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license: odc-by |
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# OpenData-Benchmark-ITA |
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## Overview |
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**OpenData-Benchmark-ITA** is a multiple-choice benchmark dataset designed to evaluate the capability of Large Language Models (LLMs) to understand, retrieve, and reason over public Open Data published by European government portals. |
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The current release focuses exclusively on Italian Open Data and is based on datasets published on the official Italian government portal, **data.gov.it**. Future releases will extend the benchmark to include harmonized governmental Open Data from additional European countries, starting with France, Spain, and Germany. |
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The dataset is released under the **ODC-BY (Open Data Commons Attribution)** license, enabling broad reuse for research, evaluation, and benchmarking purposes beyond its original project scope. |
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## Benchmark Objective |
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The primary objective of OpenData-Benchmark-ITA is to assess the *effective knowledge and practical usability* of Italian governmental Open Data by LLMs developed within the **Villanova project**. |
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Rather than testing general language understanding, the benchmark focuses on: |
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- Familiarity with real-world Open Data resources |
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- Ability to interpret dataset metadata |
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- Capability to answer content-based questions grounded in actual public datasets |
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This makes the benchmark particularly suitable for evaluating domain adaptation, retrieval-augmented generation pipelines, and public-sector–oriented AI systems. |
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## Dataset Composition |
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The benchmark is structured as a **multiple-choice question-answering task**. Each question is grounded in the content or metadata of a specific Open Data resource. |
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- **Number of datasets sampled:** 500 |
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- **Source portal:** data.gov.it |
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- **Total datasets available on portal:** ~65,000 |
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- **Data formats:** Primarily CSV for data files, paired with JSON metadata |
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Each benchmark item is derived from a *pair* consisting of: |
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1. A structured data file (mainly CSV) |
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2. The corresponding official metadata in JSON format |
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## Data Origin and Curation Process |
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The dataset is **manually curated** following a structured and quality-driven workflow. |
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The process includes: |
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- Systematic sampling from the Italian Open Data portal |
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- Manual verification of dataset relevance and accessibility |
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- Careful inspection and cleaning of metadata |
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- Manual design and validation of multiple-choice questions to ensure clarity, correctness, and grounding in the source data |
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This approach ensures that the benchmark reflects realistic usage scenarios of public Open Data and avoids synthetic or purely artificial artifacts. |
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## Selection Criteria |
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The selection of datasets followed clear, content-oriented criteria: |
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- Alignment with the objectives of the Villanova project |
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- Preference for datasets enabling automated processing and analysis |
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- Priority given to machine-readable formats, particularly CSV |
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- Availability of complete and well-structured metadata |
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The final sample consists of **500 dataset–metadata pairs**, each suitable for downstream benchmarking and evaluation tasks. |
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## Collection Period |
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No strict temporal constraints were applied during dataset selection. |
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However, preference was given to **"live" datasets**, identified by: |
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- A recent or regularly updated modification date |
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- Ongoing relevance in terms of data production and maintenance |
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This choice increases the realism of the benchmark when used to evaluate models intended for interaction with up-to-date public data sources. |
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