Provenance in Data Science | From Data Models to Context-Aware Knowledge Graphs
Idioma: inglés
Editorial: Springer, 2022
Serie: Libro 65 de 66 - Advanced Information and Knowledge Processing
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Provenance in Data Science | From Data Models to Context-Aware Knowledge Graphs | Leslie F. Sikos (u. a.) | Taschenbuch | Advanced Information and Knowledge Processing | xi | Englisch | 2022 | Springer | EAN 9783030676834 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
N° de ref. del artículo 121394529
- Título
- Provenance in Data Science | From Data Models to Context-Aware Knowledge Graphs
- Autor
- Leslie F. Sikos (u. a.)
- Editorial
- Springer
- Año de publicación
- 2022
- Estado
- Neu
- Encuadernación
- Taschenbuch
- Idioma
- inglés
- ISBN 10
- 3030676838
- ISBN 13
- 9783030676834
- Peso del artículo
- 201 gramos
- Dimensiones
- 235 x 155 x 8 mm
- Serie
- Libro 65 de 66: Advanced Information and Knowledge Processing
- Catálogos de vendedores
- Bücher
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Acerca del autor
Dr. Oshani W. Seneviratne is the Director of Health Data Research at the Institute for Data Exploration and Applications at the Rensselaer Polytechnic Institute (Rensselaer IDEA). She obtained her Ph.D. in Computer Science from Massachusetts Institute of Technology in 2014 under the supervision of Sir Tim Berners-Lee, the inventor of the World Wide Web. During her Ph.D., Oshani researched Accountable Systems for the Web. She invented a novel web protocol called HTTPA (HyperText Transfer Protocol with Accountability), and a novel provenance tracking mechanism called the Provenance Tracking Network. This work was demonstrated to be effective in several domains including electronic health care records transfer, and intellectual property protection in Web-based decentralized systems. At Rensselaer IDEA, Oshani leads the Smart Contracts Augmented with Analytics Learning and Semantics (SCALeS) project. The goal of this project is to predict, detect, and fix initially unforeseen situations in smart contracts utilizing novel combinations of machine learning, program analysis, and semantic technologies. Oshani is also involved in the Health Empowerment by Analytics, Learning, and Semantics (HEALS) Project. In HEALS she oversees the research operations targeted at the characterization and analysis of computational medical guidelines for chronic diseases such as diabetes, and the modeling of guideline provenance. Before Rensselaer, Oshani worked at Oracle specializing in distributed systems, provenance and healthcare-related research. She is the co-inventor of two enterprise provenance patents.
Prof. Deborah L. McGuinness is the Tetherless World Senior Constellation Chair and Professor of Computer, Cognitive, and Web Sciences at RPI. She is also the founding director of the Web Science Research Center and the CEO of McGuinness Associates Consulting. Deborah has been recognized with awards as a fellow of the American Association for the Advancement of Science (AAAS) for contributions to the Semantic Web, knowledge representation, and reasoning environments and as the recipient of the Robert Engelmore Award from the Association for the Advancement of Artificial Intelligence (AAAI) for leadership in Semantic Web research and in bridging Artificial Intelligence (AI) and eScience, significant contributions to deployed AI applications, and extensive service to the AI community. Deborah leads a number of large diverse data intensive resource efforts and her team is creating next-generation ontology-enabled research infrastructure for work in large interdisciplinary settings. Prior to joining RPI, Deborah was the acting director of the Knowledge Systems, Artificial Intelligence Laboratory and Senior Research Scientist in the Computer Science Department of Stanford University, and previous to that she was at AT\&T Bell Laboratories. Deborah consults with numerous large corporations as well as emerging startup companies wishing to plan, develop, deploy, and maintain semantic web and/or AI applications. Some areas of recent work include data science, next generation health advisors, ontology design and evolution environments, semantically enabled virtual observatories, semantic integration of scientific data, context-aware mobile applications, search, eCommerce, configuration, and supply chain management. Deborah holds a Bachelor of Math and Computer Science from Duke University, a Master of Computer Science from University of California at Berkeley, and a Ph.D. in Computer Science from Rutgers University.
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