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Data in Libraries: Open Data�

ALA RUSA Business Reference And Services Section (BRASS) Webinar

October 26, 2017

Presenter: Jennifer C. Boettcher

Slides will be sent to you after the webinar

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Jennifer C. Boettcher

Jennifer C. Boettcher and Leonard M. Gains. Industry Research Using the Economic Census. Greenwood Press: Phoenix, AZ. 2004

M.B.A., Georgetown University, Washington, D.C., 2005

M.L.S., State University of New York, Albany, N.Y.,1992

B.A., University of New Hampshire, Durham, N. H., 1987

Georgetown Univ 1997-present

Catholic Univ of America, Adjunct Faculty 03-07

Texas A&M Univ 94-97

ALA and RUSA Member since 1991

SLA Member since 1992

Founder of Business Information Finders (BIF) in DC

2013 Emerald Research Grant: Zombie List (reanimated business sources)

2010 Gale Cengage Learning Award for Excellence in Business Librarianship

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Librarian & Information Scientist

As a Librarian, I

Understand the source
Know how to find the source
Know the subjects covered
Know how it’s connected to other sources
Know how to read it
Know how to organize the source to reveal patterns
Make connections between publisher and researcher

As a Librarian, I don’t

Publish the primary source
Have your context or expertise
Do statistical analysis
Interpret the data
Do data entry
Have legal expertise

These are my views and do not reflect Georgetown or RUSA

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Copyright and Numeric Data

Facts are not copyrighted (In no case does copyright protection for an original work of authorship extend to any idea, procedure, process, system, method of operation, concept, principle, or discovery, regardless of the form in which it is described, explained, illustrated, or embodied in such work.) 17 USC 102b

Creative expression of data in compilation is protected (Feist 1991)

IN US ONLY

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Adaptations of DIKW pyramid by US Army Knowledge Managers,

from https://en.wikipedia.org/wiki/DIKW_pyramid

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Numeric Data: who is responsible

Analytics

Analysts

Knowledge
Context of numbers

Tacit Knowledge

Expert

Wisdom
“I Just know it”

Curation

Repository

Preserving access

Datum (single of data)

Researchers

Data
Creation of numbers

Statistics

Publishers

Information
Relations among numbers

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Numeric Data: who is responsible

Analytics

Analysts

Knowledge
Context of numbers

Tacit Knowledge

Expert

Wisdom
“I Just know it”

Curation

Repository

Preserving access

Datum (single of data)

Researchers

Data
Creation of numbers

Statistics

Publishers

Information
Relations among numbers

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Vocabulary

Datasets: Raw or statistical numbers, can be flat file as Comma Separated Variable (CSV) or Proprietary like Excel (see Bobray Bordelon’s RUSA Presentation)
Metadata: Variables or fields in the record (example, Author)
Application program interface (API): piece of software that interfaces between getting the data out and putting in your computer
Big data: Transactional (example, each check out)
Reports: How many checkout, usually as aggregated statistics

Open Data: Freely accessible data, created for a specific purpose, by-product of decision making

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Freely available Data: Public Domain

US Federal Government produced or funded data
Some States have data in public domain: California, Florida*, Indiana, Louisiana, Massachusetts*, Minnesota*, New Jersey*, North Carolina, District of Columbia, Puerto Rico, and the "organized territories" (incorporated or unincorporated)

*Check with issuing agency

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Articulate why Open Data exists

Funded research created for a specific purpose

US National Data
Some Other Countries
Non-Government Organizations (NGO)
Grants (mainly scientific, e.g. PubMed Central)
Publisher required (mainly scientific, e.g. Science)

By-product of research used in decision making
Fair Use and licensing restrictions may apply

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It “should be” Open Data, But I can’t get it

Privacy Concerns

Personally Identifiable Information (PII)
Health Insurance Portability and Accountability Act (HIPAA)
Family Educational Rights and Privacy Act (FERPA)

Security Concerns

Generally military and intelligence related

Financial Concerns

Contains proprietary data
Requires cost recovery
Contracts with creator don’t allow it

Licensing Issues

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Understand past, present, and future open data policy issues in the Federal Government

No single statistical office in US

Different data is collected for different reasons

Honesty in reporting (e.g. telling the IRS and Census what is income)
Methods and sampling maybe different
Quality and quantity vary depending on funding sources and congressional champions

Policy on data collection (priorities)

Mandated by law (in CFR)
Implemented by regulations (Federal Register)
Directed by memorandum (Presidential )
Standard of practice (Agencies)

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Understand past, present, and future of open data policy issues in the Federal Government

Office of Management and Budget

1^st responsibility is to create the Presidential Budget
OMB evaluates the effectiveness of agency programs, policies, and procedures, assesses competing funding demands among agencies, and sets funding priorities.

Oversight of paperwork and statistical gathering
Previous Administrations

Creation of Data.gov (2009)
OMB Revised Circular A-130: Managing Information as a Strategic Resource

“enables the data to be fully discoverable and usable by end users” (p33)

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Understand past, present, and future of open data policy issues in the Federal Government

New Head of OMB

Mick Mulvaney (as of February 16, 2017)

Was the Congressman from the 5th District of South Carolina, where he was first elected in 2010, he is the first Republican member to hold the seat in 128 years.

New Chief Statistician of the U.S. advises Head of OMB

Nancy Potok (as of January 19, 2017)

Was Deputy Director and Chief Operating Officer of the U.S. Census Bureau. She previously served at the U.S. Department of Commerce as Deputy Under Secretary for Economic Affairs, the Census Bureau's Associate Director for Demographic Programs, and the Principal Associate Director and Chief Financial Officer in charge of Field Operations, Information Technology, and Administration.

Sunlight Foundation concerns remain the same: budget cuts that could reduce quality, frequency of release or even collection, and purposeful alteration or miscommunication of research or statistical information.