1. Research Data Management
Kayla Siddell
Data Curation Librarian
Indiana State University

2. Any research project will require some level of data management.
Additionally, funding agencies are increasingly requiring researchers to plan and execute data management practices.
This presentation will highlight some basic data management best practices as well as cover the data life cycle.

3. What is considered data?
Determined by the community of interest
Peer review
numerical data,
publications,
samples,
physical collections,
software and models…

4. Why is data management important?
Funding
Preservation
Access
Scholarship

5. Funding Organizations Requirements

6. Preservation
Some research data are unique and cannot be replaced if destroyed or lost, yet only by referring to verifiable data can your research be judged as sound.
- See more at:

7. Access
Through universal access to data we can enable new science and knowledge creation.
Data have no value or meaning in isolation; they exist within a knowledge infrastructure—an ecology of people, practices, technologies, institutions, material objects, and relationships.
Big Data, Little Data, No Data
Scholarship in the Networked World
By Christine L. Borgman

8. Scholarship
Having the right data is usually better than having more data; little data can be just as valuable as big data.
In many cases, there are no data—because relevant data don’t exist, cannot be found, or are not available.

9. Best Practices

10. DataOne is a foundation comprised of data centers, science networks or organizations who share data and provide data management services to insure open access of earth science research.
For more info:

11. DataONE Best Practices

12. Plan Create and document data back-up policy
Create and document storage system
Define data types and formats
Create a data management plan
Provide budget information

14. Collect KEEP RAW DATA Be consistent Use appropriate field delimiters
Example:
Date, Avg Temperature, Precipitation
01Jan2010, 32.3, 0.0
02Jan2010, 34.1, 0.5
03Jan2010, 31.4, 2.5
04Jan2010, 33.2, 0.0

16. Assure Confirm match between data and descriptors
Provide for versioning
Consider compatibility
Double check data
Identify:
Outliers
Missing values
estimations

18. Describe Assign descriptive file names
Avoid spaces, and special characters
Utilize underscore ( _ ) or dashes ( - )
Use date strings for versioning purposes
An example of a good data file name:
Bat_Mating_IN_2001_LPC.csv
Bat Mating is the project name
IN is the state abbreviation
2001 is the calendar year
LPC represents Local Population count data
csv stands for the file type—ASCII comma separated variable
Instead of "data May2011" use "data_May2011" or "data-May2011"
project acronym,
study title,
location,
investigator, year(s) of study,
data type,
version number,
and file type.

20. Preserve Back-up your data Use standard terminology
Decide what to preserve
Use reliable storage
Identify sensitive data
Keep raw data

22. Discover Use standard terminology Check for web accessibility
Insure reproducible
Document search terms used
Additional parameters
Database, versions

24. Integrate Consider compatibility Consider budget information Document:
Process steps in processing
Data integration from multiple databases
Geospatial parameters

26. Analyze Compatibility Identify outliers Use appropriate software
Document methodology for:
analysis
derived data

27. In-house Options

28. What is Sycamore Scholars?
Digital Archive
For staff, students, and faculty
ETDs
Uniform Resource Identifier (URI)
Indexed and web accessible
What is Sycamore Scholars?
Sycamore Scholars is a digital archive of scholarly works created by students, staff, and faculty at Indiana State University.
Sycamore Scholars began as a means to enable ISU graduate students to submit their theses and dissertations electronically, but the repository can include journal articles, conference papers, technical reports, working papers, data sets, tutorials, music, photographs, and other digital items.
Items in Sycamore Scholars are freely available via the Web and are indexed by and accessible through Web search engines.
Unlike most web sites, files within Sycamore Scholars are maintained for the long term.
Items in Sycamore Scholars are assigned a Uniform Resource Identifier (URI), similar to a URL, but more permanent.
Also, ISU and DSpace are committed to making items accessible far into the future.

29. What kind of content can I add to Sycamore Scholars?
Documents, such as articles, preprints, working papers, technical reports, or conference presentations
Maps
Specimens
Images
Books
Audio files
Theses
Video files
Data sets
Lecture Notes
Artifacts

30. What is the Visions Project?
Digital Memory Project 
Region's history and heritage in print, pictures, and sound
Wabash Valley region in west central Indiana and east central Illinois
Partnerships
Free access
What is the Visions Project?
A Digital Memory Project is dedicated to the documentation and the preservation of the region's history and heritage in print, pictures, and sound.
As a collaborative effort involving the libraries, museums, cultural organizations and community groups, the project provides free access to its digital collection via the internet and promotes remembrance and lifelong learning for all Hoosiers.
Wabash Visions & Voices focuses on the Wabash Valley region in west central Indiana and east central Illinois.
The digital collection contains artifacts, administrative and personal papers, manuscripts, photographs, texts, yearbooks, maps, oral histories, and other audio/video files.

31. The End