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Dive into the research topics where Michelle Galea is active.

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Featured researches published by Michelle Galea.


Swarm Intelligence in Data Mining | 2006

Simultaneous Ant Colony Optimization Algorithms for Learning Linguistic Fuzzy Rules

Michelle Galea; Qiang Shen

M. Galea and Q. Shen. Simultaneous ant colony optimisation algorithms for learning linguistic fuzzy rules. A. Abraham, C. Grosan and V. Ramos (Eds.), Swarm Intelligence in Data Mining, pages 75-99.


Distributed and Parallel Databases | 2012

Data-intensive architecture for scientific knowledge discovery

Malcolm P. Atkinson; Chee Sun Liew; Michelle Galea; Paul R. Martin; Amrey Krause; Adrian Mouat; Oscar Corcho; David Snelling

This paper presents a data-intensive architecture that demonstrates the ability to support applications from a wide range of application domains, and support the different types of users involved in defining, designing and executing data-intensive processing tasks. The prototype architecture is introduced, and the pivotal role of DISPEL as a canonical language is explained. The architecture promotes the exploration and exploitation of distributed and heterogeneous data and spans the complete knowledge discovery process, from data preparation, to analysis, to evaluation and reiteration. The architecture evaluation included large-scale applications from astronomy, cosmology, hydrology, functional genetics, imaging processing and seismology.


ACM Computing Surveys | 2017

Scientific Workflows: Moving Across Paradigms

Chee Sun Liew; Malcolm P. Atkinson; Michelle Galea; Tan Fong Ang; Paul Martin; Jano van Hemert

Modern scientific collaborations have opened up the opportunity to solve complex problems that require both multidisciplinary expertise and large-scale computational experiments. These experiments typically consist of a sequence of processing steps that need to be executed on selected computing platforms. Execution poses a challenge, however, due to (1) the complexity and diversity of applications, (2) the diversity of analysis goals, (3) the heterogeneity of computing platforms, and (4) the volume and distribution of data. A common strategy to make these in silico experiments more manageable is to model them as workflows and to use a workflow management system to organize their execution. This article looks at the overall challenge posed by a new order of scientific experiments and the systems they need to be run on, and examines how this challenge can be addressed by workflows and workflow management systems. It proposes a taxonomy of workflow management system (WMS) characteristics, including aspects previously overlooked. This frames a review of prevalent WMSs used by the scientific community, elucidates their evolution to handle the challenges arising with the emergence of the “fourth paradigm,” and identifies research needed to maintain progress in this area.


international conference on e-science | 2015

VERCE Delivers a Productive E-science Environment for Seismology Research

Malcolm P. Atkinson; Michele Carpenè; Emanuele Casarotti; Steffen Claus; Rosa Filgueira; Anton Frank; Michelle Galea; Tom Garth; André Gemünd; Heiner Igel; Iraklis Klampanos; Amrey Krause; Lion Krischer; Siew Hoon Leong; Federica Magnoni; Jonas Matser; Alberto Michelini; Andreas Rietbrock; Horst Schwichtenberg; Alessandro Spinuso; Jean-Pierre Vilotte

The VERCE project has pioneered an e-Infrastructure to support researchers using established simulation codes on high-performance computers in conjunction with multiple sources of observational data. This is accessed and organised via the VERCE science gateway that makes it convenient for seismologists to use these resources from any location via the Internet. Their data handling is made flexible and scalable by two Python libraries, ObsPy and dispel4py and by data services delivered by ORFEUS and EUDAT. Provenance driven tools enable rapid exploration of results and of the relationships between data, which accelerates understanding and method improvement. These powerful facilities are integrated and draw on many other e-Infrastructures. This paper presents the motivation for building such systems, it reviews how solid-Earth scientists can make significant research progress using them and explains the architecture and mechanisms that make their construction and operation achievable. We conclude with a summary of the achievements to date and identify the crucial steps needed to extend the capabilities for seismologists, for solid-Earth scientists and for similar disciplines.


workflows in support of large scale science | 2013

The demand for consistent web-based workflow editors

Sandra Gesing; Malcolm P. Atkinson; Iraklis Klampanos; Michelle Galea; Michael R. Berthold; R. Barbera; Diego Scardaci; Gabor Terstyanszky; Tamas Kiss; Péter Kacsuk

This paper identifies the high value to researchers in many disciplines of having web-based graphical editors for scientific workflows and draws attention to two technological transitions: good quality editors can now run in a browser and workflow enactment systems are emerging that manage multiple workflow languages and support multi-lingual workflows. We contend that this provides a unique opportunity to introduce multi-lingual graphical workflow editors which in turn would yield substantial benefits: workflow users would find it easier to share and combine methods encoded in multiple workflow languages, the common framework would stimulate conceptual convergence and increased workflow component sharing, and the many workflow communities could share a substantial part of the effort of delivering good quality graphical workflow editors in browsers. The paper examines whether such a common framework is feasible and presents an initial design for a web-based editor, tested with a preliminary prototype. It is not a fait accompli but rather an urgent rallying cry to explore collaboratively a generic web-based framework before investing in many divergent individual implementations.


ACM | 2013

Proceedings of the 8th Workshop on Workflows in Support of Large-Scale Science

Sandra Gesing; Malcolm P. Atkinson; Iraklis Klampanos; Michelle Galea; Michael R. Berthold; R. Barbera; Diego Scardaci; Gabor Terstyanszky; Tamas Kiss; Péter Kacsuk

This paper identifies the high value to researchers in many disciplines of having web-based graphical editors for scientific workflows and draws attention to two technological transitions: good quality editors can now run in a browser and workflow enactment systems are emerging that manage multiple workflow languages and support multi-lingual workflows. We contend that this provides a unique opportunity to introduce multi-lingual graphical workflow editors which in turn would yield substantial benefits: workflow users would find it easier to share and combine methods encoded in multiple workflow languages, the common framework would stimulate conceptual convergence and increased workflow component sharing, and the many workflow communities could share a substantial part of the effort of delivering good quality graphical workflow editors in browsers. The paper examines whether such a common framework is feasible and presents an initial design for a web-based editor, tested with a preliminary prototype. It is not a fait accompli but rather an urgent rallying cry to explore collaboratively a generic web-based framework before investing in many divergent individual implementations.


discovery science | 2013

The Data Bonanza: Improving Knowledge Discovery in Science, Engineering, and Business

Malcolm P. Atkinson; Robert Baxter; Peter Brezany; Oscar Corcho; Michelle Galea; Mark Parsons; David Snelling; Jano van Hemert


discovery science | 2013

The Digital-Data Challenge

Malcolm P. Atkinson; Robert Baxter; Peter Brezany; Oscar Corcho; Michelle Galea; Mark Parsons; David Snelling; Jano van Hemert


discovery science | 2013

Sharing and Reuse in Knowledge Discovery

Malcolm P. Atkinson; Robert Baxter; Peter Brezany; Oscar Corcho; Michelle Galea; Mark Parsons; David Snelling; Jano van Hemert


discovery science | 2013

Data‐Intensive Seismology : Research Horizons

Michelle Galea; Andreas Rietbrock; Alessandro Spinuso; Luca Trani

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Oscar Corcho

Technical University of Madrid

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Mark Parsons

El Paso Community College

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Rob Baxter

University of Edinburgh

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Mark Parsons

El Paso Community College

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