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 94 Citations 42,356 190 World Ranking 210 National Ranking 128

Research.com Recognitions

Awards & Achievements

2008 - ACM Software System Award For Gamma, the first embodiment of a parallel, "shared nothing" database system running on a cluster of commodity computers, using data partitioning and innovative parallel query execution strategies.

2007 - Fellow of the American Academy of Arts and Sciences

1998 - Member of the National Academy of Engineering For the theory and construction of database systems.

1995 - ACM Fellow For fundamental contributions to the areas of parallel database systems, database system benchmarking, and object-oriented database systems, and for outstanding service as an educator and a technical leader.

Overview

What is he best known for?

The fields of study he is best known for:

  • Operating system
  • Database
  • Programming language

His main research concerns Database, Parallel computing, Database design, Relational database and View. David J. DeWitt specializes in Database, namely Scalability. His work deals with themes such as Data model and Relational database management system, which intersect with Database design.

His research investigates the connection between Relational database management system and topics such as Database model that intersect with issues in Oracle. His study in the field of Database machine is also linked to topics like Tuple. His View study deals with Query language intersecting with RDF query language, XML, XML schema, Binary XML and Document type definition.

His most cited work include:

  • Parallel database systems: the future of high performance database systems (1271 citations)
  • NiagaraCQ: a scalable continuous query system for Internet databases (1126 citations)
  • A comparison of approaches to large-scale data analysis (1008 citations)

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

David J. DeWitt mainly focuses on Database, Data mining, Parallel computing, Database design and Query optimization. His study in View, Database tuning, Relational database management system, Database machine and SQL is carried out as part of his studies in Database. In his study, File system and Class is inextricably linked to Scalability, which falls within the broad field of Data mining.

His work on Multiprocessing, Parallel database, Cache and Parallelism as part of general Parallel computing study is frequently linked to Tuple, therefore connecting diverse disciplines of science. His Query optimization study integrates concerns from other disciplines, such as Query language, Web search query, Sargable and Query expansion. His work carried out in the field of Query language brings together such families of science as Spatial query and Web query classification.

He most often published in these fields:

  • Database (34.18%)
  • Data mining (14.35%)
  • Parallel computing (13.92%)

What were the highlights of his more recent work (between 2004-2020)?

  • Database (34.18%)
  • Scalability (10.55%)
  • Data mining (14.35%)

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

His scientific interests lie mostly in Database, Scalability, Data mining, Data management and Distributed computing. David J. DeWitt incorporates Database and Tuple in his studies. His studies deal with areas such as Database index, Search engine indexing and Anonymity as well as Data mining.

His Data management study also includes fields such as

  • Workflow technology that connect with fields like Computer cluster,
  • Workflow which intersects with area such as Parallel database. His research investigates the connection with Distributed computing and areas like Query expansion which intersect with concerns in Database server and Gigabyte. In his study, Query language is strongly linked to Query optimization, which falls under the umbrella field of Web query classification.

Between 2004 and 2020, his most popular works were:

  • A comparison of approaches to large-scale data analysis (1008 citations)
  • Incognito: efficient full-domain K-anonymity (926 citations)
  • Mondrian Multidimensional K-Anonymity (888 citations)

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

  • Operating system
  • Database
  • Programming language

His primary scientific interests are in Database, Data mining, Scalability, SQL and Data management. His work on Data model as part of his general Database study is frequently connected to Turbocharger, thereby bridging the divide between different branches of science. David J. DeWitt has included themes like Workload, Factor and Anonymity in his Data mining study.

The study incorporates disciplines such as Big data, Database index, Search engine indexing and Table in addition to Scalability. The SQL study which covers Relational database management system that intersects with Language Integrated Query, Query by Example, Unstructured data, Query language and Spatial query. David J. DeWitt combines subjects such as Database theory, Database design, Database testing, Physical data model and Data science with his study of Data management.

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

Parallel database systems: the future of high performance database systems

David DeWitt;Jim Gray.
Communications of The ACM (1992)

1924 Citations

The Object-Oriented Database System Manifesto.

Malcolm P. Atkinson;François Bancilhon;David J. DeWitt;Klaus R. Dittrich.
DOOD (1989)

1847 Citations

Relational Databases for Querying XML Documents: Limitations and Opportunities

Jayavel Shanmugasundaram;Kristin Tufte;Chun Zhang;Gang He.
very large data bases (1999)

1757 Citations

NiagaraCQ: a scalable continuous query system for Internet databases

Jianjun Chen;David J. DeWitt;Feng Tian;Yuan Wang.
international conference on management of data (2000)

1673 Citations

Incognito: efficient full-domain K-anonymity

Kristen LeFevre;David J. DeWitt;Raghu Ramakrishnan.
international conference on management of data (2005)

1508 Citations

A comparison of approaches to large-scale data analysis

Andrew Pavlo;Erik Paulson;Alexander Rasin;Daniel J. Abadi.
international conference on management of data (2009)

1474 Citations

Mondrian Multidimensional K-Anonymity

K. LeFevre;D.J. DeWitt;R. Ramakrishnan.
international conference on data engineering (2006)

1352 Citations

On supporting containment queries in relational database management systems

Chun Zhang;Jeffrey Naughton;David DeWitt;Qiong Luo.
international conference on management of data (2001)

1303 Citations

Implementation techniques for main memory database systems

David J DeWitt;Randy H Katz;Frank Olken;Leonard D Shapiro.
international conference on management of data (1984)

1209 Citations

The Gamma database machine project

D.J. DeWitt;S. Ghandeharizadeh;D.A. Schneider;A. Bricker.
IEEE Transactions on Knowledge and Data Engineering (1990)

973 Citations

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