<?xml version="1.0" encoding="UTF-8" standalone="no"?><metadata xml:lang="en">
<Esri>
<CreaDate>20190626</CreaDate>
<CreaTime>11544900</CreaTime>
<ArcGISFormat>1.0</ArcGISFormat>
<SyncOnce>TRUE</SyncOnce>
</Esri>
<dataIdInfo>
<idAbs>Bikeways in Toronto (Removed CP_TYPE that were blank)

The Toronto bikeways data contains bicycle lanes, signed bicycle routes and pathways. It also shows suggested routes and connections in areas where routes have not yet been designated as part of the Bikeway Network. The suggested routes and connections have been identified in consultation with experienced Toronto cyclists and the Toronto Cycling Advisory Committee.

The bikeway information is appended to the enhanced Toronto Centreline file. The Toronto Centreline is a data set of linear features representing streets, walkways, rivers, railways, highways and administrative boundaries within the City of Toronto. Each line segment is described with a series of attributes including a unique identifier, name, feature code, and address ranges (where applicable).</idAbs>
<searchKeys>
<keyword>Bike</keyword>
<keyword>Toronto</keyword>
<keyword>bikeways</keyword>
<keyword>bike lanes</keyword>
<keyword>Canada</keyword>
<keyword>ArcCanada</keyword>
<keyword>active transportation</keyword>
<keyword>cycling</keyword>
</searchKeys>
<idPurp>Bikeways in Toronto.</idPurp>
<idCredit>City of Toronto</idCredit>
<resConst>
<Consts>
<useLimit/>
</Consts>
</resConst>
</dataIdInfo>
<Binary>
<Thumbnail>
<Data EsriPropertyType="PictureX">/9j/4AAQSkZJRgABAQEAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a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=</Data>
</Thumbnail>
</Binary>
</metadata>