Combining OS and OSM Data - A Case Study for geospatial data integration Name: Du Heshan Supervisor: Dr Suchith Anand

Presentation Outline Project Background Project Objective A Case Study: OS vs OSM Methodology Software Demo Current Work and Future Plan

Project Background - Geospatial data integration Geospatial data integration (GDI) is the merging of geographic data, including spatial and non-spatial data, from disparate sources with differing conceptual, contextual and typographical representations.

Project Background -Initiative for GDI >80% information has a spatial component Sources of geographic information –Different levels GEOSS (Global), INSPIRE (Europe), Ordnance Survey (National) –Different countries –Different approaches, styles: OS (Authoritative) vs OpenStreetMap (Crowdsourced) Communication, collabration, improvement

Project Background -Open Source GIS Rapid growth of open source GIS Based on open source standards –OGC, ISO TC 211 Advantages –Open access to source code –Low cost, free

Project Objective Combining OS and OSM datasets as a case study for GDI Developing software applications based on Open Source framework to automate the process

A Case Study -Ordnance Survey and OpenStreetMap source aspectOrdnance SurveyOpenStreetMap Data Collection Top-down, formal, expensive Bottom-up, informal, low cost Authority HighLow Accuracy HighLow InformationStructuredRich, flexible tag

A Case Study -Ordnance Survey and OpenStreetMap * OS-ITN portsmouth * OSM Road

Methodology First Step: How do we define data from different sources are corresponding, refering to the same object? Geometric matching Ontology matching Second Step: Semantic integration

Geometric Matching Geometric accuracy of data differs Background previous work of interest: –Ather, a quality analysis of OpenStreetMap Data –Al-Bakri and Fairbairn, assessing the accuracy of crowdsourced data and its integration with official spatial data sets. –Lianxia Xi, map matching algorithm and its application Buffer Analysis and Map matching Suffer from segmentation problem

Geometric Matching -Segmentation Problem * OS-ITN * OSM

Ontology Matching Heterogeneous databases –Independent development –Own data vocabulary –May conflict in structure, context, and value Ontology: –Nature and categories of being, their relations Semantic correspondences

Ontology Matching - similar fields dataset fieldsOS-ITNOSM road nameROADNAMEname road typeDESCRIPT1highway

Ontology Matching -Road Network Build up network, especially for OSM Rely on relationships to identify a road Matching road by road

Semantic Integration Interrrelating information Study metadata, product specification Design a new data model –First step: adding OSM field to OS data

Software Demo * Simple GDI tool * Network building

Ongoing Work and Future Plan Ongoing work: –Literature review, open source GIS software development Future Plan: –For the case study: More ontology matching Combine geometric and ontology matching, algorithm optimization Design a integrated data model –Generalize the methodology for GDI

Thank you !