The document outlines the development of a research data management service at Carnegie Mellon University amid a decentralized administrative culture. The approach focuses on building support through faculty engagement, pilot projects, and addressing existing needs without waiting for formal policies. Key successes include creating a collaborative environment and securing commitments from university leadership while responding effectively to initial requests for assistance.

1. Anything But A Policy - Building Institutional Support for
Data Services at Carnegie Mellon University
Steven Van Tuyl – Data Services Librarian - Carnegie Mellon University
Contact: svantuyl@andrew.cmu.edu – www.cmu.edu/research/data-management
Abstract
The administrative and research environment at Carnegie Mellon
University is extremely balkanized and hands-off. This environment
tends to result in innovation and productivity at the expense
(sometimes) of strong central administration. Given this
environment, the Data Management Services Group at CMU has
chosen to build a research data management service infrastructure
first and ask for a university policy on data management later. We
have been able to build a broad base of support, starting with
Faculty outreach, engaging with a handful of high profile use cases,
and by taking advantage of widespread administrative uncertainty at
the university.
About Carnegie Mellon University
The “Hunting License”
• CMU Researchers have historically been extreme freedom to do as
they please with their research
• Results in innovation and productivity
• Also – balkanization, animosity towards central authority
• CMU doesn’t like policies* – so we decided to do without
*well, not exactly, but its REALLY hard to create and pass policy at CMU…
Building Support from all Quarters
• Faculty Senate resolution to push for university-level support for
research data management
• High-profile pilot projects create champions across university
• Build support among deans and across university IT infrastructures
• Embedded data management planning into orientations and
responsible conduct of research training
Successes
• Listen and Do
• Secure University commitment (Faculty Senate, President)
• Respond to early requests for help (even without services in
place – Pilot Projects)
• Suggest services around requests for assistance and clear
research data problem areas (web hosting, data storage, backup
charges)
• Ask for Help
• ~ 80% of time initially spent talking and asking questions
• Result is a robust set of collaborators and partners:
• Find Gaps/Fill Gaps
• Push back on “the way things are normally done”
• Identify IT service gaps
• Assert into the Space
• Don’t wait for commitments or positions to be filled (see below)
• Identify existing training programs and jump on-board (e.g. RCR)
• Create a roadmap – then ask for review and assent
$135
$124
$56
$40
$22
$9
$7$3 $2$2 $11
Software Engineering
Computer Science
Engieering
Science
Humanities/Social Science
Public-Private Partnerships
Silicon Valley
Business
Social Science/Management
Fine Arts
Other
• Pittsburgh, PA
• ~12,000 students
• ~1400 faculty
• World leader in
Robotics, Comp.
Sci., Engineering
among others
• > $400 Million in
sponsored funding
in 2013
Dollars in
Millions
About CMU University Libraries
• ~ 25 Librarians & Archivists
• ~ 75 Staff & Administrative
• 3 Libraries plus affiliates
• New Dean starting mid-2013
Information Gathering
• Faculty Survey
• ~10% response rate
• Results as expected…
• Re-launch with Deans
• In-depth Data Interviews
• 10-15 Faculty
• Across data/problem types
These are good…
…But these are even better.
• “I'm fairly fond of my own solutions, especially the flexibility and
access that sorting myself out provides”
• “None of [data management plan] is written down. The PI
decides”
• “This is all advice? Not clear advice will be important to me
unless the result is that your team takes responsibility”
• “I don’t need these services, I need a University commitment to
provide these services”
• “What is a metadata?”
Web Presence – not just a pretty face
• Low cost, potentially high impact
• Provides basic information and tools (e.g. DMPTool) to start…BUT…
• …Intentionally informational – to instigate discussion (and
argument) around Type of Service and Depth of Service
Purely
Informational
Low-Level
Consultation
In-Depth
Consultation
Data Management Services Group
• Responsible for planning and execution of data management
services roadmap
• Composition not fixed initially:
• Revolving cast of characters for over a year
• Occasional experts and interested parties involved in planning
• Settled on a core group
• Final group very different from original expectations
Don’t Forget the Luck
• Keith Webster
• New Dean of Libraries
• Collaborator with ANDS
while dean at Univ.
Queensland
• Subra Suresh
• New President of CMU
• Former head of National
Science Foundation
• Steve Huth
• New Chief Information
Officer
• Interested in new,
centralized IT services
• Massive administrative changes at
CMU ca. 2012-2013
• Three key positions filled with
intensely supportive
administration
• VPR position being filled now
with expectation of support
• Also…
• Timing of OSTP Memo of 2013
• Rejection of high-profile NSF
grant  DMP rewritten, project
funded
Data Services
Librarian
Scholarly Comm.
Librarian
Head – Digital
Library
Initiatives
Head – Office of
Research
Integrity
&Compliance
Director –
Administrative
Computing
Liaison
Librarians
Research
Compliance
Office
Office of
Sponsored
Programs
College-Level
Research
Admins.
DMSG
DMSG Support
This bare-bones
website was
helpful for
defining what
was level of
service was ideal
Building a
roadmap for
services was
initiated out of
these discussions