Eduardo Pena

Computer Science

Eduardo Pena is a data scientist who plans to automate the search for relevant metadata. Considering that much of information science still depends on manual data classification, Penas’s project has enormous potential to deal with the growing complexity and demand of information management. With a degree and master’s degree in computer science from the State University of Londrina, the scientist also achieved a doctorate at the Federal University of Paraná. During this period, he had the opportunity to collaborate at the prestigious Hasso Plattner Institute in Germany.

The professor at the Federal Technological University of Paraná pursues a second passion on the weekends, also with arduous investigative rigour: scouring the internet for the best chefs and their recipes to surprise his wife and friends in the kitchen. His virtues go beyond cooking, as he guarantees he also takes care of the dishes after dinner. According to the scientist, washing dishes is the ideal time to gain insights into his scientific projects. In addition to his passion for good food and data science, Pena is passionate about music and plays several chords on his Fender Telecaster.

Open Calls

Science Call 6

Projects

How to discover relevant metadata for data management?
Science / Computer Science

Metadata is descriptive data about datasets. They can be simple, such as attribute names and statistics, or complex, such as semantic restrictions between different records. Data management and science provide compelling applications to users, but these applications depend on complex metadata. Most datasets manipulated by scientists include, at most, simple metadata, which limits the potential delivered by applications. Manually identifying this descriptive data is an error-prone task, made difficult by the complexity of modern data and applications. The objective of this project is to develop automated solutions for metadata discovery. To deal with the gigantic space of possible results, we propose to characterize and explore the synergy between data and applications to converge on the space that best assists users in applications of interest.

Amount invested

Grant Serrapilheira: R$ 200.000,00
Grant Fundação Araucária: R$ 300.000,00