Brief description: 

SLIPO is the first comprehensive cloud-based platform for the quality-assured and scalable integration of Big POI data assets. SLIPO reduces the effort, time, and complexity of POI data integration, providing POIs of increased size, coverage, richness and timeliness at a fraction of the cost. Already validated in a pre-commercial setting in multiple Data Economy domains, SLIPO delivers integrated POI assets with quality comparable to that manual-driven data integration.

POI data (Points of Interest) are the cornerstone of any application, service, and product even remotely related to our physical surroundings. The creation, update, and provision of POI datasets consists a multi-billion cross-domain and cross-border industry, with a value chain natively incorporating most domains of our Digital and Physical economy. The value and impact of POIs is reflected in the complex, expensive and labor-intensive effort required for their production and maintenance, which inherently involves stakeholders and users throughout their value chain.

The SLIPO platform allows users to securely manage and store their geospatial data assets, graphically design complex data integration workflows, full automate data integration, track the provenance of their POI assets, implement strict QA policies, and export their data integration results in third-party systems and products. Further, SLIPO provides a series of integrated analytics extracting added value from POIs data assets (e.g., identification of areas of interest) to feed decision making. Finally, the entire SLIPO platform, its data assets, workflows, and analytics, is available through Python-based Jupyter notebooks, further supporting industrial data scientists and allowing the direct exploitation of SLIPO in existing business workflows.

Main Features: 
  • World-scale POI data integration over heterogeneous geospatial data assets
  • Fully automated as well as expert-driven definition of data integration workflows
  • Secure management and provision of POI assets, integration workflows, and users
  • Integrated QA services, curation, and provenance tracking
  • Build and maintain a Knowledge Graph of your POI and geospatial data assets
  • Scalable out-of-the-box value-added analytics for POI data assets
  • Support for integration with Python-based Jupyter notebooks
  • Real-world, cross-sectoral validation
Areas of Application: 

SLIPO is relevant to all economy sectors where POI data assets are applied to power prodcuts, services, and decision-making (e.g., geomarketing, retail, logistics, tourism, mobile)

Customer Benefits: 
  • Increase value, richness, quality and timeliness of your POI data assets
  • Achieved practically identical integration results with expert-driven manual integration
  • Integration at a fraction of the effort and cost
  • Leverage proprietary and open/public geospatial data assets
  • Expand products, services and workflows across EU and the world
  • Reduce time-to-market
  • Cloud-based, low-cost, and pay-as-you-go pricing models
  • Receive expert support at every step or even outsource your integration
Technological novelty: 

Linked data technologies for geospatial data have been developed in the past years with the specific focus on addressing the scalability challenges of integrating, enriching, and querying semantically diverse geospatial Big Data assets. Validated in the domains of tourism and logistics, these technologies have proven their benefit as a cost-effective and scalable foundation for the quality-assured integration, enrichment, and sharing of generic-purpose geospatial data.

In SLIPO, we have transferred the challenge of POI data integration in the Linked Data domain, applying and specializing leading linked data software for transformation, interlinking, fusion, and enrichment, to POI data assets. This approach has successful addressed the lack of common identifiers, semantic and syntactical heterogeneity, as well as the diversity of POI assets. More importantly, SLIPO requires no linked data experience from its users, abstracting all related complexity, and lowering the entry barrier even further with its fully automated operation. As such, any company from any sector of our Data Economy can tap into high-quality POI data at a fraction of the cost,

Platform / Framework


Spiros Athanasiou
BDV Reference categories: 
Data Analytics
Information Service activities
Wholesale, retail and eCommerce
Transport, storage and logistics
Urban Mobility
Readiness Level: 
Apache License v2.0
Big Data