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cs.DB updates on arXiv.org

Block-Sphere Vector Quantization GroupAffect-4: A Multimodal Dataset of Four-Person Collaborative Interaction CogScale: Scalable Benchmark for Sequence Processing TextAlign: Preference Alignment for Text Rendering with Hierarchical Rewards LogRouter: Adaptive Two-Level LLM Routing for Log Question Answering in Big Data Systems Agentic Cost-Aware Query Planning with Knowledge Distillation for Big Data Analytics Covariance Structure and Coordinate Heterogeneity Govern Binary Quantization of Contrastive Embeddings IVF-TQ: Calibration-Free Streaming Vector Search via a Codebook-Free Residual Layer Automatic Unsupervised Ensemble Outlier Model Selection--Extended Version A Generative AI Framework for Intelligent Utility Billing CO 2 Analytics and Sustainable Resource Optimisation Towards Foundation Models for Relational Databases with Language Models and Graph Neural Networks Gaussian Relational Graph Transformer Croissant Baker: Metadata Generation for Discoverable, Governable, and Reusable ML Datasets Reducing Hallucination in Vision-Language Models via Stage-wise Preference Optimization under Distribution Shift A Horn extension of DL-Lite with NL data complexity 3D Primitives are a Spatial Language for VLMs Enabling AI-Native Mobility in 6G: A Real-World Dataset for Handover, Beam Management, and Timing Advance A CAP-like Trilemma for Large Language Models: Correctness, Non-bias, and Utility under Semantic Underdetermination EpiCastBench: Datasets and Benchmarks for Multivariate Epidemic Forecasting FERMI: Exploiting Relations for Membership Inference Against Tabular Diffusion Models Toward Multi-Database Query Reasoning for Text2Cypher Autonomous FAIR Digital Objects: From Passive Assertions to Active Knowledge HOME-KGQA: A Benchmark Dataset for Multimodal Knowledge Graph Question Answering on Household Daily Activities Detect, Localize, and Explain: Interactive Hierarchical Log Anomaly Analytics with LLM Augmentation Open Ontologies: Tool-Augmented Ontology Engineering with Stable Matching Alignment Machine Learning-Based Pre-Test Risk Stratification for PCR-Confirmed Chlamydia Using Patient-Reported Data and Urine Biomarkers Reconciling Consistency-Based Diagnosis with Actual-Causality-Based Explanations PrepBench: How Far Are We from Natural-Language-Driven Data Preparation? Anatomy of a Query: W5H Dimensions and FAR Patterns for Text-to-SQL Evaluation Building informative materials datasets beyond targeted objectives
Implementing a Scalable, Redeployable and Multitiered Rep...
Valeria Granata, Francois Liot, Xing Wang, Steen Lysgaard, Ivano · 2025-12-17 · via cs.DB updates on arXiv.org

Data sharing in large consortia, such as research collaborations or industry partnerships, requires addressing both organizational and technical challenges. A common platform is essential to promote collaboration, facilitate exchange of findings, and ensure secure access to sensitive data. Key technical challenges include creating a scalable architecture, a user-friendly interface, and robust security and access control. The BIG-MAP Archive is a cloud-based, disciplinary, private repository designed to address these challenges. Built on InvenioRDM, it leverages platform functionalities to meet consortium-specific needs, providing a tailored solution compared to general repositories. Access can be restricted to members of specific communities or open to the entire consortium, such as the BATTERY 2030+, a consortium accelerating advanced battery technologies. Uploaded data and metadata are controlled via fine grained permissions, allowing access to individual project members or the full initiative. The formalized upload process ensures data are formatted and ready for publication in open repositories when needed. This paper reviews the repository's key features, showing how the BIG-MAP Archive enables secure, controlled data sharing within large consortia. It ensures data confidentiality while supporting flexible, permissions-based access and can be easily redeployed for other consortia, including MaterialsCommons4.eu and RAISE (Resource for AI Science in Europe).