I know this probably won’t fascinate anyone except me, but I spent most of week 2 developing a classification schema for understanding citizen science data policy. Developing a classification scheme was necessary because it’s important to have a *real* metric to use when evaluating different policies, instead of comparing one policy to another in an ad hoc manor. This turned out to be much more of an undertaking than I initially thought (I defend qualitative research as “rigorous” all the time, but forget exactly how rigorous it really is until it’s time for me to engage with some data). The resulting schema is essential a 12-page list.
With apologies for WordPress formatting, here are the top level categories, which should give you a good idea about how citizen science/ PPSR data policy is generally structured:
- Vocabulary used in this classification scheme
- Terms designating permission
- Data policy– structure and location
- Data policy of a project
- Structure of data policy
- Location of data policy
- Additional Information
- Related policy
- Legal policy
- Other related policy
- Data policy– privacy and security
- Types of information collected
- Use of information collected
- Measures to maintain security
- Consequences of a security breach
- Terms of participation
- Conditions for participation
- Limitations to participation
- Data ownership and copyright
- Observations/ other raw data
- Aggregate data set
- Data use
- General conditions for use
Next week I get to validate! I’ll be testing my schema with projects not used in the initial construction, making my wonderful mentor code some projects with me to generate inter-rater reliability, and testing out with data policies outside of the PPSR realm– namely, that of Wikipedia, Facebook, and Data.gov (for a start).
Non-project highlights include eating at Moosewood, the premier vegetarian restaurant in the world.
Next week I promise you a list of the best data policies in PPSR.