Imagine you run a navigation app or a travel website, and you pull location data — restaurants, hotels, gas stations — from dozens of different sources. Each source names and categorizes places differently, has typos, outdated info, or missing details. Merging all of that into one clean, reliable list is a nightmare that normally takes armies of people. SLIPO built software that does this automatically, using smart linking technology to match, merge, and enrich millions of Points of Interest records without manual work.
Companies that rely on location data — navigation providers, travel platforms, logistics operators — waste enormous time and money trying to merge POI records from different sources. Each source uses different names, categories, and formats, leading to duplicates, errors, and outdated listings. Manual cleanup doesn't scale when you're dealing with millions of records across multiple countries.
The project delivered a complete software platform for automated POI data integration: a beta system used for real-world trials, and a final integrated system refined from trial feedback. The platform links, merges, enriches, and quality-checks POI data from open, crowdsourced, and proprietary Big Data sources using linked data technology.
If you are a mapping company dealing with messy, duplicated location records pulled from OpenStreetMap, government datasets, and commercial feeds — this project developed an integrated software system that automatically links, deduplicates, and enriches POI data across sources. It was validated in tourism and logistics with 8 consortium partners across 4 countries.
If you are a travel platform struggling to keep your hotel, restaurant, and attraction listings accurate across regions — this project built tools that merge POI data from crowdsourced and proprietary sources while checking quality. The system was trialed with a beta and final integrated version, handling the kind of large-scale data reconciliation that usually requires expensive manual curation.
If you are a delivery or logistics company that depends on accurate address and location data for route planning — this project created a scalable platform to integrate and clean POI data from multiple feeds. With 5 industry partners in the consortium and validation in the logistics domain, the system targets exactly the data quality problems that cause failed deliveries and wasted fuel.
The project received EUR 2,635,500 in EU funding and was an Innovation Action, meaning the technology was built to be close to market. Licensing or integration costs would depend on the coordinator's commercialization terms. Based on available project data, no specific pricing model is disclosed.
Yes — the project was specifically designed for 'Big POI data' and scalability is in its name. The final integrated system was tested through structured trials with consortium partners. The linked data approach was chosen precisely because it scales better than manual or rule-based integration methods.
The consortium includes 5 industry partners and 2 SMEs across 4 countries. IP arrangements would have been defined in the consortium agreement. Interested companies should contact the coordinator to discuss licensing, white-label, or integration options.
The system builds on linked data standards and was designed to work with open, crowdsourced, and proprietary data sources. Based on available project data, it integrates with existing geospatial data pipelines rather than replacing them. The 16 deliverables include the full integrated platform plus documentation.
The project delivered both a beta and a final integrated system version. With 62% industry ratio in the consortium and an Innovation Action funding scheme, the technology was built for commercial uptake. Current availability should be confirmed with the coordinator.
The system handles location data from public and commercial sources, not personal data directly. However, any deployment combining POI data with user behavior would need GDPR consideration. Based on available project data, compliance specifics are not detailed in the objectives.
The SLIPO consortium of 8 partners across 4 countries (Austria, Germany, Greece, Netherlands) is strongly industry-oriented with 5 industry partners making up 62% of the group, alongside 3 research organizations. The presence of 2 SMEs signals startup-level agility alongside larger players. Coordinated by the Athena Research Centre in Greece, the mix of German and Dutch tech ecosystems with Greek research strength covers both the engineering and scientific bases. No universities were involved, which suggests this was built for practical deployment rather than academic exploration.
Athena Research Centre (ATHINA-EREVNITIKO KENTRO), Greece — reach out to the project lead via the CORDIS contact form or the project website
Want to integrate scalable POI data tools into your mapping or logistics platform? SciTransfer can connect you with the SLIPO team and help evaluate fit for your use case.
