DataONE Data Management Workshop
May 23-24, 2012
Santa Barbara, CA
AGENDA (v4)
DataONE Data Management Workshop
May 23-24, 2012
Santa Barbara, CA
Workshop Goals:
1) Provide an introduction to data management concepts and best practices
2) Gather feedback from each lesson from students in order to assess effectiveness
Presenters:
Viv Hutchison (USGS), Carly Strasser (UCOP), Heather Henkel (USGS), Nancy Hoebelheinrich (NSIDC), Mark Schildhauer (NCEAS)
AGENDA
Day 1
9:00 – 9:45 Welcome and Introductions (Viv)
9:45 – 10:45 Introduction to Data Management (Viv)
10:45 – 11:00 BREAK
11:00 – 11:30 Data Sharing (Carly) and Advertising your Data (Nancy)
11:00 – 12:30 Data Management Plans and Tools (Carly)
- HANDS-ON: Write a Data Management Plan
12:30 – 1:30 LUNCH
1:30 – 2:00 Data Entry Manipulation (Carly)
2:00 - 2:30 Quality Assurance/Quality Control (Carly)
2:30 – 3:30 - HANDS-ON: Data Organization Tips for Your Dataset
3:30 – 3:45 BREAK
3:45 – 4:45 Analysis and Workflows (Mark)
4:45 – 5:30 - HANDS ON: Demo of Sample Data to Analysis Environment (Additionally, participants with their dataset in CSV format can
use their dataset)
6:00 Group Dinner (optional)
Day 2
9:00 – 10:00 What is Metadata? (Viv)
The Value of Metadata (Viv)
Writing Quality Metadata (Viv)
10:00 – 10:30 - HANDS-ON: Writing a Metadata Record for Your Dataset
10:30 – 10:45 BREAK
10:45 – 12:00 - HANDS-ON: Writing a Metadata Record for Your Dataset
12:00 - 1:30 LUNCH
1:30 – 3:00 Data Citation (Nancy)
- HANDS-ON: Create a Dataset Citation for Your Data
- HANDS-ON: Create a Citation for Data From Other Researchers
3:00 – 3:15 BREAK
3:15 – 4:00 Protected Backup and Data Preservation (Heather)
4:00 – 5:00 Review of course material; Survey; Comments
5:00 Adjourn
WIll try to paste the applicant information here:
Stage Subject Institution
PhD Candidate Geography UC Santa Barbara
PhD Candidate Environmental Systems UC Merced
PhD Candidate Ecology / Evolutionary Biology UC Irvine
PhD Candidate Environmental Systems UC Merced
Assistant Prof Ecology, Evolutionary Biology & Behaviour Michigan State
Researcher (Masters level) Aquatic Ecology BLM/USU National Aquatic Monitoring Center
PhD Candidate Forestry Northern Arizona State
PhD Candidate Ecology UC Davis
Masters GIS Maryland / Smithsonian
PhD Candidate Geography UC Santa Barbara
Early stage (1 yr) Postdoc Civil Environmental Engineering University of Illinois at Urbana-Champaign
PhD Candidate Ecology UC Davis
Masters Candidate LIS University of Tennesse
Late stage (4 yr) Postdoc Hydrology Dept. of Land, Air and Water Resources
PhD Candidate Geography UC Santa Barbara
PhD Candidate Agriculture UC Santa Barbara
(Stacy's comments below for us to review)
Prior to workshop:
- Online survey to evaluate perceived norms and personal practices related to each workshop theme
- Example – QA/QC:
- Based on your experience, how much effort do researchers in your field typically invest into ensuring or data quality (e.g. checking for errors during data entry, using statistical and/or graphical approaches to identifying outliers or erroneous values)
- Researchers in my field don’t do anything to ensure data quality --> researchers in my field have adopted cutting-edge practices and technologies to help ensure data quality
- How much effort do you personally invest into ensuring the quality of data you collect or checking the quality of other data you work with?
- I don’t do anything to ensure or check data quality à I have adopted cutting-edge practices and technologies to help ensure data quality
- Please describe procedures you implement and/or technologies you use to ensure or check data quality.
During workshop (after each segment):
- Online or paper survey with a segment focused on the most recently presented workshop theme
- During this session, we presented the following as best practices:
- Do you foresee obstacles to implementing these best practices in your work? How difficult do you think it will be to overcome these obstacles?
- I am already doing this + Likert scale ranging from ‘may require some work to implement, but no serious obstacles’ to ‘insurmountable obstacles’ + not applicable to my work
- Please provide more information about the serious obstacles that you see to implementing these best practices in your work.
At end of workshop:
- Online survey with a segment focused on each workshop theme
- Based on your experience, how much effort do researchers in your field typically invest into ensuring or data quality (e.g. checking for errors during data entry, using statistical and/or graphical approaches to identifying outliers or erroneous values)
- Researchers in my field don’t do anything to ensure data quality à researchers in my field have adopted cutting-edge practices and technologies to help ensure data quality
- How much effort do you personally invest into ensuring the quality of data you collect or checking the quality of other data you work with?
- I don’t do anything to ensure or check data quality à I have adopted cutting-edge practices and technologies to help ensure data quality
- Please describe any changes you plan to make in your efforts to ensure or check data quality based upon things you’ve learned during this workshop.
Ideas for pre-assessment from UCBoulder survey
• Briefly describe your research.
• How long have you been conducting this type of research?
• Can you tell us a little about what sort of data your research produces?
• How is the data stored and accessed after it is produced?
• Who has access to this data?
• Does your department/lab have procedures in place for the preservation of researchers’ data in the event they leave the university or pass away?
- Expectations?