Thomas C. Redman

26 papers receiving 1.3k citations

Peers

Thomas C. Redman
Comparison fields: 5 of 122
  • Management Science and Operations Research 1.1k
  • Management Information Systems 766
  • Information Systems 536
  • Information Systems and Management 135
  • Health Information Management 52
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Citations per year

Countries citing papers authored by Thomas C. Redman

Since Specialization
Citations

This map shows the geographic impact of Thomas C. Redman's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Thomas C. Redman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas C. Redman more than expected).

Fields of papers citing papers by Thomas C. Redman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Thomas C. Redman. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Thomas C. Redman. The network helps show where Thomas C. Redman may publish in the future.

Co-authors

The 21 scholars most cited alongside Thomas C. Redman, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Thomas C. Redman Line = papers co-authored together Thomas C. Redman links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1998438
2
Data Quality For The Information Age
1997404
3 1994174
4
Data Quality: The Field Guide
2001169
5
Improve Data Quality for Competitive Advantage
1995118
6 1994108
7 200967
8 199324
9 199520
10 198717
11 201915
12 198014
13 201910
14 20224
15
Electrophoretic gel image analysis software for the molecular biology laboratory.
19914
16 20143
17 19823
18
Data Quality: Should Universities Worry?.
20042
19 19842
20
Genetic wrappers for constructive induction in high-performance data mining
20002

About Thomas C. Redman

Thomas C. Redman is a scholar working on Management Science and Operations Research, Management Information Systems, Artificial Intelligence, Information Systems and Electrical and Electronic Engineering, having authored 28 papers that have together received 1.6k indexed citations. Recurring topics across this work include Data Quality and Management (12 papers), Big Data and Business Intelligence (8 papers), Data Mining Algorithms and Applications (3 papers), Advanced Database Systems and Queries (3 papers), Power Line Communications and Noise (2 papers), Cognitive Science and Mapping (2 papers), Air Quality and Health Impacts (2 papers) and Genetics, Bioinformatics, and Biomedical Research (1 paper). The work is most often cited by research in Management Science and Operations Research (1.1k citations), Management Information Systems (766 citations), Information Systems (536 citations), Information Systems and Management (135 citations) and Health Information Management (52 citations). Thomas C. Redman has collaborated with scholars based in United States, Germany and Australia. Frequent co-authors include A. Blanton Godfrey, Anany Levitin, Chris Fox, Thomas M. Margavio, Alan R. Zinsmeister, Ron S. Kenett, Divesh Srivastava, Monica Scannapieco, Roger W. Hoerl and Michael Welge. Their work appears in journals such as Quality Engineering, Journal of Data and Information Quality, Information Processing & Management, Communications of the ACM and Journal of the Association for Information Systems.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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