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Conferencia Semantic Workflows for Large-Scale Scientific Data Analysis

Día: 10 de octubre de 2011
Sala: H1002
Hora: 12:00
Lugar  Facultad de Informática, UPM

Título: "Semantic Workflows for Large-Scale Scientific Data Analysis"
Ponente: Yolanda Gil ( Information Sciences Institute and Department of Computer Science University of Southern California


In the coming decades, computational experimentation will push the boundaries of current science infrastructure in terms of inter-disciplinary scope and integrative models of the phenomena under study.  A key emerging concept is computational workflows, which provide a declarative representation of complex scientific applications in terms of the interrelated data retrieval and processing tasks and their mapping to the underlying computational environment.  In this talk, I will give an overview of the benefits of using workflows for scientific data analysis, including the management of distributed computations, provenance recording, and reproducibility.  I will introduce semantic workflows, which exploit a variety of metadata about data characteristics and data processing algorithms to assist users with significantly more complex analytical tasks.  Semantic workflows enable new capabilities for automated workflow generation, reuse, validation, and experiment design that have the potential to increase scientific productivity by orders of magnitude.  I will describe major benefits that semantic workflows can provide to scientists, illustrated with examples from prior and ongoing work in genomics, biomedical image processing, aquatic ecology, and earthquake simulation.

Short Bio:
Dr. Yolanda Gil is Director of Knowledge Technologies and Associate Division Director at the Information Sciences Institute of the University of Southern California, and Research Professor in the Computer Science Department. She received her M.S. and Ph. D. degrees in Computer Science from Carnegie Mellon University. Dr. Gil leads a group that conducts research on various aspects of Interactive Knowledge Capture. Her research interests include intelligent user interfaces, knowledge-rich problem solving, scientific and grid computing, and the semantic web. An area of recent interest is large-scale distributed data analysis through semantic workflows. Dr. Gil was elected to the Council of the American Association of Artificial Intelligence (AAAI), and served in the Advisory Committee of the Computer Science and Engineering Directorate of the National Science Foundation. She recently led the W3C Provenance Group, an effort to chart the state-of-the-art and posit standardization efforts in this area. In 2010 she was elected Chair of ACM SIGART, the Association for Computing Machinery's Special Interest Group on Artificial Intelligence.



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