Data is the foundation of every AI solution. Our Data Services support users in managing the complete lifecycle of data, from discovery and creation to preparation and analysis. We help users identify relevant datasets, ensure data quality and compliance, extract meaningful insights, and generate new data assets when needed. Whether working with structured or unstructured data, across scientific, industrial, or public domains, we provide tools, expertise, and infrastructure to make data usable, valuable, and actionable for AI-driven innovation.
Discover Data related Services
Integrated data lifecycle services for secure, ethical, and high-impact AI development
Application examples
DATA DISCOVERY
An organization aims to develop an AI application but lacks a complete dataset
This service facilitates, among other activities:
- Targeted Discovery: Identifying internal IT4LIA assets or searching external repositories based on coverage, format, and accessibility.
- Scalable Ingestion: Directing users to Massive Data Transfer for efficient integration of large-scale external datasets.
- Data Enrichment: Recommending Synthetic Data Generation to fill gaps or enrich incomplete datasets prior to AI processing.
Case Study: The service offers specialized support for MeteoHub Integration to Agenzia Italia Meteo, managed by CINECA. The service enables the acquisition, management, and distribution of critical meteorological data for AI-driven insights.
DATA PREPARATION
Organizations often struggle with inconsistent data quality that stalls AI training
This service facilitates, among other activities:
- IoT Time-Series Refinement: Cleaning sensor data for energy consumption models by addressing missing values, time gaps, and outlier detection using parallel processing.
- Computer Vision Standardization: Preparing image datasets for infrastructure monitoring by normalizing lighting, resolution, and color across thousands of files.
- Automated Labeling Prep: Defining repeatable workflows to segment and structure data, ensuring it meets the specific variety and quality requirements for AI.
Case Study: The service enables a public administration entity to process a massive archive of periodic images for facade degradation detection, providing the parallel processing code needed to standardize varied image formats into a single, model-ready dataset.
DATA CREATION
Scenario: Augmenting Specialized AI Training Organizations often face “cold-start” problems where real-world data is restricted or insufficient
This service facilitates, among other activities:
- Healthcare NLP: Generating large corpora of simulated Q&A pairs from official medical sources to fine-tune virtual assistants, with expert verification of medical entities.
- Computer Vision Validation: Expanding small image samples into massive datasets for smart manufacturing, simulating varied conditions like rotation, lighting, and noise to test automatic label reading.
Case Study: The service supports a SME in creating a corpus of thousands of clinically-inspired dialogue pairs, allowing them to train a specialized medical assistant without compromising patient privacy or waiting months for manual data collection.
DATA MANAGEMENT
Organizations dealing with massive, varied datasets require specialized environments for rapid analysis
This service facilitates, among other activities:
- Weather Nowcasting: Enabling the parallel processing of real-time meteorological data for immediate atmospheric forecasting.
- Infrastructure Registries: Managing large-scale technical building registries that require frequent updates and complex editing of multi-format files.
- AI Training Cycles: Handling the management and selection of massive training datasets to optimize model development on supercomputers.
Case Study: The service supports weather monitoring entities in leveraging parallel supercomputing to analyze multi-format atmospheric data, significantly reducing the time between data ingestion and live nowcasting results.