The labeling challenge is trickier with mobile sensor data. For example, a person contributing data has to log in when walking, running or biking. If a researcher wants to correlate mood with activity, the contributor might have to answer a question or two on a touch screen.

Data from a personal device — a smartphone or smartwatch — is also sensitive, raising issues of data use and privacy, which complicates the collection of sensor data.

The development of software models using mobile sensor data has been hindered, said Deborah Estrin, a professor of computer science at Cornell Tech, because of “the absence of labeled data sets. And the reason for that is the lack of a community effort to do that in an ethical, efficient way.”

Ms. Estrin is one of several computer scientists from universities around the world who are advisers to CrowdSignals, as are researchers at companies like Microsoft and Intel.

Most research using mobile data has tracked relatively small numbers of people in a single city or region, often using proprietary data from mobile carriers or device makers. CrowdSignals is intended to overcome those limitations, said Daniel Gatica-Perez, a researcher at Idiap Research Institute in Switzerland, who is an adviser on the project.

Both Apple and Samsung have introduced software tools for collecting and sharing mobile data. Samsung’s SAMI is a data exchange platform where developers can place their data and work with others. Apple’s Research Kit allows iPhone users to share their data for use in research projects, often health-related studies.

CrowdSignals is trying to build a marketplace for data with financial incentives for people to participate and label their data. All the data will be anonymized, the organization says.