera-ready versions of accepted papers can and should include all information to identify authors, and should acknowledge any funding received that directly supported the presented research. The rights retained by authors who transfer copyright to ACM can be found here.

Reproducibility. In their submission, authors may refer to a code repository, though this is not strictly required. Rebuttals and discussions will not allow hyperlinks, so authors wishing to make code visible to reviewers must do so by referencing a repository at submission time.

Upon acceptance, authors are strongly encouraged to make their code and data publicly available. We are promoting the use of the “Artifacts Available” badge in ACM Digital Library. If you release any code, dataset, or similar artifact to accompany your paper, and host it in a publicly available, archival repository for research artifacts that provides a Document Object Identifier (DOI), you are welcome to apply for this badge.

There will be two rounds of applications for the badge:

Upon submission, authors can pledge that they will make their artifacts available upon publication. This pledge will be revealed to reviewers, who may consider this commitment positively. An accepted paper that later reneges on its pledge may have its acceptance retracted.
Upon acceptance, authors who have not made such a pledge during submission, would still be welcome to apply for this badge during the camera-ready preparations.

An artifact evaluation committee will check the artifacts of all accepted papers for availability and relatedness to the paper after the acceptance notification.

Registration. To be included in the proceedings, every accepted paper must be covered by a distinct conference registration, e.g., two multi-authored papers require two registrations, even if they have overlapping authors. This registration must be Full Conference (5-day) registration, at the standard (non-student) in-person rate, payment of which must be completed by the specified deadline. This registration requirement applies universally, regardless of attendance or presentation mode.

Presentation. Every accepted paper must be presented at the conference. No-show papers may be withdrawn from the proceedings.

Official Publication Date. The official publication date is the date the proceedings are made available in the ACM Digital Library. This date for KDD 2025 will be confirmed at a later stage. The official publication date affects the deadline for any patent filings related to published work.

Program Committee Co-Chairs

Email: KDD25-ads-chairs@acm.org

Qi He (Amazon)
WeeHyong Tok (Microsoft)
Andrew Tomkins (Google)

KDD 2026 (First Cycle) – Important Dates

As KDD receives two rounds of submissions per year, the anticipated dates for the next round are as follows.

Abstract Deadline: Jul 24, 2025
Paper Deadline: Jul 31, 2025
Author Rebuttal Period: Oct 4-18, 2025
Notification: Nov 16, 2025

KDD is the premier Data Science conference, hosting both a Research and an Applied Data Science Track. A paper should either be submitted to the Research Track or the Applied Data Science Track but not both.

KDD has multiple submission cycles per year. KDD 2025 will have two deadlines, one on August 1, 2024 and another on February 1, 2025 (with full paper deadlines a week after the abstract submission deadlines). Likewise, the KDD Proceedings will have two installments. Authors of accepted papers from the August 2024 deadline must opt in for early publication on the rights form in order for their papers to be included in the first installment.

The conference will take place in Toronto, Canada, expected in August 2025.

Important Dates

Abstract Deadline: Aug 1, 2024
Paper Deadline: Aug 8, 2024
Author Rebuttal Period: Oct 4-18, 2024
Notification: Nov 16, 2024
Camera-ready: ~~Dec 19, 2024~~ Jan 12, 2025
Conference: Aug 3-7, 2025

All submission deadlines are end-of-day in the Anywhere on Earth (AoE) time zone.

Submission Site

We will use OpenReview to manage the submissions and reviewing. Submissions will not be made public on OpenReview during the reviewing period.

All listed authors must have an up-to-date OpenReview profile. Here is information on how to create an OpenReview profile. Note OpenReview’s moderation policy for newly created profiles:

New profiles created without an institutional email will go through a moderation process that can take up to two weeks.
New profiles created with an institutional email will be activated automatically.

The OpenReview profile will be used to handle conflict of interest and paper matching. Incomplete OpenReview profile is sufficient ground for desk rejection. To be considered complete, each author profile must be properly attributed with the following mandatory fields: current and past institutional affiliation (going back at least 5 years), homepage, DBLP, ORCID, Advisors and Recent Publications. In addition, other fields such as Google Scholar, LinkedIn, Semantic Scholar, Advisees and Other Relations should be indicated wherever applicable.

Abstracts and papers can be submitted through OpenReview.

Scope: Deployed Applications of Data Science

The KDD’25 Applied Data Science (ADS) track chairs solicit submissions of papers describing designs and implementations of solutions and systems of practical applications in data mining, data analytics, data science, and applied machine learning. The primary emphasis is on papers that either solve or advance the understanding of issues related to deploying data science technologies in the real world. Papers demonstrating significant, verifiable real-world impact as a result of such deployments are encouraged.

Papers should present the problem, its significance to the application domain, the decisions and tradeoffs made when making design choices for the solution, how any challenges in areas like data collection, modeling, and deployment in constrained environments were overcome, and the lessons learned from successes and failures. It is perfectly fine if the underlying machine learning algorithms are not fundamentally groundbreaking. Evidence must be provided that the solution has been deployed by quantifying post-launch performance.

Papers should describe deployed real world applications, and should be aimed at a broad audience of applied data scientists. Application areas include but are not limited to the following:

Advertising, Marketing, and E-commerce
Social and professional networks
Recommendations
Financial Applications (including fintech, banking, insurance)
Geospatial Applications (including smart cities, transportation, mapping)Industrial Applications (including medical devices, robotics, sensors)
Scientific Applications (including computational biology, health, environmental science) Trust and Responsible AI Applications (including policy enforcement, regulatory compliance, ethics, fairness, privacy, and fraud detection)
Resource Allocation Applications (including Cloud, intranet, and other large system allocation optimizations)
Applications of Generative AI (including text, code, and media)

In addition to application papers, we also solicit submissions on Data and Benchmarking for Data Science Application Domains (including curation, validation, and release of large-scale data, experiments, and performance benchmarking).

An exception to the deployed production systems requirement may be made for papers describing systems intended to solve real-world problems that were blocked from deployment. These papers should explain the attempts that were made to deploy the system in production and what lessons were learned from the failures that would be broadly applicable and serve as critical learnings for future systems in the same or related domains.

Papers that deviate from the guidelines above (e.g., a research paper, a paper describing an algorithm or system tested solely on academic benchmark data) may be desk-rejected without formal review.
Novelty for an ADS Track submission will not generally focus on novel research contributions, but may instead lie in the choice of application domain, engineering design, usability approach, or business use case.

Submission Guidelines

Deadlines. The submission deadlines are strict and no extensions, regardless of circumstances, will be allowed. Placeholder or dummy abstracts are forbidden.

Maximum authorship. In the research track, the number of submissions allowed per author is limited to 5 (five) maximum. If more than 5 papers are submitted with the same person listed as an author, the additional papers submitted after the first 5 by submission id, will be desk-rejected.

Authorship changes. The full list of author names, including the ordering, must be finalized by submission deadline. There cannot be any addition, removal, or reordering of authors after the submission deadline. The only changes allowed are the correction of spelling mistakes or new affiliation.

Anonymity. The review process will be double-blind. The submitted document should omit any author names, affiliations, or other identifying information. This may include, but is not restricted to acknowledgments, self-citations, references to prior work by the author(s), and so on. Please use the third-person to refer to your own prior work. You may explicitly refer in the paper to organizations that provided datasets, hosted experiments, or deployed solutions and tools.

\documentclass[sigconf,anonymous,review]{acmart}

Resubmission Guidelines. A paper that receives a Resubmit decision during the Feb 2024 submission cycle may submit a revised version to the Aug 2024 deadline. A paper that was rejected during the Feb 2024 deadline could not submit a revision, and could not be re-submitted as a fresh submission to the Aug 2024 deadline. Please also refer to the FAQ for Resubmission.

Resubmission must be indicated upon submission, along with the OpenReview forum id of the previous submission. The resubmission should also include a summary of changes (limited to 5000 characters) in the submission form. The reviewers/AC/SAC will have visibility of the previous submission and reviews. We anticipate that Resubmit papers that address the previously noted concerns appropriately would have a higher acceptance rate than fresh submissions, owing to the former’s selectivity and potential improvements.

Correspondingly, some of the fresh submissions to the Aug 2024 deadline may receive a Resubmit decision for Feb 2025 deadline.

Serving as Reviewer. To ensure that all papers receive a sufficient number of high quality reviewers, every submission must nominate at least one author who is a qualified reviewer (i.e., authors with at least three papers in KDD or other related conferences). Being named as a reviewer in the submission constitutes an acceptance and a commitment to carry out the regular reviewing load responsibly. Only if no qualified reviewer exists in the author list, nominate the best-qualified author for consideration by the PC chairs. Failure to provide a qualified reviewer when one exists in the author list, or failure to carry out the assigned reviewing duty properly, is sufficient ground for desk rejection.

Submissions that do not follow these guidelines or do not view or print properly, will be desk-rejected.

Reviewing Process

Reviewing. Each submission will receive at least three independent reviews, overseen by an Area Chair (AC). At least one author per submission must commit to be a reviewer, carry the regular load, and submit all their reviews on time. If any author of a submission does not carry out the reviewing task in a proper and timely manner, no author of that submission will see the reviews of that submission during the rebuttal stage.

Withdrawal. Authors may request to withdraw their submissions only during the rebuttal period. Such requests must be made in written form to the PC Chairs and are completed only upon their acknowledgment.

Transparency. By submitting paper(s) to KDD 2025, the authors agree that the original submission, reviews, meta-reviews, and discussions will be made public in OpenReview for all accepted papers.

Conflict of Interest (COI) Policy

candidate for employment at the same institution or company
co-author on book/paper or co-PI on a funded grant/research proposal in the last 24 months
active collaborator
family relationship or close personal relationship
graduate advisee/advisor relationship, regardless of time elapsed since graduation
deep personal animosity

In general, we expect authors, PC, the organizing committee, and other volunteers to adhere to ACM’s Conflict of Interest Policy as well as the ACM’s Code of Ethics and Professional Conduct.

Any transgression that falls short of ethical standards will be investigated and may face disciplinary actions. Such transgressions include, but are not limited to, falsification, dual submission, collusion, pressuring any member of the program committee. Convicted misconduct may result in a 3-year ban from SIGKDD events for all the authors.

Publication and Presentation Policies

Publication. All accepted papers will be allowed the same maximum page length in the proceedings (12 pages, of which 9 are content pages), which will be published by ACM and will be accessible via the ACM Digital Library. That is, while we allow one more content page for accepted papers, we limit the references and Appendix to only 3 pages. Accepted papers will require a further revision to meet the requirements of the camera-ready format required by ACM. Camera-ready versions of accepted papers can and should include all information to identify authors, and should acknowledge any funding received that directly supported the presented research. The rights retained by authors who transfer copyright to ACM can be found here. Authors of accepted papers from the August 2024 deadline must opt in for early publication on the rights form in order for their papers to be included in the first installment.

Reproducibility. Authors are strongly encouraged to make their code and data publicly available after the review process. We are encouraging the (optional) use of the “Artifacts Available” badge in ACM’s Digital Library. If you release any code, dataset, or similar artifact to accompany your paper, and host it in a publicly available, archival repository for research artifacts that provides a Document Object Identifier (DOI), you are welcome to apply for this badge. A special subcommittee will check the artifacts of all accepted papers for availability and relatedness to the paper after the acceptance notification.

Presentation. Every accepted paper must be presented at the conference. No-show papers may be withdrawn from the proceedings.

Program Committee Co-Chairs

Email: KDD25-ads-chairs@acm.org

Claudia Perlich (Two Sigma)
WeeHyong Tok (Microsoft)
Andrew Tomkins (Google)

Feb 2025 Deadline – Important Dates

As KDD receives two rounds of submissions per year, the anticipated dates for the next round are as follows.

Notification: May 16, 2025
Abstract Deadline: ~~Feb 1, 2025~~ Feb 3, 2025
Paper Deadline: ~~Feb 8, 2025~~ Feb 10, 2025
Author Rebuttal Period: Apr 4-18, 2025