Building an interdisciplinary

research program in an academic library

James L. Mullins Dean of Libraries

D. Scott Brandt

Associate Dean for Research

Coalition for Networked Information

April 4, 2006

Purdue University

National Science Board, Long-Lived Digital Data Collections: Enabling Research and Education in the 21st Century. National Science Foundation, September 2005. p.10

National Problems

Long-lived data collections - powerful catalysts for progress

Need for digital collections – increasing rapidly

NSB & NSF – leadership - comprehensive strategy - consistent policy framework

Petabytes of Data

Genomics datasets – NCBI of NLM Atmospheric Data – climate change,

weather prediction Geographical Information – seismological Astronomical Data – space exploration Nanotechnology – miniaturization of systems Nuclear engineering – maintenance of nuclear

reactors

from National Science Board, Long-Lived Digital Data Collections: Enabling Research and Education in the 21st Century. National Science Foundation, September 2005. p.10

National Environment

Policies & strategies – developed to facilitate management, preservation, and sharing of digital data – embrace heterogeneity in technical, scientific and other features found across the spectrum of digital data collections

Scientific and Technical Researchers – data proliferation

Organization and retrieval of data – the challenge

Solution - not apparent Information Technologists, Computer

Scientists, and Statisticians – “not our problem”

Funding agencies - assess proposals partiallyon data management plan

Assumptions

Policies

Interdisciplinary collaboration required Inter-institutional collaboration highly desirable Funding sources must be shared and clear –

external funding highly desirable Results must be replicable & contributed to academe NSF/NIH definitions of massive datasets accepted Curation of data is not new, libraries have been archiving raw data for centuries

Researchers want:

consistent access to their own data, now and in the future

informed (metadata) access to data of colleagues to share data through distributed access or duplication of data-set help in gaining this access

The Needs

Taxonomy - categorization of data per research area Storage/Curation – management of data Metadata - data description to assist “data mining” Meta Search – locate and download data Distribution Grid – transmission

The Opportunities

Taxonomy - disciplinary scientists, computer scientists and librarians Storage/Curation – information technologists and librarians Metadata – librarians Meta Search – computer scientists and librarians Distribution Grid – information technologists

PurduePurdue University

Nine Colleges: Agriculture, Consumer & Family Sciences, Education, Engineering, Liberal Arts, Management, Pharmacy/ Nursing/Health Sciences, Technology, Vet Medicine

73 Departments, several cross-disciplinary: e.g. Agricultural & Biological Engineering

Strategic directions

University: “interdisciplinaryand collaborative endeavors grounded in the strengths of academic disciplines”

Libraries: “Libraries faculty are better integrated into campus research agenda”

Interdisciplinary collaboration

Cyber Infrastructure

Oncology

Manufacturing

Energy

Nanotechnology

Bioscience

DiscoveryPark

Discovery Park: Ten recent interdisciplinary centers which are designed to facilitate and promote leading edge research

Entrepreneurship

e-Enterprise

Environment

Learning Center

Purdue University Libraries

2004 initiative for Libraries faculty to collaborate with other faculty across

campus—apply library science knowledge and expertise to research

problems:

collect, organize, describe, curate, archive, disseminate

data/information

Dean

Assoc Deanfor Research

Assoc Deanfor Learning

ResearchSystemsAdmin

DataResearchScientist

DataResearchScientist

LibraryFaculty

Directors (Copyright, University Press)

Assoc Deanfor Collections &

Information Resources

Assoc Deanfor Information

Technology

Assoc Deanfor Planning & Administration

Reorganization

Interdisciplinary research

“Libraries as partners in e-science initiatives on campus…”

Researchers with data

management needs

Librarians with library science

knowledge/expertise

Problem solvingand solutions

Determine need for collaboration

Hypothesized that researchers have data management needs and that librarians can help meet them

Employed top-down and bottom-up investigation for data collection

Verified: PU researchers said they need help in collecting, organizing and providing access to their data

Outside of the library

Attended research seminars, callouts, and discussions to identify collaboration and funding opportunities. Also created or hosted them.

Built relationships. Found researchers who understood that collecting, organizing and providing access to data and information are not only important, but critical, and thus, librarians need to be involved.

Found problems to solve, then collaborated on solutions. Talked about what we know—organizing data and

information (different meanings to different groups). Brought something to the table. Had to be prepared to

demonstrate something tangible (initially a proof-of-concept or a prototype).

Current areas of collaboration

Discovery Learning Center

Earth & Atmospheric Science

English IT at Purdue Mechanical Engineering

Technology Regenstrief Center

Agronomy Biology Cancer Center Center for the

Environment Chemical

Engineering Chemistry Cyber Center

Example: Building relationships

“[M]any model developers and users from research institutions and federal research agencies would benefit from ability to search for and retrieve WQFS data. Coupling in-house experimenter knowledge with rectified datasets represents a major barrier to making intensive datasets available beyond the research program of the initial investigator. …To date, there is no common protocol for converting a locally-housed, single-experimenter water quality dataset to a multi-user, remotely searchable and retrievable database.”

S. Brouder. “Rationale for adding WQFS to the DIR.”

Example: Water Quality Data

Agronomy and Libraries Collaboration Data format Dublin Core

Metadata DSpace

repository OAI-PMH

interoperability

First attempts

Identifying and Harvesting Knowledge Resources in Support of Food Safety, Protection and Security Curricula for U.S. Universities, NSDL proposal (Kansas Sate University Libraries as principal investigator, D. Scott Brandt, Priscilla Geahigan, Sarah Kelly Co-PIs): identify and select FS&S resources for repository, enrich with metadata, and build thesaurus to increase search ability

Cyber Infrastructure for Discovery Chemistry Research NSF proposal (James Caruthers, Chemical Engineering PI, Bartow Culp Co-PI): identify sources for test bed, help test algorithms for extracting information, assist with improving searching capabilities

Collaborative Research: Multidimensional Grammar and Distance Metrics for Analyzing, Accessing, and Synthesizing Complex Multimodal Information in a Secure Digital Library NSF proposal (Jan Allebach Electrical & Computer Engineering PI, Michael Fosmire Co-PI): identify sources for test bed, mark up documents, assist with improving searching capabilities

Current successes

E. Coli K-12 Model Organism Resource NIH proposal (Barry Wanner, Biology, PI, D. Scott Brandt, Libraries, Co-PI) : create archival process for curated database, assist in applying ontologies for data representation and annotation

An Expert System Multimedia Tutorial for Locating Technical Information, Purdue University TLT Digital Content grant (Megan Sapp, PI, Amy Van Epps and Michael Fosmire, co-PIs, with Bruce Harding, Mechanical Engineering Technology): develop tutorial for MET102 course in using and applying standards

URL-based Search Interface to the Distributed Institutional Repository Purdue University Graduate School (Michael Witt, Libraries, PI, Darcy Bullock, Civil Engineering, Co-PI): develop toolkit to deploy customized searching of dissertations by school, advisor, etc.

In the works…

AquaEcon Web Library: An Electronic Resource on Economics-Related Literature on Aquaculture, NOAA (K. Quagrainie, Agricultural Economics PI, Hal Kirkwood, Libraries, as co-PI): build and populate database )

Oncology Resource, NIH, (Marietta Harrison, Cancer Center PI, Diane Rein and Vicki Killion, Libraries, co-PIs): data mine literature and build a database of biomarkers for cancer

BBSI: Purdue University Bioinformatics Summer Internship Program NSF (Michael Kane, Technology PI, D. Scott Brandt, Libraries, Co-PI): contribute to development of curriculum of bioinformatics

Archiving Research Datasets in a Distributed Institutional Repository, Michael Witt, Libraries, various ITaP personnel: populate distributed repository with and link to datasets, enhance and expose metadata for discovery and access

Distributed Institutional Repository

Por

tal

Met

adat

aR

epos

itory

e-prints

archival collections

grid resources

native databases

DSpace

Service Provider

Data Providers

DIR opportunities

serves as a platform for research in: Systems model and architecture Metadata workflow and processes Taxonomies and ontologies Data management and preservation Sustainability/business model

Motivation (participants)

Directly related to work, and makes something difficult easier

It’s an extension of “our everyday job” Something new and exciting to do Breaking new ground, want to

contribute to interdisciplinary initiative Force the issue of how it gets done

(i.e., more people added to help out)

Motivation (non-participants)

Articulation of what is expected by the Dean Partly determined on a case-by-case basis Has to be “interesting to me” Something that uses “the skills I can bring to it” Need to get credit for it (recognition, reward) Important to allow individual to define what

interdisciplinary research is Should be opportunities to "stick your toe in the

water" before making big commitment Need time to do it, & to do “things I want to do”

Within the library

Identify research agendas (“hot spots”) and prioritize. Apply library science to interdisciplinary problems. Recognize a percentage of time that is dedicated to

research. Carry out research interest discussions, talking to

individuals about their research. Discuss published research (brown bag sessions)—

identify journal articles which fit with current or future research endeavors.

Consult on research grant applications, both brainstorming and draft proposals.

Send out research updates of progress and successes.

Recap…

12 faculty involved in 9 grants since April of last year

New positions: data research scientists to support research

Researchers are starting to come to Libraries for collaborations

“100 conversations, lead to 20 discussions, lead to 5 grants, lead to 1 award…”

Questions?

James L. Mullins

jmullins@purdue.edu

D. Scott Brandt

techman@purdue.edu

What if too successful?

1. We may need to prioritize, or focus on certain areas

2. We could “grow” capability through “soft money” appointments and collaborations with other groups

3. Goal is to build tools which scale and help people over various disciplines