Data management should happen throughout the data lifecycle, from the moment you conceive of a research project until the data are archived and preserved for future access and reuse. (Lifecycle from UK Data Archive)
Creating data design research plan data management (formats, storage etc) plan consent for sharing locate existing data collect data (experiment, observe, measure, simulate) capture and create metadata
Processing data enter data, digitise, transcribe, translate check, validate, clean data anonymise data where necessary describe data manage and store data
Analyzing data interpret data derive data produce research outputs author publications prepare data for preservation
Preserving data migrate data to best format migrate data to suitable medium back-up and store data create metadata and documentation archive data
Giving access to data distribute data share data control access establish copyright promote data
Re-using data follow-up research new research undertake research reviews scrutinise findings teach and learn
Funding agency requirements NSF, NIH Whitehouse memo that says “unclassified research funded by the Federal Govt must be stored for long-term preservation and publicly available in order to maximize the impact of the Federal research investment” A recent article in “Nature” mentioned that NIH and Wellcome Trust are withholding grant money from researchers who do not make publications openly available – this trend could someday apply to data. Funding agencies are taking open access seriously
Advance science Facilitate data reuse and repurposing Expedite the scientific process, saving time and resources in the long run Ensure research integrity – data can be used to replicate results and verify research
Support open access – MSU’s institutional repository is optimized for search engines, so your data will rise to the top of a Google search. This leads to Increased research impact Increased citations Share data and knowledge Public: scientific community Increases research efficiency – and prevents duplication of effort by enabling others to use your data Private: data management tools allow sharing within a research team Preserve your data Protect your data for future research For example, Climate researchers use data from the past hundred years to analyze climate trends. You want your data to be available to support agriculture development on Mars in the 22nd Century!
You (the researcher): Create Informative file names Logical directory and folder structures Preservation-friendly formats Document Versions Metadata ReadMes Protect Sensitive data Backup: master, local, external
Bulk data storage Data analysis and visualization Software development
Data Management Librarian: Data management consulting DMPTool Help write and revise data management plans Metadata consulting Scholarly communication Encourage data sharing and reuse Advise on copyright and sensitive data Data repository guidance Including data publishing in ScholarWorks, our institutional repository
And of course facilitates the long-term preservation and accessibility of your work.
ScholarWorks: Your scholarly output, all freely available in one place Open access to your scholarly output (articles, book chapters, presentations, blogs, data, etc.) Link to your data, even if it’s archived elsewhere (e.g. in a discipline-specific repository) Link your data to the associated articles Receive a permanent identifier for clear citations Store embargoed data for future publication Preserve your scholarly output for the long term
DATA MANAGEMENT AT
What is data management?
Why data management?
Data management roles at MSU
What does the library offer?
WHAT IS DATA MANAGEMENT?
from UK Data Archive: http://www.data-archive.ac.uk/create-
WHY DATA MANAGEMENT?
Verification of published
Preservation of access to data
Allows reuse/repurposing of
Indirect (costs avoided)
Redundant data collection
Inefficient legacy data curation
Burden of sharing-upon-request
Protects against personnel
Facilitates review and
Secure long-term stewardship
Increased impact per publication
More efficient use of research
dollarsAdapted from Dryad 101 http://wiki.datadryad.org/Publicity_Material, and
Beagrie N, Lavoie BF, Woollard M (2010) Keeping Research Data Safe 2. Bristol:
DATA MANAGEMENT ROLES
You (the researcher)
•Informative file names
•Logical directory and folder structures
•Backup: master, local, externalProtect
DATA MANAGEMENT ROLES
Research Computing Group
Bulk data storage
Data analysis consulting
DATA MANAGEMENT ROLES
Data Management Librarian