Data Management Plans: Approaches to Dissemination and Preservation

1
Data Management Plans Approaches to
Dissemination and Preservation

• Micah Altman
• Archival Director, Henry A. Murray Research
  Archive
• Associate Director, Harvard-MIT Data Center
• Senior Research Scientist, Institute for
  Quantitative Social Sciences

Portions of this presentation based on joint
work with Charles Franklin, forManaging Social
Science Research Data (Forthcoming 2008, Chapman
Hall). However, all errors are certainly my own.
2
Contents

• Context of a data management plan
• Technologies for Dissemination
• Technical and Institutional Approaches to
  Preservation

3
Data Lifecycle

• Collection
• Data Entry Verification
• Processing
• Identifier assignment
• Internal metadata
• Coding
• Merging
• Cleaning
• Research and Publication Support
• Documentation, Dissemination
• Archiving
• Recoding, Secondary Analysis, Merging
• ( and back to the beginning)

(Rinse, Lather, Repeat)
4
Whats Wrong with the Previous Slide

• Data is changed all the time.
• What metadata?
• Publications emerge before processing(the
  conference is next week)
• Dissemination happens early (sometimesmaybe if
  I know you)
• Much data is never archived

(So, I lied)
5
Questions to ask when developing a Data
Management Plan

• Who are the stakeholders?
• What do the stakeholders require and want?
• How does the plan engage with the data lifecycle
  to ensure these things?
• What are the motivating questions, use cases,
  scenarios?
• (Example) How do I update all of my tables and
  figures correctly, when I add the new data the
  reviewers suggested?
• (Example) Can I prove the direct connection from
  data collection to publication, before a hostile
  prosecutor, in court?

6
Stakeholders and Legal Requirements
7
Stakeholders Implicated as Information Flows
8
Elements of Dissemination

• Dissemination ? promoting use
• Discoverability
• Accessibility
• Comprehensibility
• (Oh yeah, ease of ingest that too.)

9
Emerging Technologies for Dissemination

• Institutional Repositories
• Web services
• Virtual-hosted archives

Plus Ça Change, Plus C'est Fou (Translation
The more things change the more they stay insane)
10
Institutional Repositories

• Some tradeoffs when used for data
• Generality vs. domain-specific services
• Institutional adoption vs. use within
  institution
• Preservation motive vs. Dissemination
• None of these tradeoffs is fundamental, but
  reflect current stage of evolution

11
A Web Services Rhebus



?


Can you count how many ?s are in this picture?
12
Archival Virtual Hosting

• Its virtual
• Noting to install
• Virtual collections
• Institutionally supported
• Persistent identifiers and citations
• No worries about file formats changing, backups,
  etc.
• All the initial setup work is done for you
• You retain total control over
• content
• Access
• presentation
• Get it now, well set it up and load the data,
  for free.

13
http//dvn.iq.harvard.edu/dvn
14
Dissemination Options Stakeholders and Lifecycles
See, Desmond Dekker
15
Elements of Preservation

• Preservation ? ensuring the possibility of use
• Finding, selecting, acquiring intellectual
  objects
• Identifying intellectual content
• Safeguarding
• Verifying

16
Early 19th Century Thinking on Digital
Preservation

• I met a traveler from an antique land Who said
  "Two vast and trunkless legs of stone Stand in
  the desert... Near them, on the sand, Half sunk
  a shattered visage lies, whose frown, And
  wrinkled lip, and sneer of cold command, Tell
  that its sculptor well those passions read Which
  yet survive, stamped on these lifeless things,
  The hand that mocked them and the heart that
  fed And on the pedestal these words appear My
  name is Ozymandius, King of Kings, Look on my
  works, ye Mighty, and despair!Nothing beside
  remains. Round the decay Of that colossal wreck,
  boundless and bare The lone and level sands
  stretch far away.
• Only half the digits were preserved.

17
Technical Strategies to Preservation

• Musical Chairs (media format migration)
• Bag and Tag (save as is, decide on action
  later)
• Assume a Can Opener (Universal Virtual
  Computer)
• RomZ and EmuZ (emulation)
• Freeze-Dry (save a reduced version)

18
Institutional Strategies for Preservation

• Ignore it, maybe someone else will take care of
  it
• (internet archive, )
• Well always be here
• (self-preservation)
• We are ever true to Insert Alma Mater
• (institutional archives)
• Ask someone else do it
• (ICPSR, MRA, Roper, )
• Ask someone(s) else do it
• (Data-PASS, Meta-Archive, ClockSS)
• Trust No One
• (LOCKSS)

All quotes are entirely fictional -)
19
Dissemination and Preservation (Mix Match
Examples)

• Refactor web pages (slightly) to facilitate
  LOCKSS (lots of journals!)
• Deliver NARA content in Dataverse Network
  (HARVARD, NARA, CENSUS)
• Harvest dataverse content into DSPACE. (MIT,
  HARVARD)
• Replicate dataverse content in SRB (UNC)
• Dataverse Datapass

20
Potential Nexuses for Preservation Failure

• Technical
• Media failure storage conditions, media
  characteristics
• Format obsolescence
• Preservation infrastructure software failure
• Storage infrastructure software failure
• Storage infrastructure hardware failure
• External Threats to Institutions
• Third party attacks
• Institutional funding
• Change in legal regimes
• Quis custodiet ipsos custodes?
• Unintentional curatorial modification
• Loss of institutional knowledge skills
• Intentional curatorial deaccessioning
• Change in institutional mission

21
Institutional Preservation Strategies --
Corollaries

• There are potential single points of failure in
  both technology, organization and legal regimes
• Diversify your portfolio multiple software
  systems, hardware, organization (e.g., Data-PASS
  -)
• Find international partners
• Many combinations of preservation dissemination
  strategies are compatible
• Layer technologies and strategies
• Leverage dissemination (in a planned way) for
  preservation (and vice-versa)
• Preservation is impossible to demonstrate
  conclusively
• Consider organizational credentials
• No organization is absolutely certain to be
  reliable

22
More Information

• Get a Dataverse at IQSS Now
• http//dvn.iq.harvard.edu/dvn
• Dataverse Network Software
• http//TheData.Org
• Data-PASS
• http//www.icpsr.umich.edu/DATAPASS/