James Annis

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dblp:99/2261 · also James Timothy Annis · DBLP profile ↗

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4ranked-venue papers

1as first author

0since 2021 · last 2005

0000-0002-0609-3987ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 3 · 1 first-authorDatabases, data management, data science and information retrieval · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems 3 papers		Distributed systems · 64% High-performance computing · 36%
Interdisciplinary, comprehensive, and emerging computing 2 papers		Computational science and engineering · 100%

Topics — the 7 heaviest of 7, each with the papers that count most for it

Topic	Weight	Papers	Last	Evidence papers
Distributed systems grid computing	0.1	2	2004	The Grid2003 Production Grid: Principles and Practice · HPDC 2004 Grid-Based Galaxy Morphology Analysis for the National Virtual Observatory · SC 2003
High-performance computing › scientific workflow scientific workflow management	0.1	2	2003	Grid-Based Galaxy Morphology Analysis for the National Virtual Observatory · SC 2003 Applying Chimera virtual data concepts to cluster finding in the Sloan Sky Survey · SC 2002
Distributed systems › grid computing data grid	0.0	1	2002	Applying Chimera virtual data concepts to cluster finding in the Sloan Sky Survey · SC 2002
Distributed systems › workflow management workflow orchestration	0.0	1	2002	Applying Chimera virtual data concepts to cluster finding in the Sloan Sky Survey · SC 2002
High-performance computing distributed computing infrastructure	0.0	1	2004	The Grid2003 Production Grid: Principles and Practice · HPDC 2004
Computational science and engineering astronomy	0.0	1	2003	Grid-Based Galaxy Morphology Analysis for the National Virtual Observatory · SC 2003
Computational science and engineering › astronomy astronomical data analysis	0.0	1	2002	Applying Chimera virtual data concepts to cluster finding in the Sloan Sky Survey · SC 2002

Methods — techniques the papers use, named apart from their topics

workflow management · 0.1grid computing · 0.1database-driven provenance tracking · 0.1

Year	Publication	Venue	Position
2005	When Database Systems Meet the Grid María A. Nieto-Santisteban, Jim Gray 0001, Alex Szalay, James Annis, Ani Thakar, William O'Mullane	CIDR	4
2004	The Grid2003 Production Grid: Principles and Practice Ian T. Foster, Jerry Gieraltowski, Scott Gose, Natalia Maltsev, Edward N. May, Alexis A. Rodriguez, Dinanath Sulakhe, A. Vaniachine, Jim Shank, Saul Youssef, David Adams, Richard Baker 0003, Wensheng Deng, Dantong Yu, Iosif Legrand, Conrad Steenberg, M. Anzar Afaq, Eileen Berman, James Annis, L. A. T. Bauerdick, Michael Ernst, Ian Fisk, Lisa Giacchetti, Gregory E. Graham, Anne Heavey, Joseph Kaiser, Nickolai Kuropatkin, Ruth Pordes, Vijay Sekhri, John Weigand, Yujun Wu, Keith Baker, Lawrence Sorrillo, John Huth, Matthew Allen, Leigh Grundhoefer, John Hicks, Fred Luehring, Steve Peck, Robert Quick, Stephen C. Simms, George Fekete, Jan vandenBerg, Kihyeon Cho, Kihwan Kwon, Dongchul Son, Hyoungwoo Park, Shane Canon, Keith R. Jackson, David E. Konerding, Jason Lee 0001, Doug Olson, Iwona Sakrejda, Brian Tierney, Mark Green 0001, Russ Miller, James Letts, Terrence Martin, David Bury, Catalin Dumitrescu, Daniel Engh, Robert W. Gardner, Marco Mambelli, Yuri Smirnov, Jens-S. Vöckler, Michael Wilde, Yong Zhao 0009, Paul Avery, Richard Cavanaugh, Bockjoo Kim, Craig Prescott, Jorge Rodríguez 0002, Andrew Zahn, Shawn McKee, Christopher T. Jordan, James E. Prewett, Timothy L. Thomas, Horst Severini, Ben Clifford, Ewa Deelman, Larry Flon, Carl Kesselman, Gaurang Mehta, Nosa Olomu, Karan Vahi, Kaushik De, Patrick McGuigan, Mark Sosebee, Dan Bradley, Peter Couvares, Alan DeSmet, Carey Kireyev, Erik Paulson 0001, Alain J. Roy, Scott Koranda, Brian Moe, Bobby Brown, Paul Sheldon	HPDC	22
2003	Grid-Based Galaxy Morphology Analysis for the National Virtual Observatory abstract As part of the development of the National Virtual Observatory (NVO), a Data Grid for astronomy, we have developed a prototype science application to explore the dynamical history of galaxy clusters by analyzing the galaxies' morphologies. The purpose of the prototype is to investigate how Grid-based technologies can be used to provide specialized computational services within the NVO environment. In this paper we focus on the key enabling technology components, particularly Chimera and Pegasus which are used to create and manage the computational workflow that must be present to deal with the challenging application requirements. We illustrate how the components interplay with each other and can be driven from a special purpose application portal. Ewa Deelman, Raymond Plante, Carl Kesselman, Mei-Hui Su, Gretchen Greene, Robert J. Hanisch, Niall Gaffney, Antonio Volpicelli, James Annis, Vijay Sekhri, Tamás Budavári, María A. Nieto-Santisteban, William O'Mullane, David Bohlender, Tom McGlynn, Arnold H. Rots, Olga Pevunova	SC	10
2002	Applying Chimera virtual data concepts to cluster finding in the Sloan Sky Survey abstract In many scientific disciplines — especially long running, data- intensive collaborations — it is important to track all aspects of data capture, production, transformation, and analysis. In principle, one can then audit, validate, reproduce, and/or re-run with corrections various data transformations. We have recently proposed and prototyped the Chimera virtual data system, a new database-driven approach to this problem. We present here a major application study in which we apply Chimera to a challenging data analysis problem: the identification of galaxy clusters within the Sloan Digital Sky Survey. We describe the problem, its computational procedures, and the use of Chimera to plan and orchestrate the workflow of thousands of tasks on a data grid comprising hundreds of computers. This experience suggests that a general set of tools can indeed enhance the accuracy and productivity of scientific data reduction and that further development and application of this paradigm will offer great value. James Annis, Yong Zhao 0009, Jens-S. Vöckler, Michael Wilde, Steve Kent, Ian T. Foster	SC	1