Participatory Mapping andParticipatory Mapping andParticipatory Mapping and Volunteered Geographic InformationParticipatory Mapping and Volunteered Geographic InformationSeth Peery, Sr. GIS Architect

Social Media for Planning April 22, 2011Virginia Tech Geospatial Information Sciences

OverviewOverviewOverviewOverview• Overlaps between GIS and “social media”

• Participatory Mapping and Citizen Sciencep y pp g• Public Participation GIS• Volunteered Geographic Information• Mashups and Web Servicesp

• Applications• Popular examples• Virginia Tech participatory mapping projectsVirginia Tech participatory mapping projects

• Best practices • Design considerations for collecting data from the public• Validity and use of VGI• Validity and use of VGI

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OpenStreetMapOpenStreetMapOpenStreetMapOpenStreetMap

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Google Map MakerGoogle Map MakerGoogle Map MakerGoogle Map Maker

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Blacksburg Bike Survey::Data CollectionBlacksburg Bike Survey::Data Collection

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Blacksburg Bike Survey::AnalysisBlacksburg Bike Survey::Analysis

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Virginia Tech eCorridors Broadband MapVirginia Tech eCorridors Broadband Map

• Started in 2006

• Combines NDT with a Google Maps front-end

• Nearly 5000 data points to date, and growing

7http://www.ecorridors.vt.edu/maps/broadbandmap

Advertised vs. Measured PerformanceAdvertised vs. Measured PerformanceSBDD Max Advertised Download Speed

< 200 mbps

200kbps - 768 kbps

768 kbps - 1.5 mbps

1 5 mbps 3 mbps1.5 mbps - 3 mbps

3 mbps - 6 mbps

6 mbps - 10 mbps

10 mbps - 25 mbps

25 mbps - 50 mbps

50 mbps - 100 mbps

100 mbps - 1 Gbps

> 1 Gbps> 1 Gbps

Virginia Tech NDT Test Data Pointsunder 200 kbps

200kbps - 768 kbps

768kbps - 1.5 mbps

1.5mbps - 3 mbps

3mbps - 6 mbps

6mbps - 10 mbps6mbps - 10 mbps

10mbps - 25 mbps

25mbps - 100 mbps

over 100 mbps

80 1 2 3 40.5

Miles

Network Performance Data in GISNetwork Performance Data in GISVirginia Data Points

under 200 kbps

200kbps - 768 kbps

768kbps - 1.5 mbps

1.5mbps - 3 mbps5 bps 3 bps

3mbps - 6 mbps

6mbps - 10 mbps

10mbps - 25 mbps

25mbps - 100 mbps

over 100 mbps

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Effect of AccelerateVirginia CampaignsEffect of AccelerateVirginia CampaignsSample Size

0

1 - 5

6 - 10

11 - 25

26 - 100

101 - 644

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Generalization by Areal UnitGeneralization by Areal Unit

Vi i i D t P i t

CountiesBlocks

Virginia Data Pointsunder 200 kbps

200kbps - 768 kbps

768kbps - 1.5 mbps

1.5mbps - 3 mbps

3mbps - 6 mbps

6mbps - 10 mbps

10mbps 25 mbps10mbps - 25 mbps

25mbps - 100 mbps

over 100 mbps

Average DownloadAvg_downlo

no data

under 200 kbps

200 kbps - 768 kbps200 kbps - 768 kbps

768kbps - 1.5 mbps

1.5 mbps - 3 mbps

3 mbps - 6 mbps

6 mbps - 10 mbps

10 mbps - 25 mbps

25 mbps - 100 mbps

over 100 mbps

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over 100 mbps

Areal Averages used in AnalysisAreal Averages used in Analysisg yg y

County-level aggregated map data

County business patterns

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y p

InterpolationInterpolationKriging Predicted Values

0.002038659

0.002038659 - 0.2

0.2 - 0.768

0.768 - 1.5

1.500000001 - 3

3.000000001 - 6

6.000000001 - 10

10.00000001 - 20

20.00000001 - 92.98016357

92.98016358 - 100

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Economic Development ResearchEconomic Development Research

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Designing Interfaces for VGIDesigning Interfaces for VGIDesigning Interfaces for VGIDesigning Interfaces for VGI• CONSTRAIN USER INPUT as much as possible!• List boxes are preferable to free-form text• Collect as much metadata as you can (IP, timestamp, zoom level, other map

variables) for later filtering use• “Users are evil” – protect against SQL injection (but also junk data)… validate,

validate!• Decide on level of isolation between the users and the data

– Writing directly to production – Writing to a staging DB

Human approval required first (Moderation)– Human approval required first (Moderation)• All VGI is spatial, but not all VGI is GIS – ESRI stack vs. traditional DBs (e.g.,

MySQL)• Protection of PII (and… getting useful data vs. getting a usefully large sample

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size)• Spatial unit of VGI – smaller is better

Data Ingestion and AnalysisData Ingestion and AnalysisData Ingestion and AnalysisData Ingestion and Analysis• Workflow depends on research questions and software platform for

analysis• Data may have been collected in different format than required for

analysis• For GIS, we can ingest csv/txt as XY data – more direct import into

SAS/SPSS/R/etcSAS/SPSS/R/etc.• Need to eliminate outliers and obvious errors – use as much metadata

as you can – but note impacts of doing this on sample size• Spatial generalization points to polygons averages sums• Spatial generalization – points to polygons, averages, sums.• Suitability for interpolation?• Mapping underlying pattern vs. mapping the distribution of

responsesresponses

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Validity ThreatsValidity ThreatsValidity ThreatsValidity Threats• VGI/geospatial crowdsourcing methodologically similar to a survey instrument• Sampling bias – spatial/other• Precision/accuracy of VGI spatial data• Correctness of attribute data (assertion)• Credibility of VGI [1] y

• Authority vs. credibility• Uniqueness, situation, formal training• Perception of accuracy and provenance

• User input mistakes vs systematic abuse (astroturfing)• User input mistakes vs. systematic abuse (astroturfing)• Identification and filtering of outliers• Uncertainty and how to quantify it

[1] Flanagin, A. J. and M. J. Metzger (2008). "The credibility of volunteered geographic information." GeoJournal 72: 137.

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Contact InformationContact InformationContact InformationContact Information

Seth PeerySeth PeerySenior GIS Architect, Enterprise GISVirginia Tech Geospatial Information Sciences2060 Torgersen Hall (0197), Blacksburg, VA 24061(540) 231-2178sspeery@vt edusspeery@vt.eduhttp://gis.vt.edu