After a dataset is identified, it will go through an evaluation for prioritization across the five categories. A 0-2 ranking (0 = None/Poor, 1 = Some/Acceptable and 2 = All/Good) will be assigned to each dataset for each category and then a composite score will be calculated.
Recognizing that data quality impacts the usefulness of a released dataset, each dataset will also be evaluated for quality. The inventory of datasets will be ranked and then scheduled for release according to priority, quality and resources available.
I. Data commonly asked for in Open Record Requests
- Have requests for the data been made under Wisconsin Open Records laws?
II. Data of public interest
- During external events (e.g. hackathons, community engagement events) have residents requested the dataset?
- Does the dataset deal with a topic that is commonly valuable to external users?
III. Data which has documentation (metadata)
- Is the data easily understood? If not, does data documentation exist?
IV. Data which does not have sensitive or confidential information
- What is the level of effort to thoughtfully publish data to protect private and sensitive information?
V. Data which can be easily produce and distributed
- Does producing this data in an open way require intensive resources?
- Does future system changes create additional works or rework to produce the data?