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Minisymposium Presentation
Advancing Research through Integrated Scientific and Operational Data Management and Governance
Presenter
Rodrigo is the Data Science Initiative Director and an Associate Professor at the Institute of Mathematical and Computational Engineering and the Industrial and Systems Engineering Department in the School of Engineering at Pontificia Universidad Católica de Chile. He is also a member of the Advisory Board of the Columbia Global Center | Santiago and a Board Member of the Chilean Institute of Operational Research.Rodrigo's research focuses on combinatorial problems and managing uncertainty in these contexts. His work combines predictive and prescriptive analytics with combinatorial and stochastic optimization techniques to develop robust decision support tools for applied problems. His interests include scheduling problems and designing approximation algorithms to compute high-quality solutions efficiently.Rodrigo holds a B.S. in Electrical and Industrial Engineering and an M.S. in Electrical Engineering from Pontificia Universidad Católica de Chile, as well as a Ph.D. in Industrial Engineering and Operations Research from Columbia University.
Description
Scientific field stations generate vast amounts of data, ranging from environmental measurements to operational logistics. However, the lack of structured data governance and integration strategies often hinders the full potential of these datasets, limiting their impact on research and decision-making. At Universidad Católica, we are developing a data platform designed to streamline the management, sharing, and utilization of scientific and operational data across the Regional Field Stations Network (RCER). This platform aims to provide researchers with reliable, well-organized, and accessible data by implementing robust governance models, standardized storage structures, and seamless cloud integration. By bridging scientific and operational data streams, we enhance reproducibility, data-driven decision-making, and interdisciplinary collaboration. A key component of this effort involves the development of local data management strategies that ensure field stations can efficiently capture and process their data before integrating with the broader system. In this presentation, we will discuss the challenges of scientific data governance in distributed field environments, the methodologies we are employing to create a scalable and sustainable data infrastructure, and the expected impact on research output. Through this initiative, we aim to empower scientists by unlocking the full potential of the data they generate, ultimately advancing research across multiple disciplines.