Crowdsourced Data
This is placeholder text for 2-3 paragraphs about crowdsourced data to describe what it is.
Crowdsourcing can refer to a wide range of activities, typically including technology-centric means such as mobile apps, social media platforms, or location-based services. In some cases, crowdsourced data can also refer any data source generated by the public, including surveys or intersection walk-buttons. For the purposes of this guidebook, crowdsourced data will focus on actively generated data from users using either a mobile app or social media platfrom.
Mobile apps or websites provide users the opportunity to identify, review, or geo-tag certain aspects of the park while visiting. Each source has specifically tailored information from users and different methods to extract or use the data.
Resource Considerations
| Cost | Time |
|---|---|
 |  |
Factors that Could Increase Cost and Time
- data sharing agreements
- building technical capacity
- verifying data, understanding any systemic biases in data users
Problem Areas Addressed
| Visitor Data Area | Addressed? (Y/N) |
|---|---|
| High-Visitation Hot Spots | Y |
| Counts | N |
| Demographics | N |
| Visitor trip route | N |
| Visitor time spent | N |
| Yearly trends | Not Really |
| Trends across hours, days, months | Y |
| Within-Park Travel Patterns | N |
| Trip Purpose | N |
| Visitor Feedback | Y |
| Modal Preferences | N |
| Route or Corridor Preferences | Y |
| Type of Visitor | Y |
Pros/Cons
| Pros | Cons |
|---|---|
| new types of data available | data biases |
| can be free or cheap to produce | entries are generally not verified |
| generally real-time |