Research
This page collects the ten original research artifacts published with a permanent identifier (DOI) on Zenodo: two benchmark datasets, three software repositories and five open-data datasets, each with an open licence and a verifiable ORCID author. Every card shows the concept DOI (the stable identifier to cite) and the specific version DOI cited, plus a link to the artifact's home: the GitHub repository for the software and the benchmarks, the dedicated page on this site for the open-data datasets. To cite an artifact correctly, use the concept DOI: it always resolves to the latest version.
Sport Intelligence Benchmark
Ensemble V2 LightGBM meta-learner methodology for football match outcome prediction, with an end-to-end reproducible synthetic dataset. The repository reports two distinct Brier scores, deliberately never reconciled into one: the synthetic-sample score (reproducible with a single command, generated, not real data) and the production score, 0.5783 on 97,000 real historical matches, openly stated as not verifiable by third parties because the underlying data is not redistributable. Code: MIT. Contents of data/: CC-BY-4.0.
MITCC-BY-4.0How to cite
10.5281/zenodo.21602378 (opens in a new tab)Version cited: v1.0.0 — Version DOI: 10.5281/zenodo.21602379
Citation & DOI
Version cited: v1.0.0 — Version DOI:
10.5281/zenodo.21602379MITCC-BY-4.0 (data/)Citation (APA):Calò, F. (2026). Sport Intelligence Benchmark (v1.0.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.21602378GEO Retrofit Benchmark
Additive answer-first + FAQ retrofit engine and structural GEO/AEO detection gate that took a real bilingual (IT+EN) content corpus of 194 articles from 741 structural findings to 0. The repository ships a synthetic before/after fixture pair to mechanically reproduce the transform: the real 194-article corpus is not redistributed, but the code that produced the result is fully verifiable. Code: MIT. Contents of fixtures/: CC-BY-4.0.
MITCC-BY-4.0How to cite
10.5281/zenodo.21602375 (opens in a new tab)Version cited: v1.0.0 — Version DOI: 10.5281/zenodo.21602376
Citation & DOI
Version cited: v1.0.0 — Version DOI:
10.5281/zenodo.21602376MITCC-BY-4.0 (fixtures/)Citation (APA):Calò, F. (2026). GEO Retrofit Benchmark (v1.0.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.21602375INP/CWV Playbook
Four Angular SSR patterns that took a real production home page from a mobile PageSpeed score of 59 to 88 (Moto G Power, 4G). Each pattern documents the anti-pattern that caused the regression, the fix, and the measured effect: precompute-instead-of-fan-out, PlatformLocation vs REQUEST at prerender time, afterNextRender to kill forced reflow, and why a host-based script-src 'self' Content-Security-Policy (never strict-dynamic) is the only prerender-compatible shape.
MITHow to cite
10.5281/zenodo.21602163 (opens in a new tab)Version cited: v1.0.0 — Version DOI: 10.5281/zenodo.21602164
Citation & DOI
Version cited: v1.0.0 — Version DOI:
10.5281/zenodo.21602164MITCitation (APA):Calò, F. (2026). INP/CWV Playbook (v1.0.0) [Computer software]. Zenodo. https://doi.org/10.5281/zenodo.21602163Production Postmortems
Four real production incidents from a Spring Boot backend, each documented with symptom, root cause, why the existing test suite did not catch it, the fix, and an anti-repeat rule: a Flyway checksum crash from a one-line comment edit, an ArchUnit architecture-fitness test that silently ran zero tests for months, an in-place JAR overwrite racing a live JVM, and a duplicate-simple-name Spring bean crashing boot. Plus one minimal, dependency-free reproduction of the Flyway checksum mechanism.
MITHow to cite
10.5281/zenodo.21602370 (opens in a new tab)Version cited: v1.0.0 — Version DOI: 10.5281/zenodo.21602371
Citation & DOI
Version cited: v1.0.0 — Version DOI:
10.5281/zenodo.21602371MITCitation (APA):Calò, F. (2026). Production Postmortems (v1.0.0) [Computer software]. Zenodo. https://doi.org/10.5281/zenodo.21602370Clean Architecture Spring Boot Template
A 4-layer Clean Architecture Spring Boot 3.4 template (Java 21) with JWT auth, Flyway migrations, a generic rate-limit slice, a Resilience4j preset, and - the whole point - an ArchUnit fitness gate that genuinely runs (four rules, Tests run: 4), not the silent Tests run: 0 false-green that the idiomatic @ArchTest static-field pattern produces on Spring Boot 3.4. Sanitized by hand from a production backend; the example aggregate is a generic Task, not any business vertical.
MITHow to cite
10.5281/zenodo.21602171 (opens in a new tab)Version cited: v1.0.0 — Version DOI: 10.5281/zenodo.21602172
Citation & DOI
Version cited: v1.0.0 — Version DOI:
10.5281/zenodo.21602172MITCitation (APA):Calò, F. (2026). Clean Architecture Spring Boot Template (v1.0.0) [Computer software]. Zenodo. https://doi.org/10.5281/zenodo.21602171EU AI Act Obligations Matrix — Italy focus 2026
Structured catalog of the obligations established by EU Regulation 2024/1689 (AI Act), mapped by article, risk category, target actor, enforcement deadline and penalty tier. Designed as a compliance-planning resource for providers, deployers, creators and solopreneurs in the EU market, with specific notes for Italian legal context.
CC-BY-4.0How to cite
10.5281/zenodo.20804743 (opens in a new tab)Version cited: v1.1.0 — Version DOI: 10.5281/zenodo.21705646
Citation & DOI
Version cited: v1.1.0 — Version DOI:
10.5281/zenodo.21705646CC-BY-4.0Citation (APA):Calò, F. (2026). EU AI Act Obligations Matrix — Italy focus 2026 (v1.1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.20804743Museums Open — Italy 2026 Q2
Registry of Italian museums and galleries derived from OpenStreetMap (ODbL-1.0) and enriched with Wikidata (CC0) identifiers. First iteration of the Museums Open index; v2.0 will add MiC accessibility data and the UK + France extension.
ODbL-1.0How to cite
10.5281/zenodo.20804745 (opens in a new tab)Version cited: v1.0.0 — Version DOI: 10.5281/zenodo.20804746
Citation & DOI
Version cited: v1.0.0 — Version DOI:
10.5281/zenodo.20804746ODbL-1.0Citation (APA):Calò, F. (2026). Museums Open — Italy 2026 Q2 (v1.0.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.20804745Puglia Tech Ecosystem 2026 — Startup, scale-up, corporate hub
Curated snapshot of the Puglia (South Italy) tech ecosystem: startups, scale-ups, corporate research centers and innovation hubs active in 2026. Derived from public sources: PugliaTechs, Crunchbase, Registro Imprese, LinkedIn verified. v1.0.0 includes 52 entities.
CC-BY-4.0How to cite
10.5281/zenodo.20804747 (opens in a new tab)Version cited: v1.1.0 — Version DOI: 10.5281/zenodo.21705726
Citation & DOI
Version cited: v1.1.0 — Version DOI:
10.5281/zenodo.21705726CC-BY-4.0Citation (APA):Calò, F. (2026). Puglia Tech Ecosystem 2026 — Startup, scale-up, corporate hub (v1.1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.20804747Quality of Life — Italian Regional Capitals 2026 Q2
Multidimensional cultural-density index across 20 Italian regional capitals, derived from OpenStreetMap (ODbL-1.0) and Wikidata (CC0-1.0) POIs. Schema is globally shaped for future European and global expansion.
ODbL-1.0How to cite
10.5281/zenodo.20804749 (opens in a new tab)Version cited: v1.1.0 — Version DOI: 10.5281/zenodo.21705736
Citation & DOI
Version cited: v1.1.0 — Version DOI:
10.5281/zenodo.21705736ODbL-1.0Citation (APA):Calò, F. (2026). Quality of Life — Italian Regional Capitals 2026 Q2 (v1.1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.20804749Best Times to Visit — 30 Italian Cities 2026
Monthly travel recommendation scores for 30 major Italian cities. Three signals per month: weather comfort (0–100), events density (0–100), and inverse tourist crowds (0–100), combined into a composite score. Editorial curation based on Open-Meteo historical climate data and ISTAT tourism flows 2019–2024.
CC-BY-4.0How to cite
10.5281/zenodo.20804751 (opens in a new tab)Version cited: v1.0.0 — Version DOI: 10.5281/zenodo.20804752
Citation & DOI
Version cited: v1.0.0 — Version DOI:
10.5281/zenodo.20804752CC-BY-4.0Citation (APA):Calò, F. (2026). Best Times to Visit — 30 Italian Cities 2026 (v1.0.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.20804751