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RETS Overview

RETS Overview . New Topic. What is RETS? RETS background RETS benefits to real estate industry stakeholders RETS source code examples. Topic Objectives. Build familiarity with RETS Understand RETS benefits Identify opportunities to employ RETS. RETS is delivering real benefits.

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RETS Overview

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  1. RETS Overview New Topic • What is RETS? • RETS background • RETS benefits to real estate industry stakeholders • RETS source code examples

  2. TopicObjectives • Build familiarity with RETS • Understand RETS benefits • Identify opportunities to employ RETS RETS is delivering real benefits

  3. What is RETS?An IT Standard • Open standard for exchanging real estate data • RETS is not closed or hidden • A standard described in a document • RETS is not software RETS meets the needs of real estate industry stakeholders

  4. What is RETS?Technical Principles • Enables data suppliers to provide access to data • Uses a standard data access interface • Applies widely-used concepts • Uses Internet standards where possible Sample RETS implementations are available

  5. What is RETS?Community Organization • Organized and funded by NAR • Regular meetings sponsored by NAR • Attended by all interested companies & individuals • Improvement ideas sought from industry participants • RETS standard is changed by Change Proposals • Workgroups address details of the RETS standard • Plugfests are held to establish interoperability • Compliance certification is available

  6. Who is Using RETS? Prepared by: RETS Overview • 40 of the top 59 MLS - hold 50% of listings • All of Rapattoni’s 89 MLS customers • All of Interealty’s 38 MLS customers • Marketlinx’s 26 of 27 MLS customers • FNIS - 16 of approximately 300 MLS customers • Custom in-house MLS systems: • MRIS • Denver Metrolist

  7. How do RETS Clientsand Servers interact? Query syntax Result set Realtor client MLS server

  8. What is RETS Used for? • Data pulls for MLS data customers: • Homestore & other data aggregators • IDX/VOW web sites • Brokerage systems • Newspapers/book publishers • Statistical summary/market trend analysis • Attach a given client software product to multiple brands of MLS servers • PC, laptop, PDA, cell phone

  9. What themes motivateddevelopment of RETS? • High software development costs for data distribution • Inability to plug clients into multiple MLS systems in an economic way • High IT support costs Pain leads to action

  10. When didRETS development start? • Development began in 1999 • Collaborative effort between NAR and a number of industry technology leaders • Driven by need to make access to and transfer of MLS information easier • Versions 1.0 and 1.5 of RETS have been adopted by: • most of the major RETS service providers • many of the RETS service consumers

  11. RETS Value Propositionfor each Stakeholder • MLS Organizations & Staff • Brokers • MLS Service Providers • MLS Data Consumers • MLS Customers • Consumers • Fostering Innovation Read the full set of values for all stakeholders: www.rets.org/retsvalue/

  12. RETSExample Specification Text 7.7.3 Sub-queriesThis query language provides for a nesting of sub-queries. For example:Query=((AREA=|1,2)|(CITY=ACTON)),(LP=200000+)Example: Query=(ST=|ACT,SOLD), (LP=200000-350000), (STR=RIVER*), (STYLE=RANCH), (EXT=+WTRFRNT,DOCK), (LDATE=2000-03-01+), (REM=*FORECLOSE*), (TYPE=~CONDO,TWNHME), (OWNER=P?LE)Verbally, this would be interpreted as “return properties with (ST equal ACT or SOLD) and (LP between 200000 and 350000, inclusive) and (STR beginning with RIVER) and (STYLE equal RANCH) and (EXT equal WTRFRNT and DOCK) and (LDATE greater than or equal to 2000-03-01) and (REM containing FORECLOSE) and (TYPE not equal toCONDO and not equal to TWNHME) and (OWNER starting with P and having LE in the 3rd and 4th characters).”

  13. RETSMetadata Example <METADATA-RESOURCE Version="1.1.3" Date="Mon, 24 Feb 2003 …“ > <COLUMNS> ResourceID StandardName VisibleName ... </COLUMNS> <DATA> Property Property Property ... </DATA> <METADATA-CLASS Resource="Property" Version="0.0.0" ... > <COLUMNS> ClassName VisibleName StandardName ... </COLUMNS> <DATA> RES Single Family Residential ... </DATA > <METADATA-TABLE Resource="Property" Class="RES“ Version ..."> <COLUMNS> SystemName StandardName LongName ... </COLUMNS> <DATA> EF ExtFeat Features </DATA > <DATA> AR MLSArea MLS Area ... </DATA >

  14. RETSCompact Decoded Query Example http://rets.ftc2.com:6103/search?SearchType=Property&Class=RES&Count=1&StandardNames=1&Select=Stories,YearBuilt,Style&Limit=10&Format=COMPACT-DECODED&QueryType=DMQL&Query= (ListPrice=50000-420000), (County=|HAMILTON-OH), (ListingStatus=|Active), (ListDate=2003-09-05+)

  15. RETS Compact Decoded Results Example <RETS ReplyCode="0" ReplyText="V1.1.6 : Success"><COUNT Records="3" /><DELIMITER value = "09"/><COLUMNS> Stories YearBuilt Style </COLUMNS><DATA> 3 1979 Colonial </DATA> <DATA> 1 1998 Rancher </DATA> <DATA> 3 1908 Cottage </DATA> </RETS>

  16. RETS XML Query Example http://rets.ftc2.com:6103/search?SearchType=Property&Class=RES&Count=1&StandardNames=1&Select=Stories,YearBuilt,Style&Limit=10&Format=STANDARD-XML&QueryType=DMQL&Query= (ListPrice=50000-420000), (County=|HAMILTON-OH), (ListingStatus=|Active), (ListDate=2003-09-05+)

  17. RETS XML Results Example <RETS ReplyCode="0" ReplyText="V0.9.8 Success"><COUNT Records="5" /><REData> <Properties> <ResidentialProperty>… <Stories>3</Stories> <YearBuilt>1979</YearBuilt> <Heating></Heating> <Cooling /> <Pool>None</Pool> <Type></Type> <Style> Colonial </Style>…

  18. RETSComponents • Transport http • Request http parameters • Query form DMQL • Output data formats compact compact decoded XML • Output metadata formats compact XML

  19. TopicSummary • RETS offers a comprehensive solution to improve real estate industry data distribution • RETS provides benefits to all industry stakeholders: • improved timeliness of data • reduced operating costs • increased revenue Discussion Time

  20. InnovativeTech Support

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