<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<metadata xml:lang="en">
<Esri>
<CreaDate>20230228</CreaDate>
<CreaTime>13494800</CreaTime>
<ArcGISFormat>1.0</ArcGISFormat>
<ArcGISstyle>FGDC CSDGM Metadata</ArcGISstyle>
<SyncOnce>FALSE</SyncOnce>
<DataProperties>
<itemProps>
<itemName Sync="FALSE">Roads</itemName>
<imsContentType Sync="TRUE">002</imsContentType>
</itemProps>
<coordRef>
<type Sync="TRUE">Projected</type>
<geogcsn Sync="TRUE">GCS_North_American_1983_HARN</geogcsn>
<csUnits Sync="TRUE">Linear Unit: Foot_US (0.304801)</csUnits>
<projcsn Sync="TRUE">NAD_1983_HARN_StatePlane_Washington_North_FIPS_4601_Feet</projcsn>
<peXml Sync="TRUE">&lt;ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.0.0'&gt;&lt;WKT&gt;PROJCS[&amp;quot;NAD_1983_HARN_StatePlane_Washington_North_FIPS_4601_Feet&amp;quot;,GEOGCS[&amp;quot;GCS_North_American_1983_HARN&amp;quot;,DATUM[&amp;quot;D_North_American_1983_HARN&amp;quot;,SPHEROID[&amp;quot;GRS_1980&amp;quot;,6378137.0,298.257222101]],PRIMEM[&amp;quot;Greenwich&amp;quot;,0.0],UNIT[&amp;quot;Degree&amp;quot;,0.0174532925199433]],PROJECTION[&amp;quot;Lambert_Conformal_Conic&amp;quot;],PARAMETER[&amp;quot;False_Easting&amp;quot;,1640416.666666667],PARAMETER[&amp;quot;False_Northing&amp;quot;,0.0],PARAMETER[&amp;quot;Central_Meridian&amp;quot;,-120.8333333333333],PARAMETER[&amp;quot;Standard_Parallel_1&amp;quot;,47.5],PARAMETER[&amp;quot;Standard_Parallel_2&amp;quot;,48.73333333333333],PARAMETER[&amp;quot;Latitude_Of_Origin&amp;quot;,47.0],UNIT[&amp;quot;Foot_US&amp;quot;,0.3048006096012192],AUTHORITY[&amp;quot;EPSG&amp;quot;,2926]]&lt;/WKT&gt;&lt;XOrigin&gt;-2147483647&lt;/XOrigin&gt;&lt;YOrigin&gt;-2147483647&lt;/YOrigin&gt;&lt;XYScale&gt;3045.8952375697668&lt;/XYScale&gt;&lt;ZOrigin&gt;0&lt;/ZOrigin&gt;&lt;ZScale&gt;1&lt;/ZScale&gt;&lt;MOrigin&gt;0&lt;/MOrigin&gt;&lt;MScale&gt;1&lt;/MScale&gt;&lt;XYTolerance&gt;0.00065662140159349113&lt;/XYTolerance&gt;&lt;ZTolerance&gt;0.001&lt;/ZTolerance&gt;&lt;MTolerance&gt;0.001&lt;/MTolerance&gt;&lt;HighPrecision&gt;true&lt;/HighPrecision&gt;&lt;WKID&gt;2926&lt;/WKID&gt;&lt;LatestWKID&gt;2926&lt;/LatestWKID&gt;&lt;/ProjectedCoordinateSystem&gt;</peXml>
</coordRef>
</DataProperties>
<SyncDate>20230502</SyncDate>
<SyncTime>13335000</SyncTime>
<ModDate>20250107</ModDate>
<ModTime>9373500</ModTime>
<scaleRange>
<minScale>150000000</minScale>
<maxScale>5000</maxScale>
</scaleRange>
<ArcGISProfile>FGDC</ArcGISProfile>
</Esri>
<dataIdInfo>
<envirDesc Sync="FALSE">Esri ArcGIS 13.0.0.36056</envirDesc>
<dataLang>
<languageCode Sync="TRUE" value="eng">
</languageCode>
<countryCode Sync="TRUE" value="USA">
</countryCode>
</dataLang>
<idCitation>
<resTitle Sync="FALSE">Road_Name_Labels</resTitle>
<presForm>
<PresFormCd Sync="TRUE" value="005">
</PresFormCd>
</presForm>
</idCitation>
<spatRpType>
<SpatRepTypCd Sync="TRUE" value="001">
</SpatRepTypCd>
</spatRpType>
<idPurp>Road Name Label Layer</idPurp>
<idAbs>Road Name Label Layer created from the Roads Layer, which was created from the PenCom RCL layer with paired down fields for the public. </idAbs>
<searchKeys>
<keyword>Road</keyword>
<keyword>Name</keyword>
<keyword>Labels</keyword>
</searchKeys>
<idCredit>Clallam County IT GIS</idCredit>
<resConst>
<Consts>
<useLimit/>
</Consts>
</resConst>
</dataIdInfo>
<mdLang>
<languageCode Sync="TRUE" value="eng">
</languageCode>
<countryCode Sync="TRUE" value="USA">
</countryCode>
</mdLang>
<distInfo>
<distFormat>
<formatName Sync="TRUE">Enterprise Geodatabase Feature Class</formatName>
</distFormat>
</distInfo>
<mdHrLv>
<ScopeCd Sync="TRUE" value="005">
</ScopeCd>
</mdHrLv>
<mdHrLvName Sync="TRUE">dataset</mdHrLvName>
<refSysInfo>
<RefSystem>
<refSysID>
<identCode Sync="TRUE" code="2926">
</identCode>
<idCodeSpace Sync="TRUE">EPSG</idCodeSpace>
<idVersion Sync="TRUE">6.3(9.0.0)</idVersion>
</refSysID>
</RefSystem>
</refSysInfo>
<spatRepInfo>
<VectSpatRep>
<geometObjs Name="Roads">
<geoObjTyp>
<GeoObjTypCd Sync="TRUE" value="002">
</GeoObjTypCd>
</geoObjTyp>
<geoObjCnt Sync="TRUE">0</geoObjCnt>
</geometObjs>
<topLvl>
<TopoLevCd Sync="TRUE" value="001">
</TopoLevCd>
</topLvl>
</VectSpatRep>
</spatRepInfo>
<spdoinfo>
<ptvctinf>
<esriterm Name="Roads">
<efeatyp Sync="TRUE">Simple</efeatyp>
<efeageom Sync="TRUE" code="3">
</efeageom>
<esritopo Sync="TRUE">FALSE</esritopo>
<efeacnt Sync="TRUE">0</efeacnt>
<spindex Sync="TRUE">TRUE</spindex>
<linrefer Sync="TRUE">FALSE</linrefer>
</esriterm>
</ptvctinf>
</spdoinfo>
<eainfo>
<detailed Name="Roads">
<enttyp>
<enttypl Sync="FALSE">Roads</enttypl>
<enttypt Sync="TRUE">Feature Class</enttypt>
<enttypc Sync="TRUE">0</enttypc>
</enttyp>
<attr>
<attrlabl Sync="TRUE">OBJECTID</attrlabl>
<attalias Sync="TRUE">OBJECTID</attalias>
<attrtype Sync="TRUE">OID</attrtype>
<attwidth Sync="TRUE">4</attwidth>
<atprecis Sync="TRUE">10</atprecis>
<attscale Sync="TRUE">0</attscale>
<attrdef Sync="TRUE">Internal feature number.</attrdef>
<attrdefs Sync="TRUE">Esri</attrdefs>
<attrdomv>
<udom Sync="TRUE">Sequential unique whole numbers that are automatically generated.</udom>
</attrdomv>
</attr>
<attr>
<attrlabl Sync="TRUE">SHAPE</attrlabl>
<attalias Sync="TRUE">Shape</attalias>
<attrtype Sync="TRUE">Geometry</attrtype>
<attwidth Sync="TRUE">8</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
<attrdef Sync="TRUE">Feature geometry.</attrdef>
<attrdefs Sync="TRUE">Esri</attrdefs>
<attrdomv>
<udom Sync="TRUE">Coordinates defining the features.</udom>
</attrdomv>
</attr>
<attr>
<attrlabl Sync="TRUE">Map_Name</attrlabl>
<attalias Sync="TRUE">Map_Name</attalias>
<attrtype Sync="TRUE">String</attrtype>
<attwidth Sync="TRUE">30</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">Road_No</attrlabl>
<attalias Sync="TRUE">Road_No</attalias>
<attrtype Sync="TRUE">String</attrtype>
<attwidth Sync="TRUE">7</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">RoadClass</attrlabl>
<attalias Sync="TRUE">RoadClass</attalias>
<attrtype Sync="TRUE">String</attrtype>
<attwidth Sync="TRUE">15</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">Edit_Date</attrlabl>
<attalias Sync="TRUE">Edit_Date</attalias>
<attrtype Sync="TRUE">Date</attrtype>
<attwidth Sync="TRUE">8</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">StreetName</attrlabl>
<attalias Sync="TRUE">StreetName</attalias>
<attrtype Sync="TRUE">String</attrtype>
<attwidth Sync="TRUE">60</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">LSt_PreDir</attrlabl>
<attalias Sync="TRUE">LSt_PreDir</attalias>
<attrtype Sync="TRUE">String</attrtype>
<attwidth Sync="TRUE">2</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">LSt_Type</attrlabl>
<attalias Sync="TRUE">LSt_Type</attalias>
<attrtype Sync="TRUE">String</attrtype>
<attwidth Sync="TRUE">5</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
<attr>
<attrlabl Sync="TRUE">Shape.STLength()</attrlabl>
<attalias Sync="TRUE">Shape.STLength()</attalias>
<attrtype Sync="TRUE">Double</attrtype>
<attwidth Sync="TRUE">0</attwidth>
<atprecis Sync="TRUE">0</atprecis>
<attscale Sync="TRUE">0</attscale>
</attr>
</detailed>
</eainfo>
<mdDateSt Sync="TRUE">20250107</mdDateSt>
<Binary>
<Thumbnail>
<Data EsriPropertyType="PictureX">iVBORw0KGgoAAAANSUhEUgAAAMgAAACFCAYAAAAenrcsAAAAAXNSR0IB2cksfwAAAAlwSFlzAAAO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</Data>
</Thumbnail>
</Binary>
</metadata>
