1. Threats to Open Data: Implications for Library Collections and Services
Michele Hayslett and John N. Vickery
IASSIST 2007
McGill University, Montréal, Québec, CANADA
May 15-18, 2007

2. Introduction
“Open Data is the single most important problem in data-driven science.”
Peter Murray-Rust
University of Cambridge
“scientific datasets are the modern equivalents of medieval manuscripts. “
Sayeed Choudhury
Johns Hopkins University

3. Introduction Threats: Infrastructure Commodification of data Metadata
Research Culture
Legislation and Intellectual Property

4. Infrastructure: the challenges
Version tracking and migration
What version is most current
Workable across diverse computing platforms
Permission controls
To foil mischief-makers
To give appropriate parties appropriate rights
Flexibility
Perform multiple functions (lab notebook [date stamping], data analysis, paper drafts, data preservation, etc.) within one application
Store multiple data types (images, numbers, sound, etc.)

5. Infrastructure: the implications
Advantages of data repository over home-grown solutions
Necessary to liaise with IT departments as well as faculty
Build in-house expertise and act as translators
Take the lead in cost-sharing
On the basis of existing arrangements
New initiatives

6. Infrastructure: the implications
Leverage expertise
Preservation
Metadata and Organization
Collections
Reallocate staff and resources
Become central players in a domain that includes….
Industry, supercomputing initiatives, professional societies, government, etc.

7. Commodification of data: the challenges
Data as commodity

8. Commodification of data: the challenges
Publication requirements
Gaining prevalence in the sciences
Publishers are well aware of the value of data
Publishers and computing companies will add on more sophisticated information services

9. Commodification of data: the implications
Value added products and services
Will be requested by researchers
Libraries must be prepared to pay for these products
Allocating money for datasets
Not a traditional part of libraries budgets
Weigh costs and benefits

10. Commodification of data: the implications
Open vs. proprietary products
Institutional data repositories
Participation in open data initiatives
Who will own the data?

11. Metadata creation: the challenges
Agreeing on standards…
”is like Middle-East peacekeeping —
every detail has to be worked out
and agreed on.”
– Martin Elvis, Harvard-Smithsonian Center for Astrophysics
Standards are even more difficult across multiple disciplines and data formats
Scale of project is also an issue

12. Metadata creation: the implications
Libraries have metadata expertise and need to bring the resources to solve the problem
Provide proven models in DDI and varied repositories
Librarians/Libraries as data managers on research projects?
Could libraries take over the role of metadata creation?
Requires re-alignment of legacy departments
LOC no longer doing series authority files
Considering dumping subject headings

13. Research culture: the challenges
Lack of priority for metadata creation
“The task of entering metadata is something that people appear to resist unless it is mandated in their job descriptions or through other enforcement mechanisms." – Schweik, Stepanov and Grove (2005)
Need for community-wide codes of practice
National Academies of Sciences
UPSIDE: Uniform Principle for Sharing Integral Data and Materials Expeditiously
Trust necessary discipline-wide (no scooping)

14. Research culture: the challenges
Emphasis on confidentiality
“competitive edge of data secrecy“
– Mike Carroll, Villanova Law School
Academic advancement
ability to claim credit – track origination with data
on what basis – award collaboration
Change from the inside necessary

15. Research culture: the implications
Can serve as examples and provide education on these issues
“…there is an underlying “science” to organizing documents…Many team members may not possess these important skills. ” – Schweik, Stepanov and Grove (2005)
Serve as neutral party to build community of trust
Serve as mediator between university and larger open data projects

16. Legislation and IP: the challenges
Legislation to protect datasets/databases
Data in U.S. vs. Data in E.U.
H.R. 3261: Database and Collections of Information Misappropriation Act (failed)
To protect or not?
National Research Council’s Committee on Responsibilities of Authorship in the Biological Sciences said yes
Open Data advocates say no
Existing legislation, rules ineffective
Shelby Amendment; Information Quality Act
NIH requirement - data publicly available within 6 mos.

17. Legislation and IP: the implications
License vs. copyright
Licensing
Time
Money
What would change if data were protected?

18. Summary Challenges Opportunities Infrastructure
Commodification of data
Metadata
Research Culture
Legislation/IP
Opportunities
Liaise between stakeholders
Capture data at the source
Provide expert help
Build community of trust
Manage access

19. Questions Michele Hayslett michele_hayslett@ncsu.edu John N. Vickery

20. Questions for You How many of you are planning data repositories?
How many of your institutions have a repository architect in the library or plan to hire one?