A Brief Introduction to the Data Curation Profiles

Transcription

1 A Brief Introduction to the Data Curation Profiles Jake Carlson Data Services Specialist

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3 Setting the stage Since 2004: Purdue Interdisciplinary Research Initiative revealed many data needs on campus What faculty said Not sure how or whether to share data Lack of time to organize data sets Need help describing data for discovery Want to find new ways to manage data Need help archiving data sets/collections

4 Investigating Data Curation Profiles across Research Domains Data Curation Profiles This lead to a research award from IMLS Goals of the project: A better understanding of the practices, attitudes and needs of researchers in managing and sharing their data. Identify possible roles for librarians and the skill sets they will need to facilitate data sharing and curation. Develop data curation profiles a tool for librarians and others to gather information on researcher needs for their data and to inform curation services. Purdue: Brandt PI, Carlson Proj Mgr, Witt copi; GSLIS UIUC: Palmer co-pi, Cragin Proj Mgr

5 Data Curation Profiles Methodology Initial interview based on Conducting a Data Interview poster, then pre-profile based on model of data in a few published papers Interviews were transcribed, reviewed Coding, wanted more detail -> 2nd Interview Developed and revised a template for Profile In our experience, one of the most effective tactics for eliciting datasets for the collection is a simple librarianresearcher interview. In this poster, we share a set of ten questions

6 What the interviews asked Research Data Lifecycle (story of the data) Data Management / Storage Disposition of the Data Data Dissemination and Sharing Data Preservation and Repositories Roles for Libraries and Librarians

7 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)

8 Prioritize your needs for the following types of services 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 n=19 The ability to cite this dataset in my publications The ability for people to easily discover this dataset using Google Witt, M. (2009, May 18). Eliciting Faculty Requirements for Research Data Repositories 4th Int l Conference on Open Repositories. Georgia Tech, Atlanta, GA.

9 Prioritize your needs for the following types of services The ability of the repository to provide version control for the data The process of submitting this dataset to a repository is automated n=19 The ability for me to submit this dataset to a repository myself The ability to make these data accessible in multiple formats Witt, M. (2009, May 18). Eliciting Faculty Requirements for Research Data Repositories 4th Int l Conference on Open Repositories. Georgia Tech, Atlanta, GA.

10 Cragin, M.H., Palmer, C.L., Carlson, J.R., & Witt, M. (2010). Data Sharing, Small Science, and Institutional Repositories. Philosophical Transactions of the Royal Society A, 368(1926). If cyberinfrastructure is principally about data: how to get it, how to share it, how to store it, and how to leverage it for scientific discovery and learning (Edwards, Jackson, Bowker and Knobel 2007, p. 31), then advancing cyberinfrastructure is dependent on our understanding of how to support data practices and needs.

11 The Data Curation Profile A means to capture requirements for specific data generated by a single scientist or lab, based on their reported their needs and preferences for these data. Represents the researcher s needs and perspectives. A concise, structured document suitable for sharing and annotation. A resource for Librarians, Archivists, IT Professionals, Data Mangers, and others.

12 Characteristics of the DCP Data Curation Profiles Tells the story of the data Focused on a specific data set provides depth not breadth Interview based Meant to be discipline neutral and widely applicable to different types of data Modular allows for flexibility and tailoring to specific situations and uses

13 DCP Sections Data Curation Profiles Information about the Data and its Context Overview of the Research Focus Intended Audience Funding Data Kinds and Stages Data Narrative (data lifecycle) Target Data for Sharing Use/re-use Value Contextual Narrative

14 Data Stage Output Typical File Size Format Other / Notes Primary Data Sensor 100k in 1 file per proprietary to FTP downloads are Raw data day the sensor mostly automated. Processing Sensor data open/acces Data are formatted into.csv before bring reformatted into a Stage 1 sible format Roughly 6kb.csv /.xls mysql database. Processed Analyzed Published Image Data vectors charts/ Graphs charts/ graphs Stills taken from video 800 records per intersection per day. SQL /.xls.xls /.emf.ppt Ancillary Data.gif /.jpg /.ppt Data are extracted from the mysql database for analysis purposes. charts and graphs used for interpretation. Data are presented via power point. Images generated from video.

15 More DCP Sections Data Curation Profiles Information about Needs Intellectual Property Organization and description of data Ingest Access Discovery Tools Interoperability Measuring Impact Data Management Preservation

16 The DCP Toolkit Data Curation Profiles The Data Curation Profile Toolkit consists of 4 components: User Guide Interviewer s Manual Interview Worksheet DCP Template Photo from:

17 Scenarios for using DCP across campus Data Curation Profiles Research proposal development: data mgmt plans Research data sets: local data management Research data sets: local data assessment Resource data collections: data of use to community Reference data collections: data useful in long term Helping faculty in preparation of sharing data Helping faculty in preparation of archiving data in repository In general liaison role, seeking to understand specific faculty research Used during a collaboration or research project to understand data mgmt needs Participating with VP for Research Office to understand NSF mandate needs

18 How does Purdue use the Profiles? Strategy 1: D2C2 provides expert consultant/collaborator reputation with researchers. Strategy 2: D2C2 creates tools to help liaison librarians engage researchers; Data Curation Profiles help give structure to conversations about data and facilitate information gathering. D2C2 DCP librarians researchers

19 Questions? Jake Carlson Data Services Specialist