Logistics for Webinar You must call in for audio: 866-740-1260 access code 9870179# Participants muted Ask questions in chat any time 20 minutes for Q&A Recording & slides, schedule of webinars: blog.dmptool.org/webinar-series DMPTool Webinar Series 8: Data Curation Profiles & the DMPTool Sponsored by IMLS 13 August 2013
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DMPTool Webinar 8: Data Curation Profiles and the DMPTool (presented by Jake Carlson)
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Logistics for Webinar
You must call in for audio: 866-740-1260 access code 9870179#
Participants mutedAsk questions in chat any time
20 minutes for Q&A
Recording & slides, schedule of webinars: blog.dmptool.org/webinar-series
DMPTool Webinar Series 8: Data Curation Profiles & the DMPTool Sponsored by IMLS13 August 2013
28 May Introduction to the DMPTool
4 June Learning about data management: Resources, tools, materials
18 June Customizing the DMPTool for your institution
25 June Environmental Scan: Who's important at your campus
9 July Promoting institutional services; EZID Outreach Made Simple!
16 July Health Sciences & DMPTool - Lisa Federer, UCLA
30 July Digital humanities and the DMPTool - Miriam Posner, UCLA
13 Aug Data curation profiles and the DMPTool – Jake Carlson, Purdue
27 Aug Talking points for meeting with institutional stakeholders
10 Sep Tools and resources that work with/complement the DMPTool
Beyond funder requirements: more extensive DMPs
Case studies 1 – How librarians have successfully used the tool
Case studies 2 – How librarians have successfully used the tool
Outreach Kit Introduction
Certification program introduction
blog.dmptool.org/webinar-series
Data Curation Profiles & the DMPTool
Jake Carlson Associate Professor of Library Science / Data
Services Specialist
Purdue University Libraries
DMPTool Webinar Series 8: Data Curation Profiles & the DMPTool Sponsored by IMLS13 August 2013
Road Map
• History / Background of the DCP Toolkit
• Comparing the DMP and the DCP
• Case Study in using the DCP
“Investigating Data Curation Profiles across Research Domains”
• Awarded in 2007 to Purdue Libraries and Graduate School of Library and Information Science at UIUC
• Goals of the project: – To understand the practices, attitudes and needs of
researchers in managing and sharing their data. – To Identify possible roles for librarians to facilitate data
sharing and curation.– To develop a tool for librarians to gather information on
researcher needs for their data.
Interview areas: 20 faculty, 12 disciplines
Agronomy & Soil Science (Purdue & UIUC),
Anthropology (UIUC), Biochemistry (Purdue),
Biology (Purdue), Civil Engineering (Purdue),
Earth & Atmospheric Sciences (Purdue & UIUC),
Electrical & Computer Engineering (Purdue),
Food Science (Purdue), Geology (UIUC),
Horticulture & Plant Science (Purdue & UIUC),
Kinesiology (UIUC), Speech and Hearing (UIUC)
What we asked …
• Research Data Lifecycle (story of the data)
• Characteristics of the Data• Data Management / Storage• Data Dissemination and Sharing• Data Preservation and
The ability to cite this dataset in my publications
The ability for researchers within my discipline to easily find this dataset
The ability for researchers outside of my discipline to easily find this dataset
The ability for people to easily discover this dataset using Google
Prioritize your needs for the following types of services
Witt, M. (2009, May 18). Eliciting Faculty Requirements for Research Data Repositories 4th Int’l Conference on Open Repositories. Georgia Tech, Atlanta, GA.
n=19
Prioritize your needs for the following types of services
The ability for me to submit this dataset to a repository myself
The process of submitting this dataset to a repository is automated
The ability to make these data accessible in multiple formats
The ability of the repository to provide version control for the data
Witt, M. (2009, May 18). Eliciting Faculty Requirements for Research Data Repositories 4th Int’l Conference on Open Repositories. Georgia Tech, Atlanta, GA.
n=19
An interview based tool for gathering:
• Information about a particular data set.
• What a researcher is doing to manage / curate the data set.
• What a researcher would like to do with the data.