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Looking into the future…. Providing Social Science Data Services Jim Jacobs. First principles. Metadata are data about data -- information about information. It ’ s all about having complete, accurate, re-usable metadata.

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looking into the future

Looking into the future…

Providing Social Science Data Services

Jim Jacobs

first principles
First principles
  • Metadata are data about data -- information about information.
  • It’s all about having complete, accurate, re-usable metadata.
  • Software to process the metadata is secondary. We should be able to have metadata today that we know will be usable in unforeseeable computing environments (operating systems, software, hardware).
first principles1
First principles

Metadata should be…

  • Comprehensive
  • Complete
  • Uncompromised
  • Consistent
  • Flexible
  • Sharable
  • Usable and re-usable
  • Preservable
  • Parseable by computer
  • Documented
  • Non-proprietary
how xml fits in
How XML fits in…

XML is designed to make it easy to find and usejust the elements you need from a large document.

“Cherry picking”

how xml fits in1
How XML fits in…
  • XML is designed to be parseable with generic tools.
  • XML can encode meaning and can be self-documenting
  • XML is non-proprietary, open, flexible.
how xml fits in2
How XML fits in…

<stdyDscr>

<citation>

<titlStmt>

<titl>Great Power Wars, 1495-1815</titl>

<IDNo>9955</IDNo>

</titlStmt>

<rspStmt>

<AuthEnty>Levy, Jack S.</AuthEnty>

</rspStmt>

<prodStmt>

<fundAg>National Science Foundation.</fundAg>

<grantNo>SES86-10567</grantNo>

</prodStmt>

<distStmt>

<distrbtr abbr="ICPSR" affiliation="Institute for

Social Research, University of Michigan"

URI="http;//www.icpsr.umich.edu">Inter-university

Consortium for Political and Social Research</distrbtr>

<distDate date="1994-05-20">1994-05-20</distDate>

</distStmt>

<serStmt>

</serStmt>

<verStmt>

<dateAdded>1994-05-20</dateAdded>

<dateUpdated>1994-05-20</dateUpdated>

</verStmt>

<biblCit>Levy, Jack S. GREAT POWER WARS, 1495-1815 [Computer file].

New Brunswick, NJ and Houston, TX: Jack S. Levy and T. Clifton Morgan

<titl>Great Power

Wars, 1495-1815</titl>

You can cherry-pick just what you need from a large XML document…

from legacies to the future
From legacies to the future
  • SAS
  • SPSS
  • OSIRIS
  • PDF
  • Paper
  • Data dictionary
  • Etc.
  • HTML
  • PDF
  • Any stat package
  • Nesstar, SDA, Dataverse
  • Library OPAC
  • Google
  • OAI, METS, etc.
  • RSS, RDF
  • GIS
  • DDI 3, 4…

DDI

from many contributors to many uses
From many contributors to many uses
  • researcher
  • Data collector
  • Analyst
  • Data producer,distributor
  • Data archivist
  • Data librarian
  • Users of statistics
  • Governmentagency
  • The web
  • Live documents
  • Databases
  • publications
  • Data archives
  • Data libraries
  • Institutional repositories
  • Secondary analysis
  • New research
  • New knowledge

DDI

oais functional model

OAIS Functional Model

OAIS Functional Model

Ingest

Archival Storage

Access

data stewardship life cycle

Data Discovery

Data Repurposing

Data Dissemination

Data Production

Data Repository

Data stewardship life cycle
ddi production

Data Discovery

Data Repurposing

Data Dissemination

Data Production

Data Repository

DDI Production
ddi use

Data Discovery

Data Repurposing

Data Dissemination

Data Production

Data Repository

DDI Use
ddi will enable transformation
DDI will enable transformation
  • New kinds of data discovery (beyond “indexing”)
  • Metadata as a primary resource (metadata as data)
metadata for data discovery
Metadata for data discovery
  • ICPSR uses DDI metadata to create its Variables database.
  • Nesstar and Dataverse software use metadata to produce searchable indexes of data repositories
metadata for data discovery1
Metadata for data discovery
  • Harvesting of DDI from many repositories to create indexes across collections should become common. (oclc.org/oaister/)
  • Data discovery by concept and methodology and geography and time period, not just keyword, can become the new norm.
metadata as data
Metadata as data

When we use DDI 3, we are creating digital information that is structured according to processes and functions:

  • DDI 3: Study Concept, Collection, Processing, Distribution, Archiving, Discovery, Analysis, Repurposing.
metadata as data1
Metadata as data

When we use DDI 3, we are creating digital information that is structured according to processes and functions

By doing this, we are creating data! We can treat “metadata” as data.

  • Researchers will analyze metadata the way we would analyze any data file.
metadata as data2
Metadata as data
  • As we create and preserve more metadata of this kind, we are creating a new body of knowledge.
  • We are accumulating a body of information that makes it possible to study trends across time and geography.
metadata as data an example
Metadata as data: an example
  • The technical documentation for the Army's Korean conflict casualty electronic records file has casualty codes that were never used in the data files.
  • The presence of codes in the metadata for injury by lethal gas and by radiation exposure suggests that Army personnel who designed this record-keeping system expected the possible use of those as weapons. Examination of the data alone would have missed this suggestion.
metadata as data an example1
Metadata as data: an example
  • The codes for 'place of casualty' included, in addition to South Korea Sector and North Korea Sector, the Indo-China Sector, Tibet Sector, Mongolia Sector, Honan Sector (sic), Manchuria Sector, North Japan Sector, South Japan Sector, South China Sector, and Formosa Sector."
metadata as data another example
Metadata as data: another example
  • A researcher at the Danish Data Archive is doing a qualitative analysis of the questionnaires used in seven surveys about ethnic minorities in Danish society, "with the purpose of showing how surveys ... mirror and project societal understandings of the subjects under investigation."
metadata as data yet another example
Metadata as data: yet another example
  • Wendy Thomas of the Minnesota Population Center examined U.S. Census metadata from 1790 through 2000 and compared the changing concept of race and ethnicity as embodied in the categories used by the Census Bureau questions over time. Those concepts are only documented in the metadata, not the Census data files themselves.
metadata as data yet another example1
Metadata as data: yet another example

Politics in Race / Ethnicity / Ancestry: Mining the Metadata for Answers

Wendy L. Thomas

Minnesota Population Center

Presented at: APDU 2004, 18 October 2004