His primary scientific interests are in Workflow, Data science, XML, Information retrieval and Ontology. Shawn Bowers has included themes like Reuse and Component in his Workflow study. The study incorporates disciplines such as World Wide Web, Darwin Core, Set and Data discovery in addition to Data science.
His XML research is multidisciplinary, relying on both Theoretical computer science, RDF, Topic Maps and Metamodeling. His Information retrieval research includes themes of Data integration and Ecological Metadata Language. His Ontology research includes elements of Ecology, Biodiversity, Data mapping and Data element.
Shawn Bowers mostly deals with Workflow, Data science, Information retrieval, Workflow technology and Workflow engine. Shawn Bowers integrates Workflow and Provenance in his studies. His Data science study also includes
The Information retrieval study combines topics in areas such as Data mining and Database. His study in Workflow technology is interdisciplinary in nature, drawing from both Workflow management system and Data lineage. His research integrates issues of Programming language and Dependency graph in his study of Workflow engine.
Shawn Bowers mainly focuses on Workflow, Answer set programming, Data dependency, Data mining and Natural language processing. Particularly relevant to Workflow engine is his body of work in Workflow. His biological study spans a wide range of topics, including Distributed computing, Dataflow, Workflow technology, Perl and Workflow management system.
His Answer set programming research focuses on Theoretical computer science and how it connects with White box. Shawn Bowers has researched Data mining in several fields, including Automated theorem proving and Logical consequence. His Natural language processing study combines topics from a wide range of disciplines, such as Identifier, Scalability and Artificial intelligence.
His primary areas of investigation include Artificial intelligence, Congruence, Region connection calculus, Natural language processing and Workflow. His work deals with themes such as Scalability, Species level, Information integration and Answer set programming, which intersect with Artificial intelligence. His Scalability research is multidisciplinary, incorporating perspectives in Imperfect, Ostensive definition and Bioinformatics.
Shawn Bowers combines subjects such as Identifier, Pairwise comparison, Ontology alignment and Knowledge representation and reasoning with his study of Answer set programming. With his scientific publications, his incorporates both Congruence and Data mining. His work on Workflow engine as part of general Workflow study is frequently linked to Directory, therefore connecting diverse disciplines of science.
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An ontology for describing and synthesizing ecological observation data
Ecological Informatics (2007)
The New Bioinformatics: Integrating Ecological Data from the Gene to the Biosphere
Matthew B. Jones;Mark P. Schildhauer;O. J. Reichman;Shawn Bowers.
Annual Review of Ecology, Evolution, and Systematics (2006)
The First Provenance Challenge
Luc Moreau;Bertram Ludaescher;Ilkay Altintas;Roger S. Barga.
Special Issue: The First Provenance Challenge
Luc Moreau;Bertram Ludäscher;Ilkay Altintas;Roger S. Barga.
Concurrency and Computation: Practice and Experience (2008)
Provenance in Scientific Workflow Systems
Susan B. Davidson;Sarah Cohen Boulakia;Anat Eyal;Bertram Ludäscher.
IEEE Data(base) Engineering Bulletin (2007)
Scientific workflow design for mere mortals
Timothy McPhillips;Shawn Bowers;Daniel Zinn;Bertram Ludäscher.
Future Generation Computer Systems (2009)
An Ontology-Driven Framework for Data Transformation in Scientific Workflows
Shawn Bowers;Bertram Ludäscher.
data integration in the life sciences (2004)
Actor-oriented design of scientific workflows
Shawn Bowers;Bertram Ludäscher.
Lecture Notes in Computer Science (2005)
Advancing ecological research with ontologies
Trends in Ecology and Evolution (2008)
Scientific Workflows: Business as Usual?
Bertram Ludäscher;Mathias Weske;Timothy Mcphillips;Shawn Bowers.
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