| Time |
Topic |
Presenter |
| 09:30–10:30 |
- Introduction
- Agenda & Goals
- Overview of social factors that impact scientific collaboration Q&A
- Discussion
|
Diane Sonnenwald |
| 10:30–11:00 |
Understanding interdisciplinary research design Case study: Compliance and Compromise |
Elisabeth Davenport |
| 11:00–11:30 |
Break |
|
| 11:30–12:30 |
Group discussion of case study:
Example of possible discussion questions
- Many funding agencies encourage social scientists to collaborate with natural scientists when conducting studies regarding collaboration, etc. Do we and the funding agencies understand the trade-offs (advantages and disadvantages) in this approach?
- Should project proposals accommodate contests, negotiation, and compromise activity?
- Can project planning templates handle interdisciplinary ´comportment´ issues?
- When collaborating across disciplines natural scientists & engineers typically have equipment, samples, prototypes that are dramatically visible and help explain and justify their research design. What is analogous to these within social science?
|
|
| 12:30–14:00 |
Lunch |
|
| 14:00–15:15 |
Data collection & analysis processes
Case study: Activities & artifacts in e-social science (30 min)
Group discussion:
Example of possible discussion questions:
- Is interpretation less contested in natural sciences where data are jointly read from shared instrumentation?
- Does the role of papers differ in social science, e.g., documentation of research results vs. formulation/creation of research results? Does the length of papers, time to publication imply differences in collaboration for social science?
- How do we protect subjects in, e.g., video data?
|
Mike Fraser |
| 15.15–16:00 |
Promises and challenges in data curation and re-use
Case study: Separation by time and labour (20 min)
Group discussion:
Example of possible discussion questions
- What professional social science organizations are investigating such issues?
- What are motivations to share and/or re-use data? Are these motivations dependent on data type and format (quantitative, qualitative, text, video, audio, etc.)?
- Is social science interpretive in ways that complicate distributed work?
- What are the ethical issues in data re-use?
|
Dawn Nafus |
| 16:00–16:30 |
Break |
|
| 16:30–17:00 |
Wrap-up |
Diane Sonnenwald
Elisabeth Davenport |
