Barbara Lerner's research focuses on helping scientists understand the provenance of their data. Just as the provenance, or history, of a piece of art work can improve confidence in the authenticity of the art, so too, the history of scientific data can improve one's confidence in the reliability of the data. The provenance of scientific data includes information such as where and when the data was collected, using what instruments, and what scientist or organization was responsible for the collection, but it extends far beyond this. It also includes history about how the data is processed from its point of collection to its point of dissemination. This typically includes information about adjustments to sensor readings to account for sensors slipping out of calibration, discarding of clearly inaccurate data (such as air temperatures far outside of the normal range), and information about the insertion of modeled data to replace missing data (due to power failures, for example).
Scientists can use this provenance to help them better understand their data. Lerner's research focuses on ways to automate the collection of provenance and to make provenance accessible to scientists using visualization and query technology.
In addition, Lerner is interested in technology to assist the blind. In a project motivated by her mother-in-law when she lost her sight, Lerner has developed technology that allows a blind person to play bridge with sighted players, using playing cards, rather than a computer interface to minimize the disruption to the normal social nature of a bridge game. Working with honors student Srishti Palani, she developed a system using Bluetooth sensors to identify people in the vicinity of a blind person and to provide haptic and audible feedback to notify the blind person.
At Ӱ̳, Lerner has introduced courses in software design, programming languages, and a software practicum in which students work in teams to design and develop software solutions for clients. She also teaches courses in object-oriented programming, algorithms and operating systems.
Areas of Expertise
Scientific data provenance, software design, assistive technology
Education
- Ph.D., Carnegie Mellon
- B.S., Moravian College