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Evento: 'Palestra Juliana Freire: Using Provenance to enable Reproducible Science'

Eventos PESC (Palestras, Seminários, etc.)
Palestras, Seminários, etc. do PESC/COPPE/UFRJ.
Data: Monday, August 01, 2011 At 14:00
Duração: 2 Horas

Palestra: Using Provenance to enable Reproducible Science

Prof. Juliana Freire (Polytechnic Institute of New York University)Data: 01 de agosto de 2011
Horário: 14h
Local: CT, Bloco H, Sala H-324-A


While computational experiments have become an integral part of the scientific method, it is still a challenge to repeat such experiments, because often, computational experiments require specific hardware, non-trivial software installation, and complex manipulations to obtain results. Generating and sharing repeatable results takes a lot of work with current tools. Thus, a crucial technical challenge is to make this easier for (i) the author of the paper, (ii) the reviewer of the paper, and, if the author is willing to disseminate code to the community, (iii) the eventual readers of the paper. While a number of tools have been developed that attack sub-problems related to the creation of reproducible papers, no end-to-end solution is available. Besides giVing authors the ability to link results to their provenance, such a solution should enable reviewers to assess the correctness and the relevance of the experimental results described in a submitted paper. Furthermore, upon publication, readers should be able to repeat and utilize the computations embedded in the papers. But even when the provenance associated with a result is available and contains a precise and executable specification of the computational process (i.e., a workflow), shipping the specification to be run in an environment different from the one it has been designed at raises many challenges. From hard-coded locations for input data, to dependencies on specific version of software libraries and hardware, adapting a workflow to run on a new environment can be challenging and sometimes impossible.

We posit that integrating data acquisition, derivation, analysis, and visualization as executable components throughout the publication process will make it easier to generate and share repeatable results. To this end, we have built a provenance-rich infrastructure to support the life-cycle of 'reproducible publications'---their creation, review and re-use. In this talk, I will give an overview of this infrastructure and describe in detail two of its components: a mechanism that supports reliable links between derived data and their provenance and a method for adapting workflows to run in different environments.

This is joint work with Claudio Silva, David Koop, Emanuele Santos, Matthias Troyer, Bela Bauer, Carlos E. Scheidegger

Juliana Freire is a Professor at the Department of Computer Science and Engineering at the Polytechnic Institute of New York University. Before, she was an Associate Professor at the School of Computing, University of Utah; an Assistant Professor at OGI/OHSU; and a member of technical staff at the Database Systems Research Department at Bell Laboratories (Lucent Technologies). An important theme is Professor Freire's work is the development of data management technology to address new problems introduced by emerging applications. Her recent research has focused on two main topics: scientific data management and Web mining. Within scientific data management, she is best known for her work in provenance and scientific workflows, and for being a co-creator of the open-source VisTrails system. Professor Freire is an active member of the database and Web research communities, having co-authored over 100 technical papers and holding 4 U.S. patents. She is a recipient of an NSF CAREER and an IBM Faculty award. She has chaired or co-chaired several workshops and conferences, and she has participated as a program committee member in over 60 events. Her research has been funded by grants from the National Science Foundation, Department of Energy, National Institutes of Health, the University of Utah, Microsoft Research, Yahoo! and IBM.


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