Data Infrastructure Services for Data Curation

Jian QinSchool of Information Studies

Syracuse UniversitySyracuse, New York

ALA 2015, San Francisco, CA 2015-06-28

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Data infrastructure

“a sustainable data infrastructure that will be discoverable, searchable, accessible, and usable to the entire research and education community.”

“usable by multiple scientific disciplines…”

“…that can support and provide data solutions to a broader range of scientific disciplines while reducing duplicative efforts.”

http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=504776

Nature of an infrastructure• Embeddedness. Infrastructure is sunk into, inside of, other

structures, social arrangements, and technologies.• Transparency. Infrastructure does not have to be reinvented

each time of assembled for each task, but invisibly supports those tasks.• Reach or scope beyond a single event or a local practice.• Learned as part of membership. • Links with conventions of practice. • Embodiment of standards. • Built on an installed base.• Becomes visible upon breakdown.• Is fixed in modular increments, not all at once or globally.

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Star, S.L. & Ruhleder, K. (1996). Steps toward an ecology of infrastructure: Design and access for large information space. Information Systems Research, 7(1): 111-134.

Capability of infrastructural services

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Safe haven

DOI minting

service or

related support

Active data

storage

Data catalog

Data repository

Institutional repository

Code of good research practice

Institutional

research strategy

Data governance /

Access committee

Institutional RDM policy or aspirational

statementOpen access policy

Source: http://www.dcc.ac.uk/projects/opd-for-rdm

5

Data infrastructure services

Library & info services

Data science IT

management

Data infrastructure

services

Data services

Data infrastructure

Library IT

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Data repositories

Publication repositories

Scenario: Data repositories

Institutional repositories

Community repositories

Subject repositories

Links between data and

publications

Separate or combined?

Relations?

May be at institutional and/or community levels

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A broader view of RDM: data science

“An emerging area of work concerned with the collection,

presentation, analysis, visualization, management, and preservation of large collections of information.”

Stanton, J. (2012). Introduction to Data Science. http://ischool.syr.edu/media/documents/2012/3/DataScienceBook1_1.

pdf

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Building data infrastructure services

“It’s all about transformation”

http://www.arl.org/storage/documents/publications/2012-hrsym-pres-neal-j.pdf

• To change in composition or structure (what we are/what we do)

• To change the outward form or appearance (how we are viewed/understood)

• To change in character or condition (how we do it)

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The keyword for data infrastructure services is:

Capacity Building

Research Data Management

Insti

tutio

naliz

ation

Infrastructure

Standards

Policy, procedures,

training, best practice,

compliance, IP

protection and rights

Networks, systems, databases, software tools, data services

Data format

standards,

metadata

standards,

ontologies,

controlled

vocabularies/taxon

omies

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Start it the right way

• Repeatable• Sustainable financially and technically• A community of practice• Institutionalization • Collaboration and coordination• Conformance to regulations and laws

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Capacity building: RDM human capital– Deep Subject, Process, or Technical Expertise – Deep Service Commitment – Commitment to Research and Development – Commitment to Assessment and Evaluation – Communication and Marketing Skills – Project Development and Management Skills – Political Engagement – Resource Development Skills – Commitment to Rigor – Entrepreneurial Spirit – Commitment to Collaboration – Leadership/Inspirational Capacityhttp://www.arl.org/storage/documents/publications/2012-hrsym-pres-neal-j.pdf

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MS in Library and Information Science

CAS in Data Science

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Thank you!

http://ischool.syr.edu/