D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 72 Citations 24,461 256 World Ranking 705 National Ranking 427

Research.com Recognitions

Awards & Achievements

2019 - Fellow of the American Association for the Advancement of Science (AAAS)

2018 - IEEE Fellow For contributions to scientific workflow management

Overview

What is she best known for?

The fields of study she is best known for:

  • Operating system
  • Artificial intelligence
  • Database

Ewa Deelman mainly focuses on Workflow, Workflow management system, Distributed computing, Workflow technology and Data science. Her Workflow research incorporates elements of Grid computing, Scheduling, Cloud computing and Software engineering. Her study in Workflow management system is interdisciplinary in nature, drawing from both Executable, Data management, Workflow engine, Computation and Distributed Computing Environment.

Her Workflow engine study deals with Task intersecting with Cluster analysis. Her work carried out in the field of Distributed computing brings together such families of science as Programming language, Compiler, Scalability and Data grid. Her Data science research is multidisciplinary, incorporating elements of Transparency and Application software.

Her most cited work include:

  • GW170104: Observation of a 50-Solar-Mass Binary Black Hole Coalescence at Redshift 0.2 (1948 citations)
  • Pegasus: A framework for mapping complex scientific workflows onto distributed systems (1072 citations)
  • Workflows and e-Science: An overview of workflow system features and capabilities (670 citations)

What are the main themes of her work throughout her whole career to date?

Ewa Deelman mainly investigates Workflow, Distributed computing, Workflow management system, Cloud computing and Data science. She interconnects Grid, Grid computing, Scheduling and Software engineering in the investigation of issues within Workflow. Her work focuses on many connections between Grid computing and other disciplines, such as Semantic grid, that overlap with her field of interest in Metadata.

Her Distributed computing research integrates issues from Resource allocation, Resource management, Cluster analysis, Resource and Provisioning. Ewa Deelman has researched Workflow management system in several fields, including Scalability, Data management, Task, Workflow engine and Workflow technology. Her work on Windows Workflow Foundation and Workflow Management Coalition as part of general Workflow technology study is frequently linked to Event-driven process chain, therefore connecting diverse disciplines of science.

She most often published in these fields:

  • Workflow (57.30%)
  • Distributed computing (27.53%)
  • Workflow management system (26.40%)

What were the highlights of her more recent work (between 2016-2021)?

  • Workflow (57.30%)
  • Distributed computing (27.53%)
  • Workflow management system (26.40%)

In recent papers she was focusing on the following fields of study:

Her main research concerns Workflow, Distributed computing, Workflow management system, Software engineering and Data science. Her Workflow study integrates concerns from other disciplines, such as Supercomputer, Set, Task, Resource and Cloud computing. Her work deals with themes such as Scheduling, Provisioning, File system and Resource management, which intersect with Distributed computing.

The various areas that Ewa Deelman examines in her Workflow management system study include Software deployment, Workflow engine, RAID, Software and Checksum. The concepts of her Software engineering study are interwoven with issues in Term, Container, Feature and Distributed database. Ewa Deelman has included themes like Domain, Workflow technology, Key and Knowledge sharing in her Data science study.

Between 2016 and 2021, her most popular works were:

  • GW170104: Observation of a 50-Solar-Mass Binary Black Hole Coalescence at Redshift 0.2 (1948 citations)
  • Genetic analyses of diverse populations improves discovery for complex traits (209 citations)
  • The future of scientific workflows (65 citations)

In her most recent research, the most cited papers focused on:

  • Operating system
  • Artificial intelligence
  • Software

Workflow, Distributed computing, Workflow management system, Genomics and Genome-wide association study are her primary areas of study. Her Workflow technology study, which is part of a larger body of work in Workflow, is frequently linked to Automation, bridging the gap between disciplines. She combines subjects such as Workflow engine and Computational science with her study of Workflow technology.

The Distributed computing study combines topics in areas such as Resource, Bottleneck, File system and Resource management. Her Workflow management system research incorporates themes from Software and Software engineering. Her studies examine the connections between Data science and genetics, as well as such issues in Domain, with regards to Key, Panorama, Testbed and Use case.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

GW170104: Observation of a 50-Solar-Mass Binary Black Hole Coalescence at Redshift 0.2

B. P. Abbott;R. Abbott;T. D. Abbott;F. Acernese.
Physical Review Letters (2017)

2071 Citations

Pegasus: A framework for mapping complex scientific workflows onto distributed systems

Ewa Deelman;Gurmeet Singh;Mei-Hui Su;James Blythe.
Scientific Programming (2005)

1530 Citations

Workflows and e-Science: An overview of workflow system features and capabilities

Ewa Deelman;Dennis Gannon;Matthew Shields;Ian Taylor.
Future Generation Computer Systems (2009)

1163 Citations

Workflows for e-Science: Scientific Workflows for Grids

Ian J. Taylor;Ewa Deelman;Dennis B. Gannon;Matthew Shields.
(2014)

917 Citations

The cost of doing science on the cloud: the Montage example

Ewa Deelman;Gurmeet Singh;Miron Livny;Bruce Berriman.
ieee international conference on high performance computing data and analytics (2008)

871 Citations

Examining the Challenges of Scientific Workflows

Y. Gil;E. Deelman;M. Ellisman;T. Fahringer.
IEEE Computer (2007)

733 Citations

Pegasus: Mapping Scientific Workflows onto the Grid

Ewa Deelman;James Blythe;Yolanda Gil;Carl Kesselman.
Lecture Notes in Computer Science (2004)

693 Citations

Mapping Abstract Complex Workflows onto Grid Environments

Ewa Deelman;James Blythe;Yolanda Gil;Carl Kesselman.
Journal of Grid Computing (2003)

657 Citations

Characterization of scientific workflows

S. Bharathi;A. Chervenak;E. Deelman;G. Mehta.
workflows in support of large-scale science (2008)

601 Citations

Characterizing and profiling scientific workflows

Gideon Juve;Ann Chervenak;Ewa Deelman;Shishir Bharathi.
Future Generation Computer Systems (2013)

599 Citations

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