Data collection, analysis, and management
Key Concepts:
- What is data? What forms does it take, and how is it recorded?
- Have students draw on the white-board an example "figure"
of their own data (e.g., typical data from their own
experiments, or what they expect to collect during their
first-year research rotations). How are these data similar?
How are they different?
Discuss the following questions:
Is there a universal standard for data collection? (students
should appreciate that various forms of data require
different types of collection and storage, but that a key
universal concept is in careful documentation and accurate
recording of data, in whatever form it exists, in the most
permanent way possible).
Ask students how they handle data management. What should be
in a data book? How much record keeping is electronic vs
ink-on-page?
What key information do you need to record regarding data?
How has data recording changed over time?
How can bias influence data collection? (e.g., Golgi vs
Ramon y Cajal).
- Who owns the data?
- Discuss ownership of data. Ask whether the source of
funding should matter?
For how long should you keep data? Show
students Dartmouth's
data retention policy.
Key points to convey: Sponsoring entities (e.g., NIH, NSF,
Dartmouth, etc.) have specific rules regarding data
retention. Dartmouth's policy follows NIH policy in stating
that data should be retained for 3 years following the final
research reporting event. But emphasize that typically
researchers keep data for much longer times (e.g.,
indefinitely), and that federal agencies can audit data for
as long as it is in the possession of the institution.
- When and how should data be shared?
- Ask students, "when is it appropriate to share
experimental results?" Discuss the various points of view on
this. What considerations go into such a decision?
- What types of data manipulations are appropriate?
- How is data handled? Ask the students how they personally
utilize data from acquisition to figure making. Make them aware
that in many cases the "final product" is different than the
"raw data" originally acquired. Which transformations of data
are ethically sound?
Show students the data manipulation slide show.
Is it ever appropriate to "toss out" observations (data)?
- When and how should data be shared?
- Ask students, "when is it appropriate to share experimental
results?" Discuss the various points of view on this. What
considerations go into such a decision?
Delivery:
- Emphasize that the course is about, and for, them.
They are embarking on a dynamic research career, and many of them
are intrinsically interested in learning about the course topics
(professionalism, mentoring, authorship/peer-review, and data
management).
- Tailor the course for your students. Professional expectations
regarding data collection, authorship, and collaborations differ
from field to field. Your students will be most interested in
their own research discipline. For instance, when discussing
standards of conduct, share with students guidelines published by
professional societies that they are members of, or from journals
that they are likely to publish in.
- Let your students take over. As facilitators, we want
to accomplish two things: we want to start an appropriate
conversation of the relevant material. Second, we want to guide
the discussion so that it touches on all of the relevant concepts
and points of view. These goals can be accomplished by emphasizing
to students that the course is not about "right" vs "wrong", and
that all points of view will be respectfully discussed. As
facilitator, a key resource you have is silence... your students
will carry on the conversation. Your role is to keep that
conversation on track and on time (i.e., covering the relevant
topics in the allotted amount of time).
- Be creative with discussion points and case studies.
While you are free to use any of the prepared cases from the text
books, or from Ethics
CORE, you can also develop your own discussions around
relevant current events applicable to the course content. For
example, Science magazine had
an article
in March about the NIH’s new focus on unprofessional conduct
during peer review of grants. These types of topical articles can
be effective launching points for relevant discussions of the
course material.
Case studies useful for this topic: