[hpc-announce] Call for Papers – DRAI 2025 Data Readiness for AI Workshop (in conjunction with ICPP 2025)

[Jean Luca Bez]

Call for Papers DRAI 2025
Data Readiness for AI Workshop
(in conjunction with ICPP 2025)

https://urldefense.us/v3/__https://sites.google.com/lbl.gov/drai__;!!G_uCfscf7eWS!doXqtIOSVmjHL4Hrxc9Je3jJPCJ7-uEy21CLDe-tPwvtbBlICHiZQnHHvSD-0LFYaYgsl10VAYAFySjK8TPXYg$ 

September 8 – San Diego, CA, USA

Submission Deadline: June 15, 2025

Data fuels Artificial Intelligence (AI) applications. Hence,
collecting and managing the lifecycle of high-quality data that has
been evaluated to be ready for AI is critical to creating new large AI
models that assist in enabling scientific breakthroughs across
domains. However, there are several challenges in achieving AI
readiness for research data. This workshop aims to enable discussions
on novel and efficient methods for collecting and preparing data for
AI across multiple scientific domains, metrics to quantify data
readiness, frameworks for improving data readiness, assessments of the
impact of data on AI model performance, and existing challenges and
caveats in managing and transforming historical and new data from
various science domains into AI-ready data. The workshop seeks to
bring together researchers from academia, industry, and national
laboratories to share insights, foster collaboration, and push the
existing boundaries between data and AI in scientific discoveries.

Topics of Interest (including but not limited to):

- Efficient Data Quality Improvement (Semi-/Automatic Methods)
- Quantifiable Metrics for AI Data Readiness
- Frameworks and Tools for Assessing & Automating Data Readiness
- Frameworks for Data Readiness Improvement
- Distributed and Parallel Algorithms for AI Data Processing (HPC Intersection)
- Scalability of AI Readiness Solutions
- Creation and usage of AI-ready benchmark datasets
- Novel Approaches for Handling Massive Datasets
- Real-World Use Case Assessments of Data Readiness Impact on AI Performance
- Data Readiness in Integrated Scientific Pipelines: Use Cases,
Challenges, Needs
- Role of FAIR principles in AI readiness of data
- Ethical and Comprehensive Data Collection
- Collection of balanced data and the characterization of biases
- AI Algorithms for Non-AI-Ready Scientific Data
- Social Impacts of Data in AI Applications
- Data Governance: Metrics, Methods, and Use Cases (Security, Privacy,
Management)
- The importance of provenance and contextual information, e.g., as
captured in datasheets
- Transparency and ethics related to AI readiness
- AI readiness of multi-modal scientific data and streaming data

All submissions will receive at least three reviews. We strongly
encourage authors to share code, data, and artifacts alongside their
papers.

Important Dates
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Paper Submission Deadline: June 15, 2025
Notification of Acceptance: July 1, 2025
Camera-Ready Deadline: July 15, 2025
Workshop Date: September 8, 2025

Submission Guidelines
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DRAI is accepting submissions for regular and short papers. Regular
papers should be 6 (six) pages (including references), and short
papers should be 2 (two) pages (including references), both formatted
according to the ICPP 2025 workshop proceedings style (ACM Sigconf
format). Detailed submission instructions are available at
https://urldefense.us/v3/__https://sites.google.com/lbl.gov/drai__;!!G_uCfscf7eWS!doXqtIOSVmjHL4Hrxc9Je3jJPCJ7-uEy21CLDe-tPwvtbBlICHiZQnHHvSD-0LFYaYgsl10VAYAFySjK8TPXYg$ . Submissions, reviews, and
communications with authors will be handled through Linklings. To
submit, please access https://urldefense.us/v3/__https://ssl.linklings.net/conferences/icpp__;!!G_uCfscf7eWS!doXqtIOSVmjHL4Hrxc9Je3jJPCJ7-uEy21CLDe-tPwvtbBlICHiZQnHHvSD-0LFYaYgsl10VAYAFySj4MjR_3w$  and
select the “DRAI - Data Readiness for AI Workshop”.

Organizers
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Jean Luca Bez, Lawrence Berkeley National Laboratory (LBNL), USA
Suren Byna, The Ohio State University (OSU), USA

For inquiries, contact: jlbez at lbl.gov, byna.1 at osu.edu