uni-heidelbergdegis

Towards a framework for

Intrinsic Data Quality Analysis ofVolunteered Geographic Information

Alexander Zipf GIScience Research Group

Heidelberg Universityzipfuni-heidelbergde

uni-heidelbergdegis

Smart Mobility OpenRouteServiceorg

VGI for Humanitarian Aid Big Spatial Data Analytics

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Dimensions of Spatial Data Quality

bull Lineage

bull Completeness

bull Logical Consistency

bull Positional Accuracy

bull Attribute Accuracy

bull etchellip

OSMatrixuni-hdde

uni-heidelbergdegis

Goodchild Haklay M (2010)

Neis Zielstra amp Zipf (2012) The Street Network Evolution of Crowdsourced Maps - OpenStreetMap in Germany 2007-2011Future Internet Vol4 pp1-21

VGI Data Quality

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iOSManalyser Intrinsic OSM Analysis

etc

Barron C Neis P amp Zipf A (2013)A Comprehensive Framework for Intrinsic

OpenStreetMap Quality Analysis Transactions in GIS DOI 101111tgis12073

uni-heidelbergdegis

iOSManalyser Intrinsic Quality Indicators

Barron C Neis P amp Zipf A (2013)A Comprehensive Framework for Intrinsic

OpenStreetMap Quality Analysis Transactions in GIS

DOI 101111tgis12073

uni-heidelbergdegis

OSMapper Contribution Index

Jokar Arsanjani J Mooney P Helbich M Zipf A (2015)An exploration of future patterns of the contributions to OpenStreetMap amp development of a Contribution Index Transactions in GIS DOI 101111tgis12139

uni-heidelbergdegis

Degrossi LC Albuquerque JP Rocha RS Zipf A (2018) A taxonomy of quality assessmentmethods for volunteered andcrowdsourced geographic informationTransactions in GIS 2018 001ndash19

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Conceptual Quality Dimension for VGI

bull Accuracy Indicators Eg Number of features with multiple classications number of contributors

Distance between conceptualization ampdomain knowledge Degree of correctness in the classication of features in classes

bull Granularity Eg Depth of classes in the class hierarchy

Level of thematic description from abstract to specifc concepts

bull Completeness Eg Number of classes number of attributes

Coverage in the conceptualization of the features of interest

bull Consistency Eg Number of features in a class with the same attributes ratio between consistent features or attributes to all others

Degree of homogeneity in the descriptions of geographic features

bull Compliance Eg Ratio between the number of classes and attributes dened in an external source S and the total number of classes ampattributes

Degree of adherence of an attribute a feature or a set of features to a given source S

bull Richness Eg Number of attributes describing a feature

Amount and variety of dimensions that are included in the description of the real-world entity

Ballatore A amp A Zipf (2015) A Conceptual Quality Framework forVolunteered Geographic Information COSIT 2015 Santa Fe

uni-heidelbergdegis

osm-visgeoguni-heidelbergde

Mocnik F-B Zipf A Raifer M (2017)The OpenStreetMap folksonomy and its evolution Geo-Spatial Information Science GSIS Taylor amp Francis Vol 20 2017 pp 219-230

Development of the OSM Wiki

Investigating the OSM folksonomy

uni-heidelbergdegis

osmatrixuni-hdde

Roick O Loos L amp Zipf A (2012) Visualizing spatio-temporal quality metrics of Volunteered

Geographic Information ndash A case study for OpenStreetMap Geoinformatik 2012 Braunschweig

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ohsome API

OSHDB API

OSHDBFlexibility

Usability

ohsomeorgOSM-HISTORY PLATFORM

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ohsome APIrarr REST web service

rarr interactive analyses and

visualizations in browser

ohsomeorgOSM-HISTORY PLATFORM

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apiohsomeorgv09swagger-uihtml

ohsomeorgOSM-HISTORY PLATFORM

Examplehttpsapiohsomeorgv09

elementscountgroupByboundary

bboxes=Kathmandu8522768545278|

Pokhara839142281693840775282687

amptypes=way

amptime=2015-01-012017-01-01P1M

ampkeys=buildingampvalues=residential

ampshowMetadata=true

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ohsome dashboard (preview)

ohsomeorgappsdashboard

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ohsome exampleso

hso

me

org

Evolution of OSM buildings in Africa

Context HOT coordinates OSM building mapping tasks within theirMalaria Elimination Campaign

total number of OSM buildings 2008 - 2017

Processing using Big Data Frameworks (Apache Ignite Spark etc)

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Completeness

street lengths aggregated for street categories

percentage of streets which include street names

Topological correctness

percentage of intersecting OSM ways that do not share a common node

percentage of OSM endpoints close (distance 1 m) but not connected to an OSM way

User activity Number of users that edited OSM streets

Routing Nepal Earthquake 2015

httpdisasteropenrouteserviceorg

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Routing Nepal Earthquake 2015

Auer Eckle Fendrich Griesbaum Kowatsch Marx Raifer Schott Troilo Zipf (2018)Towards Using the Potential of OpenStreetMap History for Disaster Activation MonitoringISCRAM 2018 Rochester

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Evolution Topological Correctness

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githubcomGIScienceoshdb

apiohsomeorgv09swagger-uihtml

ohsomeorgappsdashboard

Want to try it yourself

zipfuni-heidelbergde

Get in touchhellip

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bull The ohsome platform enables analyses of data evolution amp quality the detection of contribution patterns etc

bull Future versions will facilitate monitoring OSM data in near-real time on a global scale and bring extended functionalities

bull Your ideas welcome

bull Further work on enhancing OSM

Conclusion amp Outlook

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Thank you very much

Alexander Zipf

GIScience Research Group

Heidelberg University

zipfuni-heidelbergde

Questions

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OSM Research Overview

Jokar Arsanjani J Zipf A Mooney P Helbich M (eds) (2015)

OpenStreetMap in GIScience experiences research applications

373p Springer Science Heidelberg Berlin ISBN 978-3-319-14279-1