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SDMX 2007 global conference presentation - The FRB and XML.ppt

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					  The FRB and SDMX:
National data and International
          standards

           San Cannon
      Federal Reserve Board
          SDMX Conference
          9-11 January 2007
Background
• The Fed is a statistical agency as well as a
  central bank and regulatory agency.
• Lots of data and information are available on the
  public website.
• Statistical data are varied: monthly industrial
  production indexes, daily interest and exchange
  rates, quarterly financial flows for various sectors
  of the economy, surveys of small businesses
  and consumers, etc.


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  9-11 January 2007
Serving our users better
To some, it may appear that the statistical agency
  role is secondary.
• Data are not always easy to find.
• Downloads are not customizable.
• Example: Trying to extract one industrial
  production series requires retrieving two text
  files, cutting and pasting, reformatting….
• Complete – yes. User Friendly – no.



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Data Download Program (DDP)
• XML designated as key format but project team
  wrestled with implementation details.
• Staff weighed a homegrown DTD setup against
  the new SDMX standard.
• SDMX looked to have greater benefits and was
  adopted.
• Good decision: additional internal applications
  as well as interagency projects using SDMX are
  in the works.



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 9-11 January 2007
A lot to learn
• SDMX is based on data structure definitions
  („key families‟) and codelists, with every concept
  represented by a code with a corresponding
  definition.
• We were unfamiliar with this type of data
  modeling, so it proved challenging.
• Two of our pilot datasets translated easily to this
  new format; others needed more work.



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Data structures differ
Some data structures are readily adapted to the
  concept/codelist representation. Series “keys”
  have no real mnemonic value.

HBBA           Int. Rate, Official, Discount rate/Base rate
HBCA           Int. Rate, Official, Intra-day loans
SCBA           Indust. Production, Motor vehicles, NSA
SCBB           Indust. Production, Motor vehicles, SA


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Hierarchical relationships
We allow data to be modeled hierarchically, and use
  mnemonics that reflect this.
RIFSPFF_N.B                       JQI_I02Y3361T3_N.M:
R.*:Rate                          J.*:Indices except of prices
R.I.*:Rate of interest in money   J.Q.*:Production
and capital markets               J.Q.I.:Industrial
R.I.F.*:Federal Reserve System    _I.*:NAICS-based industry
R.I.F.S.*:Short-term or money     classification
market                            02Y:codes from year 2002
R.I.F.S.P.*:Private securities    3361.:Motor Vehicle Manufacturing
R.I.F.S.P.FF.:Federal funds       T:thru
_N.:Not seasonally adjusted       3363:Motor Vehicle Parts
.B:Business (Five days, Monday-   Manufacturing
Friday)                           _N.:Not seasonally adjusted
                                  .M:Monthly
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   9-11 January 2007
Applying the SDMX model
• Data represented by a concrete number of concepts are
  much easier to represent with key family dimensions and
  attributes:
   JQI_I02YMF_N.M            → Topic_Industry_SA.Freq
   FA156900005.Q             → Prefix (2 digits), Sector (2),
      instrument type (5), series type (1), frequency
• Hierarchical relationships and varying number of concepts
  makes life more difficult:
   RIFSPPNA2P2D30_N.B → Topic?_SA.Freq
   RIFLGFCY20_XII_N.B → Topic?_Inflate_SA.Freq

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Decisions we made
• Allow a variable number of data structure
  definitions per dataset.
• Use the compact format for internal
  exchange and external downloads.
• Stick with SDMX 1.0, for now.
• Use a relational database to store data
  and XML information for retrieval.

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 9-11 January 2007
Final product: DDP!
•      We have a flexible application whose interface
       is entirely driven by the data structure
       definitions.
•      “We store the XML as carefully sliced text in a
       relational database and we can build an index
       structure that allows us to respond to ad-hoc
       queries very efficiently, even for large volumes
       of data.”
                        Data Download Program


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Strengths and weaknesses
• Because interface is entirely data driven, it is
  easy to add new data.
• Internal architecture is complex, due to security
  and the data workflow:
   – SDMX files are generated by data staff and
     transmitted to public website staff for processing.
   – These files are made available on the website and
     “shredded” for database entry and lookup.
• Current structure is not set up for codelist
  sharing.


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What do the users say?
•      “Really excellent. One of the
       best I’ve used on the web.”

•      “This Data Download thing is
       better than sliced bread.”

•      “I downloaded the XML files, but I
       cannot run them. All I see is the
       xml code.”

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What do the numbers say?
•      More than 250,000 unique visits since April –
       about 50,000 per month.

•      Data Download Program is the 6th most visited
       area on the Federal Reserve website.




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    9-11 January 2007
Next steps
• Add more data: reserves, exchange rates,
  consumer credit.

• Continue working with other central banks and
  statistical agencies on common framework.

• Prepare to move to SDMX 2.0 to take advantage
  of additional features.



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  9-11 January 2007
The last slide…

                      Questions? Comments?

                  Thank you for your attention!

                           San Cannon
                        scannon@frb.gov
                         (202) 452-3710

  SDMX Conference                                 15
  9-11 January 2007

				
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